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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 05 Nov 2012 14:40:36 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/05/t1352144546rnlrc7qwgybl4bd.htm/, Retrieved Sun, 05 Feb 2023 23:17:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=186260, Retrieved Sun, 05 Feb 2023 23:17:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2012-11-05 19:40:36] [1d663168d22fd6b8a85a991d8b072eec] [Current]
- R  D    [Multiple Regression] [multiple regression] [2012-12-12 20:47:29] [596b77fae3c3637cb35f2a3968c5e5d1]
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Dataseries X:
58,58527778	79	30	112285
33,60611111	58	28	84786
49,03	60	38	83123
49,81138889	108	30	101193
34,21805556	49	22	38361
14,65166667	0	26	68504
107,0927778	121	25	119182
9,213888889	1	18	22807
28,23472222	20	11	17140
41,40583333	43	26	116174
45,95722222	69	25	57635
65,8925	78	38	66198
48,14611111	86	44	71701
36,98083333	44	30	57793
71,90916667	104	40	80444
50,02305556	63	34	53855
90,22194444	158	47	97668
64,15666667	102	30	133824
65,77361111	77	31	101481
37,63138889	82	23	99645
56,36805556	115	36	114789
59,76305556	101	36	99052
95,63805556	80	30	67654
42,75972222	50	25	65553
36,92861111	83	39	97500
48,53444444	123	34	69112
48,44861111	73	31	82753
62,65222222	81	31	85323
62,12	105	33	72654
34,67138889	47	25	30727
61,58277778	105	33	77873
58,54638889	94	35	117478
47,29611111	44	42	74007
72,37805556	114	43	90183
23,57027778	38	30	61542
81,78444444	107	33	101494
28,05861111	30	13	27570
59,90027778	71	32	55813
90,3075	84	36	79215
1,993333333	0	0	1423
46,53944444	59	28	55461
29,55777778	33	14	31081
26,82222222	42	17	22996
73,82472222	96	32	83122
74,90305556	106	30	70106
41,42	56	35	60578
48,84	57	20	39992
42,46416667	59	28	79892
31,01805556	39	28	49810
32,33555556	34	39	71570
100,6391667	76	34	100708
21,88888889	20	26	33032
50,87972222	91	39	82875
77,2125	115	39	139077
41,84138889	85	33	71595
46,89138889	76	28	72260
6,718888889	8	4	5950
91,46305556	79	39	115762
18,06361111	21	18	32551
28,0825	30	14	31701
60,81833333	76	29	80670
67,79222222	101	44	143558
94,88055556	94	21	117105
28,77694444	27	16	23789
64,81333333	92	28	120733
71,23944444	123	35	105195
57,26694444	75	28	73107
86,52027778	128	38	132068
65,5	105	23	149193
49,4275	55	36	46821
57,54888889	56	32	87011
54,59805556	41	29	95260
48,38444444	72	25	55183
39,79055556	67	27	106671
52,09972222	75	36	73511
52,13361111	114	28	92945
33,06	118	23	78664
50,60888889	77	40	70054
20,435	22	23	22618
54,16083333	66	40	74011
46,52444444	69	28	83737
39,93222222	105	34	69094
76,53916667	116	33	93133
67,55527778	88	28	95536
50,83305556	73	34	225920
37,68027778	99	30	62133
42,30527778	62	33	61370
33,39472222	53	22	43836
96,24583333	118	38	106117
40,49722222	30	26	38692
53,70527778	100	35	84651
22,48694444	49	8	56622
34,10388889	24	24	15986
36,27361111	67	29	95364
31,28083333	46	20	26706
79,57444444	57	29	89691
66,96277778	75	45	67267
41,235	135	37	126846
56,86472222	68	33	41140
50,5775	124	33	102860
38,98444444	33	25	51715
61,25444444	98	32	55801
67,51666667	58	29	111813
45,2125	68	28	120293
50,72583333	81	28	138599
64,48277778	131	31	161647
73,69944444	110	52	115929
23,77055556	37	21	24266
86,34416667	130	24	162901
62,51666667	93	41	109825
64,5325	118	33	129838
40,26833333	39	32	37510
12,02416667	13	19	43750
43,265	74	20	40652
45,7525	81	31	87771
56,09444444	109	31	85872
65,40388889	151	32	89275
61,33361111	51	18	44418
27,62944444	28	23	192565
25,73916667	40	17	35232
37,03555556	56	20	40909
17,04472222	27	12	13294
34,98055556	37	17	32387
27,98611111	83	30	140867
62,37472222	54	31	120662
22,86555556	27	10	21233
28,33611111	28	13	44332
28,20083333	59	22	61056
67,64194444	133	42	101338
6,371666667	12	1	1168
11,54611111	0	9	13497
42,35388889	106	32	65567
17,1825	23	11	25162
27,75638889	44	25	32334
36,80194444	71	36	40735
88,165	116	31	91413
5,848333333	4	0	855
58,23361111	62	24	97068
6,291111111	12	13	44339
8,726111111	18	8	14116
12,97166667	14	13	10288
36,58277778	60	19	65622
25,48194444	7	18	16563
67,98583333	98	33	76643
51,25277778	64	40	110681
22,18416667	29	22	29011
35,67305556	32	38	92696
27,1775	25	24	94785
10,615	16	8	8773
41,9725	48	35	83209
75,68277778	100	43	93815
47,915	46	43	86687
30,01194444	45	14	34553
91,14083333	129	41	105547
69,60527778	130	38	103487
97,51861111	136	45	213688
43,89305556	59	31	71220
27,46277778	25	13	23517
23,73305556	32	28	56926
63,67833333	63	31	91721
97,67194444	95	40	115168
23,39083333	14	30	111194
33,45694444	36	16	51009
90,16611111	113	37	135777
36,40805556	47	30	51513
56,74194444	92	35	74163
45,98416667	70	32	51633
39,36722222	19	27	75345
32,23555556	50	20	33416
69,4575	41	18	83305
83,27083333	91	31	98952
54,39944444	111	31	102372
48,12777778	41	21	37238
70,69111111	120	39	103772
28,99694444	135	41	123969
37,80111111	27	13	27142
55,41	87	32	135400
25,69416667	25	18	21399
62,31388889	131	39	130115
37,71694444	45	14	24874
20,66888889	29	7	34988
22,56666667	58	17	45549
4,08	4	0	6023
50,45361111	47	30	64466
75,51555556	109	37	54990
1,999722222	7	0	1644
12,96111111	12	5	6179
4,874166667	0	1	3926
37,04666667	37	16	32755
26,45194444	37	32	34777
42,38916667	46	24	73224
27,26277778	15	17	27114
22,11638889	42	11	20760
16,44277778	7	24	37636
38,87277778	54	22	65461
32,94777778	54	12	30080
20,24444444	14	19	24094
18,1875	16	13	69008
27,67861111	33	17	54968
19,99027778	32	15	46090
21,46444444	21	16	27507
13,69138889	15	24	10672
37,53638889	38	15	34029
30,12388889	22	17	46300
24,92944444	28	18	24760
12,30444444	10	20	18779
21,56888889	31	16	21280
50,42444444	32	16	40662
37,2275	32	18	28987
34,46222222	43	22	22827
25,73055556	27	8	18513
33,84666667	37	17	30594
14,69861111	20	18	24006
22,74222222	32	16	27913
16,38361111	0	23	42744
14,86527778	5	22	12934
16,89222222	26	13	22574
15,65972222	10	13	41385
18,19166667	27	16	18653
22,48583333	11	16	18472
21,195	29	20	30976
28,89194444	25	22	63339
27,25111111	55	17	25568
18,88583333	23	18	33747
8,608055556	5	17	4154
37,62722222	43	12	19474
20,41777778	23	7	35130
17,53416667	34	17	39067
17,015	36	14	13310
20,80944444	35	23	65892
8,826111111	0	17	4143
22,62138889	37	14	28579
24,21833333	28	15	51776
13,91388889	16	17	21152
18,2625	26	21	38084
15,73694444	38	18	27717
43,99972222	23	18	32928
12,90416667	22	17	11342
20,45111111	30	17	19499
10,66527778	16	16	16380
25,5275	18	15	36874
38,75722222	28	21	48259
14,49	32	16	16734
14,32416667	21	14	28207
19,5975	23	15	30143
23,57111111	29	17	41369
28,48277778	50	15	45833
24,07722222	12	15	29156
23,80805556	21	10	35944
9,628333333	18	6	36278
41,82777778	27	22	45588
27,66972222	41	21	45097
5,374722222	13	1	3895
27,60361111	12	18	28394
23,95277778	21	17	18632
8,565833333	8	4	2325
8,807222222	26	10	25139
24,94611111	27	16	27975
17,24666667	13	16	14483
11,15305556	16	9	13127
7,676111111	2	16	5839
21,38611111	42	17	24069
10,40555556	5	7	3738
15,04361111	37	15	18625
13,85055556	17	14	36341
23,42694444	38	14	24548
17,82638889	37	18	21792
16,495	29	12	26263
33,14111111	32	16	23686
21,30611111	35	21	49303
28,72916667	17	19	25659
19,54	20	16	28904
12,05833333	7	1	2781
29,12166667	46	16	29236
17,28194444	24	10	19546
19,25111111	40	19	22818
14,75472222	3	12	32689
5,49	10	2	5752
24,07777778	37	14	22197
23,3625	17	17	20055
21,65138889	28	19	25272
24,75361111	19	14	82206
25,27916667	29	11	32073
11,18	8	4	5444
17,82972222	10	16	20154
14,12694444	15	20	36944
15,72583333	15	12	8019
17,44222222	28	15	30884
20,14861111	17	16	19540




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 14 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=186260&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=186260&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186260&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.







Multiple Linear Regression - Estimated Regression Equation
UREN[t] = + 4.08354824245505 + 0.318850258329672blogged_computations[t] + 0.492731537367996compendiums_reviewed[t] + 0.000106006678565742`totsize\r`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
UREN[t] =  +  4.08354824245505 +  0.318850258329672blogged_computations[t] +  0.492731537367996compendiums_reviewed[t] +  0.000106006678565742`totsize\r`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186260&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]UREN[t] =  +  4.08354824245505 +  0.318850258329672blogged_computations[t] +  0.492731537367996compendiums_reviewed[t] +  0.000106006678565742`totsize\r`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186260&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186260&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
UREN[t] = + 4.08354824245505 + 0.318850258329672blogged_computations[t] + 0.492731537367996compendiums_reviewed[t] + 0.000106006678565742`totsize\r`[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.083548242455051.6920622.41340.0164370.008219
blogged_computations0.3188502583296720.0324999.811200
compendiums_reviewed0.4927315373679960.1083074.54948e-064e-06
`totsize\r`0.0001060066785657422.8e-053.74660.0002170.000108

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 4.08354824245505 & 1.692062 & 2.4134 & 0.016437 & 0.008219 \tabularnewline
blogged_computations & 0.318850258329672 & 0.032499 & 9.8112 & 0 & 0 \tabularnewline
compendiums_reviewed & 0.492731537367996 & 0.108307 & 4.5494 & 8e-06 & 4e-06 \tabularnewline
`totsize\r` & 0.000106006678565742 & 2.8e-05 & 3.7466 & 0.000217 & 0.000108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186260&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]4.08354824245505[/C][C]1.692062[/C][C]2.4134[/C][C]0.016437[/C][C]0.008219[/C][/ROW]
[ROW][C]blogged_computations[/C][C]0.318850258329672[/C][C]0.032499[/C][C]9.8112[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]compendiums_reviewed[/C][C]0.492731537367996[/C][C]0.108307[/C][C]4.5494[/C][C]8e-06[/C][C]4e-06[/C][/ROW]
[ROW][C]`totsize\r`[/C][C]0.000106006678565742[/C][C]2.8e-05[/C][C]3.7466[/C][C]0.000217[/C][C]0.000108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186260&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186260&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.083548242455051.6920622.41340.0164370.008219
blogged_computations0.3188502583296720.0324999.811200
compendiums_reviewed0.4927315373679960.1083074.54948e-064e-06
`totsize\r`0.0001060066785657422.8e-053.74660.0002170.000108







Multiple Linear Regression - Regression Statistics
Multiple R0.860359682284416
R-squared0.740218782900541
Adjusted R-squared0.737484243773178
F-TEST (value)270.692335499486
F-TEST (DF numerator)3
F-TEST (DF denominator)285
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation11.7187938564727
Sum Squared Residuals39139.0868933934

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.860359682284416 \tabularnewline
R-squared & 0.740218782900541 \tabularnewline
Adjusted R-squared & 0.737484243773178 \tabularnewline
F-TEST (value) & 270.692335499486 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 285 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 11.7187938564727 \tabularnewline
Sum Squared Residuals & 39139.0868933934 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186260&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.860359682284416[/C][/ROW]
[ROW][C]R-squared[/C][C]0.740218782900541[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.737484243773178[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]270.692335499486[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]285[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]11.7187938564727[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]39139.0868933934[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186260&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186260&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.860359682284416
R-squared0.740218782900541
Adjusted R-squared0.737484243773178
F-TEST (value)270.692335499486
F-TEST (DF numerator)3
F-TEST (DF denominator)285
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation11.7187938564727
Sum Squared Residuals39139.0868933934







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
158.5852777855.95762467429332.62765310570674
233.6061111145.3612285207549-11.7551174107549
349.0350.7499553046393-1.71995530463934
449.8113888964.0284560872026-14.2170671972026
534.2180555634.6138269191653-0.395771359165287
614.6516666724.1564497224905-9.50478305249051
7107.092777867.616805899367439.4759719006326
89.21388888915.6892604914575-6.47537160245752
928.2347222217.697554790713210.5371674292867
1041.4058333342.9203491978953-1.51451586789529
1145.9572222244.51219942053881.44502279946118
1265.892554.695096919848311.1974030801517
1348.1461111160.7856429628409-12.6395318528409
1436.9808333339.0213497043504-2.04051637435039
1571.9091666765.48083785400336.42832881599674
1650.0230555646.63297646189433.39007909810575
1790.2219444487.97373159699782.24821284300216
1864.1566666765.5744584655032-1.41779179550323
1965.7736111154.667359539777711.1062515702223
2037.6313888952.1251302706354-14.4937413806354
2156.3680555670.6580639214981-14.2900083614981
2259.7630555664.5259332042936-4.76287764429359
2395.6380555651.545290861555444.0927646984446
2442.7597222239.29340539315863.46631682684141
2536.9286111160.1003008013295-23.1716896913295
2648.5344444467.3813358565521-18.8468914165521
2748.4486111151.4066654302798-2.95805432027977
2862.6522222254.22990466083118.42231755916889
2962.1261.52477532472980.595224675270159
3034.6713888934.64506603043910.0263228595609374
3161.5827777862.0780241801644-0.495246400164443
3258.5463888963.7545289178702-5.20814002787024
3347.2961111146.65292043903130.643190670968715
3472.3780555671.17993409195571.19812146804428
3523.5702777837.5056671923153-13.9353894123153
3681.7844444465.219708451225216.5647359887748
3728.0586111122.97717010618665.08144100381336
3859.9002777848.405876530427311.4944012495727
3990.307557.002624329980533.3048756700195
401.9933333334.2343957460541-2.24106241305409
4146.5394444442.57143293014423.96801150985583
4229.5577777824.7986418669884.75913591301203
4326.8222222228.289424807855-1.46720258785499
4473.8247222259.27206937362114.552652846379
4574.9030555660.0953259539714.80772960603
4641.4245.606439090952-4.18643909095202
4748.8436.352062803807412.4879371961926
4842.4641666745.1612820941838-2.6971154241838
4931.0180555635.5953840229757-4.57732846297573
5032.3355555641.7278849679659-9.39232940796586
51100.639166755.744760731020744.8944059689793
5221.8888888926.773185987-4.88429709699996
5350.8797222261.1007551939429-10.2210329739429
5477.212574.71094874260682.50155125739323
5541.8413888955.0355090855353-13.1941201955353
5646.8913888949.7726935149745-2.88130462497447
576.7188888899.23601619603056-2.51712730703056
5891.4630555660.760793731978330.7022618280217
5918.0636111123.0991947339955-5.03558362399554
6028.082523.90781523270974.17468476729028
6160.8183333351.15694121908049.66139211091964
6267.7922222273.1857187394844-5.39349651948445
6394.8805555656.816746903613338.0638086563867
6428.7769444423.09800269164455.67894174835545
6564.8133333360.01275937836644.8005739516336
6671.2394444471.6991063766077-0.459661936607715
6757.2669444449.543630913397.72331352661001
6886.5202777877.62026975345728.90000802654277
6965.564.71110512179320.788894878206835
7049.427544.32198649296145.10551350703856
7157.5488888946.930319013376310.6185698766237
7254.5980555641.54381961781613.054235942184
7348.3844444445.20882181968463.17562262031537
7439.7905555650.0581054687652-10.2675499087652
7552.0997222253.5283099104745-1.42858769047452
7652.1336111164.0817514776344-11.9481403676344
7733.0661.3796134475157-28.3196134475157
7850.6088888955.7704714888041-5.16158259880408
7920.43524.8287383409717-4.39373834097168
8054.1608333352.68258707426231.47824625573767
8146.5244444448.7573803565658-2.23293591656579
8239.9322222261.6401230864038-21.7079008664038
8376.5391666767.2030389367049.33612773329596
8467.5552777856.066308065226711.4889697147733
8550.8330555668.0615181926053-17.2284626326053
8637.6802777857.0181828974576-19.3379051174577
8742.3052777846.6180348556181-4.31275707561813
8833.3947222236.4696145176314-3.07489229763141
8996.2458333371.68078785470124.565045475299
9040.4972222230.56168637097889.93553584902122
9153.7052777862.1877492305707-8.48247145057067
9222.4869444429.6513733533023-7.16442891330235
9334.1038888925.2561341027518.84775478724897
9436.2736111149.8449510289583-13.5713399189583
9531.2808333331.4363052307566-0.155471900756565
9679.5744444446.055072558158133.5193718818418
9766.9627777857.3009880458229.661789734178
9841.23578.8059231489266-37.5709231489266
9956.8647222246.386621298211210.4781009217888
10050.577570.7849679657504-20.2074679657504
10138.9844444432.40603058356146.57841385643855
10261.2544444457.01356142518574.2408830148143
10367.5166666748.719002559719218.7976641102808
10445.212552.3137102398854-7.10121023988536
10550.7258333358.3993218559956-7.67348852599556
10664.4827777878.2632713121663-13.7804935321663
10773.6994444477.0683648413026-3.3689204013026
10823.7705555628.8007281474571-5.03017258745711
10986.3441666774.628232667182111.7159340028179
11062.5166666765.5807987726849-3.06413210268493
11164.532571.7317145901189-7.19921459011893
11240.2683333336.26242802608914.00590530391091
11312.0241666722.2282929979839-10.2041263279839
11443.26541.84248160326521.4225183967348
11545.752554.48940900996-8.73690900996004
11656.0944444463.2159095605945-7.12146512059451
11765.4038888977.4610926749679-12.0572037849679
11861.3336111133.922683738425327.4109273715747
11927.6294444444.7573568931618-17.1279124531618
12025.7391666728.9488220101261-3.20965534012606
12137.0355555636.13042066972250.905134890277491
12217.0447222220.0145364506251-2.96981423062511
12334.9805555627.69068223461757.28987332538249
12427.9861111160.262908594378-32.276797484378
12562.3747222249.367117699764713.0076045202353
12622.8655555619.87066039702252.99489516297747
12728.3361111124.11635353564634.21975757435374
12828.2008333340.2081510725115-12.0073177425115
12967.6419444477.9278619622523-10.2859175222523
1306.3716666678.52629868034388-2.15463201334388
13111.546111119.948904219368821.59720689063118
13242.3538888960.5996247146961-18.2457358246961
13317.182519.5044911411566-2.32199114115664
13427.7563888933.8588679879052-6.1024790979052
13536.8019444448.7784339804851-11.9764895404851
13688.16566.03524437483522.129755625165
1375.8483333335.449584985947440.398748347052562
13858.2336111145.96767743074612.265933679254
1396.29111111119.0154914491215-12.7243803381215
1408.72611111115.2610954659671-6.53498435496711
14112.9716666716.0435585539387-3.07189188393875
14236.5827777839.5328332130684-2.95005543306837
14325.4819444416.94045634047118.54148809952894
14467.9858333359.71568415722098.27014917277913
14551.2527777855.9321514606087-4.67937368060872
14622.1841666727.2456593079822-5.06149263798217
14735.6730555642.8369500053184-7.16389444531838
14827.177533.9282046253826-6.75070462538256
14910.61514.057001265731-3.44200126573101
15041.972545.4546741669359-3.48217416693595
15175.6827777867.10104673189118.5817310481089
15247.91549.1275171772722-1.21251717727222
15330.0119444428.99290015492431.01904428507571
15491.1408333376.605911501648914.5349218283511
15569.6052777875.2281933900291-5.62291561002913
15697.5186111192.27245768620645.24615342379359
15743.8930555645.7201867897657-1.82713122976568
15827.4627777820.95327374631136.50950403368867
15923.7330555634.1177757393418-10.3847201793418
16063.6783333349.168830740360614.5095025896394
16197.6719444466.29216143555331.379783004447
16223.3908333335.1167045965494-11.7258712665494
16333.4569444428.85315680717114.60378763282892
16490.1661111172.737963111944517.4281479980555
16536.4080555639.3121785379466-2.90412297794655
16656.7419444458.5251491191358-1.7832046791358
16745.9841666747.6439183556929-1.65975168569288
16839.3672222231.43252785619057.9346943638095
16932.2355555633.4230110772514-1.18745551725137
17069.457534.856462864514634.6010371354854
17183.2708333358.863172266300324.4076610636997
17254.3994444465.6027202735886-11.2032758335886
17348.1277777831.451247815130616.6765299648694
17470.6911111172.5626342474916-1.87152313749164
17528.9969444480.471868084165-51.474923644165
17637.8011111121.975248472771515.8258626372285
17755.4161.9442341907138-6.53423419071377
17825.6941666723.19240928794912.50175738205093
17962.3138888978.8625210225754-16.5486321325754
18037.7169444427.96686151308659.75008292691352
18120.6688888920.48828816524970.180600724750338
18222.5666666735.7817975628229-13.2151308928229
1834.085.99742750077519-1.91742750077519
18450.4536111140.68528304540869.76832806459139
18575.5155555662.898600537335212.6169550226647
1861.9997222226.48977503032483-4.49005280832483
18712.9611111111.02842429610881.9326868138912
1884.8741666674.99246199987214-0.118295332872141
18937.0466666727.23696115496179.8097055150383
19026.4519444435.3350112569096-8.88306681690958
19142.3891666738.33845005374974.05071661625029
19227.2627777820.11700333528767.14577444471243
19322.1163888925.096004650374-2.97961576037401
19416.4427777822.1307243020949-5.68794652209491
19538.8727777839.0808591999452-0.208081419945244
19632.9477777830.40292153193082.54485624806922
19720.2444444420.4634759824254-0.219031542425358
19818.187522.9059712359784-4.71847123597844
19927.6786111128.8090180099918-1.13040689999183
20019.9902777826.5635773846195-6.57329960461951
20121.4644444421.5790339725739-0.114589532573944
20213.6913888921.8231622878856-8.13177339788563
20337.5363888927.198132384416110.3382565055839
20430.1238888924.38279927855765.7410896114424
20524.9294444424.50524850959750.424195930402452
20612.3044444419.1173809898977-6.81293654989775
20721.5688888924.1074329684418-2.53854407844179
20850.4244444426.480904670732723.9435397692673
20937.227526.228739773213610.9987602267864
21034.4622222231.0540176243473.40820459565297
21125.7305555618.59685915658777.13369640341227
21233.8466666727.50061225994916.34605441005086
21314.6986111121.8745174073216-7.1759062973216
21422.7422222225.129425525698-2.38720330569803
21516.3836111119.947523070533-3.56391196053302
21614.8652777817.8889837367686-3.02370595676862
21716.8922222221.1721597067535-4.27993748675351
21815.6597222218.0646472039789-2.40492498397892
21918.1916666722.5535523905309-4.3618857205309
22022.4858333317.43276104843585.05307228156424
22121.19526.4684993566279-5.27349935662786
22228.8919444429.6092555364683-0.717311096468262
22327.2511111132.7071273434118-5.45601623341181
22418.8858333323.8636792382195-4.97784590821951
2258.60805555614.4945874121214-5.88653185612143
22637.6272222225.771261857436111.8559603625639
22720.4177777818.5902395636281.82753821637203
22817.5341666727.4422560724476-9.90808940244765
22917.01523.8713479571852-6.85634795718519
23020.8094444433.5611247075113-12.7516802675113
2318.82611111112.8991700470089-4.07305893600885
23222.6213888925.8088141905352-3.18742530053518
23324.2183333325.8909303256256-1.67259699562563
23413.9138888919.8038417760083-5.88995288600829
23518.262526.7581755902521-8.49567559025214
23615.7369444428.0072128414132-12.2702684014132
23743.9997222223.776859768474220.2228624515258
23812.9041666720.6770178092564-7.7728511392564
23920.4511111124.0925163529545-3.64140524295453
24010.6652777818.8052463685246-8.13996858852458
24125.527521.12271621834224.40478378165777
24238.7572222228.474494061317910.2827281586821
24314.4923.9443768660116-9.4543768660116
24414.3241666720.667775572834-6.34360890283397
24519.597522.0034365565646-2.40593655656459
24623.5711111126.0920321548576-2.52092104485763
24728.4827777832.2756383181622-3.79286053816221
24824.0772222218.39145512319385.68576709680619
24923.8080555619.51702309542514.29103246457487
2509.62833333316.6249524016051-6.99661906860509
25141.8277777828.365231501907113.4625462780929
25227.6697222232.2843543019788-4.61463208197875
2535.3747222229.13422915112234-3.75950692912234
25427.6036111119.78887264623077.81473846376929
25523.9527777821.1309562376712.82182154232902
2568.5658333338.85174198622975-0.285908653229754
2578.80722222219.9658722251706-11.1586500031706
25824.9461111123.54174664812071.40436446187926
25917.2466666717.6476009242964-0.400934254296356
26011.1530555615.0112858815742-3.85823032157425
2617.67611111113.2239263531477-5.54781524214769
26221.3861111128.403169973956-7.01705886395603
26310.405555569.523173260158120.882382299841881
26415.0436111125.2463552494598-10.2027441394598
26513.8505555620.254632862969-6.40407730296903
26623.4269444425.7003515275663-2.27340708756634
26717.8263888927.0602730125815-9.23388412258147
26816.49522.0270375816036-5.53203758160355
26933.1411111124.68133529540068.45977581459936
27021.3061111130.8171168420482-9.51100573204824
27128.7291666721.58592720936987.14323946063024
27219.5421.4082750442006-1.86827504420061
27312.058333337.103036161222074.95529716877793
27429.1216666729.7335759780559-0.611909308055905
27517.2819444418.7352763552931-1.45333191529311
27619.2511111128.6183181771469-9.36720706714694
27714.7547222214.41812978149550.336592438504459
2785.498.8672643155979-3.3772643155979
27924.0777777825.1322795679286-1.05450178792861
28023.362520.00640270795133.35609729204865
28121.6513888925.0522554663912-3.40086657639121
28224.7536111125.7543296920461-1.0007185820461
28325.2791666722.15020484670253.12896182329749
28411.189.18237681667631.9976231833237
28517.8297222217.29221402345370.537508196546342
28614.1269444422.6372435976928-8.5102991576928
28715.7258333315.62914812123480.0966852087652423
28817.4422222223.6762387970302-6.23401657703016
28920.1486111119.4590777311220.689533378878005

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 58.58527778 & 55.9576246742933 & 2.62765310570674 \tabularnewline
2 & 33.60611111 & 45.3612285207549 & -11.7551174107549 \tabularnewline
3 & 49.03 & 50.7499553046393 & -1.71995530463934 \tabularnewline
4 & 49.81138889 & 64.0284560872026 & -14.2170671972026 \tabularnewline
5 & 34.21805556 & 34.6138269191653 & -0.395771359165287 \tabularnewline
6 & 14.65166667 & 24.1564497224905 & -9.50478305249051 \tabularnewline
7 & 107.0927778 & 67.6168058993674 & 39.4759719006326 \tabularnewline
8 & 9.213888889 & 15.6892604914575 & -6.47537160245752 \tabularnewline
9 & 28.23472222 & 17.6975547907132 & 10.5371674292867 \tabularnewline
10 & 41.40583333 & 42.9203491978953 & -1.51451586789529 \tabularnewline
11 & 45.95722222 & 44.5121994205388 & 1.44502279946118 \tabularnewline
12 & 65.8925 & 54.6950969198483 & 11.1974030801517 \tabularnewline
13 & 48.14611111 & 60.7856429628409 & -12.6395318528409 \tabularnewline
14 & 36.98083333 & 39.0213497043504 & -2.04051637435039 \tabularnewline
15 & 71.90916667 & 65.4808378540033 & 6.42832881599674 \tabularnewline
16 & 50.02305556 & 46.6329764618943 & 3.39007909810575 \tabularnewline
17 & 90.22194444 & 87.9737315969978 & 2.24821284300216 \tabularnewline
18 & 64.15666667 & 65.5744584655032 & -1.41779179550323 \tabularnewline
19 & 65.77361111 & 54.6673595397777 & 11.1062515702223 \tabularnewline
20 & 37.63138889 & 52.1251302706354 & -14.4937413806354 \tabularnewline
21 & 56.36805556 & 70.6580639214981 & -14.2900083614981 \tabularnewline
22 & 59.76305556 & 64.5259332042936 & -4.76287764429359 \tabularnewline
23 & 95.63805556 & 51.5452908615554 & 44.0927646984446 \tabularnewline
24 & 42.75972222 & 39.2934053931586 & 3.46631682684141 \tabularnewline
25 & 36.92861111 & 60.1003008013295 & -23.1716896913295 \tabularnewline
26 & 48.53444444 & 67.3813358565521 & -18.8468914165521 \tabularnewline
27 & 48.44861111 & 51.4066654302798 & -2.95805432027977 \tabularnewline
28 & 62.65222222 & 54.2299046608311 & 8.42231755916889 \tabularnewline
29 & 62.12 & 61.5247753247298 & 0.595224675270159 \tabularnewline
30 & 34.67138889 & 34.6450660304391 & 0.0263228595609374 \tabularnewline
31 & 61.58277778 & 62.0780241801644 & -0.495246400164443 \tabularnewline
32 & 58.54638889 & 63.7545289178702 & -5.20814002787024 \tabularnewline
33 & 47.29611111 & 46.6529204390313 & 0.643190670968715 \tabularnewline
34 & 72.37805556 & 71.1799340919557 & 1.19812146804428 \tabularnewline
35 & 23.57027778 & 37.5056671923153 & -13.9353894123153 \tabularnewline
36 & 81.78444444 & 65.2197084512252 & 16.5647359887748 \tabularnewline
37 & 28.05861111 & 22.9771701061866 & 5.08144100381336 \tabularnewline
38 & 59.90027778 & 48.4058765304273 & 11.4944012495727 \tabularnewline
39 & 90.3075 & 57.0026243299805 & 33.3048756700195 \tabularnewline
40 & 1.993333333 & 4.2343957460541 & -2.24106241305409 \tabularnewline
41 & 46.53944444 & 42.5714329301442 & 3.96801150985583 \tabularnewline
42 & 29.55777778 & 24.798641866988 & 4.75913591301203 \tabularnewline
43 & 26.82222222 & 28.289424807855 & -1.46720258785499 \tabularnewline
44 & 73.82472222 & 59.272069373621 & 14.552652846379 \tabularnewline
45 & 74.90305556 & 60.09532595397 & 14.80772960603 \tabularnewline
46 & 41.42 & 45.606439090952 & -4.18643909095202 \tabularnewline
47 & 48.84 & 36.3520628038074 & 12.4879371961926 \tabularnewline
48 & 42.46416667 & 45.1612820941838 & -2.6971154241838 \tabularnewline
49 & 31.01805556 & 35.5953840229757 & -4.57732846297573 \tabularnewline
50 & 32.33555556 & 41.7278849679659 & -9.39232940796586 \tabularnewline
51 & 100.6391667 & 55.7447607310207 & 44.8944059689793 \tabularnewline
52 & 21.88888889 & 26.773185987 & -4.88429709699996 \tabularnewline
53 & 50.87972222 & 61.1007551939429 & -10.2210329739429 \tabularnewline
54 & 77.2125 & 74.7109487426068 & 2.50155125739323 \tabularnewline
55 & 41.84138889 & 55.0355090855353 & -13.1941201955353 \tabularnewline
56 & 46.89138889 & 49.7726935149745 & -2.88130462497447 \tabularnewline
57 & 6.718888889 & 9.23601619603056 & -2.51712730703056 \tabularnewline
58 & 91.46305556 & 60.7607937319783 & 30.7022618280217 \tabularnewline
59 & 18.06361111 & 23.0991947339955 & -5.03558362399554 \tabularnewline
60 & 28.0825 & 23.9078152327097 & 4.17468476729028 \tabularnewline
61 & 60.81833333 & 51.1569412190804 & 9.66139211091964 \tabularnewline
62 & 67.79222222 & 73.1857187394844 & -5.39349651948445 \tabularnewline
63 & 94.88055556 & 56.8167469036133 & 38.0638086563867 \tabularnewline
64 & 28.77694444 & 23.0980026916445 & 5.67894174835545 \tabularnewline
65 & 64.81333333 & 60.0127593783664 & 4.8005739516336 \tabularnewline
66 & 71.23944444 & 71.6991063766077 & -0.459661936607715 \tabularnewline
67 & 57.26694444 & 49.54363091339 & 7.72331352661001 \tabularnewline
68 & 86.52027778 & 77.6202697534572 & 8.90000802654277 \tabularnewline
69 & 65.5 & 64.7111051217932 & 0.788894878206835 \tabularnewline
70 & 49.4275 & 44.3219864929614 & 5.10551350703856 \tabularnewline
71 & 57.54888889 & 46.9303190133763 & 10.6185698766237 \tabularnewline
72 & 54.59805556 & 41.543819617816 & 13.054235942184 \tabularnewline
73 & 48.38444444 & 45.2088218196846 & 3.17562262031537 \tabularnewline
74 & 39.79055556 & 50.0581054687652 & -10.2675499087652 \tabularnewline
75 & 52.09972222 & 53.5283099104745 & -1.42858769047452 \tabularnewline
76 & 52.13361111 & 64.0817514776344 & -11.9481403676344 \tabularnewline
77 & 33.06 & 61.3796134475157 & -28.3196134475157 \tabularnewline
78 & 50.60888889 & 55.7704714888041 & -5.16158259880408 \tabularnewline
79 & 20.435 & 24.8287383409717 & -4.39373834097168 \tabularnewline
80 & 54.16083333 & 52.6825870742623 & 1.47824625573767 \tabularnewline
81 & 46.52444444 & 48.7573803565658 & -2.23293591656579 \tabularnewline
82 & 39.93222222 & 61.6401230864038 & -21.7079008664038 \tabularnewline
83 & 76.53916667 & 67.203038936704 & 9.33612773329596 \tabularnewline
84 & 67.55527778 & 56.0663080652267 & 11.4889697147733 \tabularnewline
85 & 50.83305556 & 68.0615181926053 & -17.2284626326053 \tabularnewline
86 & 37.68027778 & 57.0181828974576 & -19.3379051174577 \tabularnewline
87 & 42.30527778 & 46.6180348556181 & -4.31275707561813 \tabularnewline
88 & 33.39472222 & 36.4696145176314 & -3.07489229763141 \tabularnewline
89 & 96.24583333 & 71.680787854701 & 24.565045475299 \tabularnewline
90 & 40.49722222 & 30.5616863709788 & 9.93553584902122 \tabularnewline
91 & 53.70527778 & 62.1877492305707 & -8.48247145057067 \tabularnewline
92 & 22.48694444 & 29.6513733533023 & -7.16442891330235 \tabularnewline
93 & 34.10388889 & 25.256134102751 & 8.84775478724897 \tabularnewline
94 & 36.27361111 & 49.8449510289583 & -13.5713399189583 \tabularnewline
95 & 31.28083333 & 31.4363052307566 & -0.155471900756565 \tabularnewline
96 & 79.57444444 & 46.0550725581581 & 33.5193718818418 \tabularnewline
97 & 66.96277778 & 57.300988045822 & 9.661789734178 \tabularnewline
98 & 41.235 & 78.8059231489266 & -37.5709231489266 \tabularnewline
99 & 56.86472222 & 46.3866212982112 & 10.4781009217888 \tabularnewline
100 & 50.5775 & 70.7849679657504 & -20.2074679657504 \tabularnewline
101 & 38.98444444 & 32.4060305835614 & 6.57841385643855 \tabularnewline
102 & 61.25444444 & 57.0135614251857 & 4.2408830148143 \tabularnewline
103 & 67.51666667 & 48.7190025597192 & 18.7976641102808 \tabularnewline
104 & 45.2125 & 52.3137102398854 & -7.10121023988536 \tabularnewline
105 & 50.72583333 & 58.3993218559956 & -7.67348852599556 \tabularnewline
106 & 64.48277778 & 78.2632713121663 & -13.7804935321663 \tabularnewline
107 & 73.69944444 & 77.0683648413026 & -3.3689204013026 \tabularnewline
108 & 23.77055556 & 28.8007281474571 & -5.03017258745711 \tabularnewline
109 & 86.34416667 & 74.6282326671821 & 11.7159340028179 \tabularnewline
110 & 62.51666667 & 65.5807987726849 & -3.06413210268493 \tabularnewline
111 & 64.5325 & 71.7317145901189 & -7.19921459011893 \tabularnewline
112 & 40.26833333 & 36.2624280260891 & 4.00590530391091 \tabularnewline
113 & 12.02416667 & 22.2282929979839 & -10.2041263279839 \tabularnewline
114 & 43.265 & 41.8424816032652 & 1.4225183967348 \tabularnewline
115 & 45.7525 & 54.48940900996 & -8.73690900996004 \tabularnewline
116 & 56.09444444 & 63.2159095605945 & -7.12146512059451 \tabularnewline
117 & 65.40388889 & 77.4610926749679 & -12.0572037849679 \tabularnewline
118 & 61.33361111 & 33.9226837384253 & 27.4109273715747 \tabularnewline
119 & 27.62944444 & 44.7573568931618 & -17.1279124531618 \tabularnewline
120 & 25.73916667 & 28.9488220101261 & -3.20965534012606 \tabularnewline
121 & 37.03555556 & 36.1304206697225 & 0.905134890277491 \tabularnewline
122 & 17.04472222 & 20.0145364506251 & -2.96981423062511 \tabularnewline
123 & 34.98055556 & 27.6906822346175 & 7.28987332538249 \tabularnewline
124 & 27.98611111 & 60.262908594378 & -32.276797484378 \tabularnewline
125 & 62.37472222 & 49.3671176997647 & 13.0076045202353 \tabularnewline
126 & 22.86555556 & 19.8706603970225 & 2.99489516297747 \tabularnewline
127 & 28.33611111 & 24.1163535356463 & 4.21975757435374 \tabularnewline
128 & 28.20083333 & 40.2081510725115 & -12.0073177425115 \tabularnewline
129 & 67.64194444 & 77.9278619622523 & -10.2859175222523 \tabularnewline
130 & 6.371666667 & 8.52629868034388 & -2.15463201334388 \tabularnewline
131 & 11.54611111 & 9.94890421936882 & 1.59720689063118 \tabularnewline
132 & 42.35388889 & 60.5996247146961 & -18.2457358246961 \tabularnewline
133 & 17.1825 & 19.5044911411566 & -2.32199114115664 \tabularnewline
134 & 27.75638889 & 33.8588679879052 & -6.1024790979052 \tabularnewline
135 & 36.80194444 & 48.7784339804851 & -11.9764895404851 \tabularnewline
136 & 88.165 & 66.035244374835 & 22.129755625165 \tabularnewline
137 & 5.848333333 & 5.44958498594744 & 0.398748347052562 \tabularnewline
138 & 58.23361111 & 45.967677430746 & 12.265933679254 \tabularnewline
139 & 6.291111111 & 19.0154914491215 & -12.7243803381215 \tabularnewline
140 & 8.726111111 & 15.2610954659671 & -6.53498435496711 \tabularnewline
141 & 12.97166667 & 16.0435585539387 & -3.07189188393875 \tabularnewline
142 & 36.58277778 & 39.5328332130684 & -2.95005543306837 \tabularnewline
143 & 25.48194444 & 16.9404563404711 & 8.54148809952894 \tabularnewline
144 & 67.98583333 & 59.7156841572209 & 8.27014917277913 \tabularnewline
145 & 51.25277778 & 55.9321514606087 & -4.67937368060872 \tabularnewline
146 & 22.18416667 & 27.2456593079822 & -5.06149263798217 \tabularnewline
147 & 35.67305556 & 42.8369500053184 & -7.16389444531838 \tabularnewline
148 & 27.1775 & 33.9282046253826 & -6.75070462538256 \tabularnewline
149 & 10.615 & 14.057001265731 & -3.44200126573101 \tabularnewline
150 & 41.9725 & 45.4546741669359 & -3.48217416693595 \tabularnewline
151 & 75.68277778 & 67.1010467318911 & 8.5817310481089 \tabularnewline
152 & 47.915 & 49.1275171772722 & -1.21251717727222 \tabularnewline
153 & 30.01194444 & 28.9929001549243 & 1.01904428507571 \tabularnewline
154 & 91.14083333 & 76.6059115016489 & 14.5349218283511 \tabularnewline
155 & 69.60527778 & 75.2281933900291 & -5.62291561002913 \tabularnewline
156 & 97.51861111 & 92.2724576862064 & 5.24615342379359 \tabularnewline
157 & 43.89305556 & 45.7201867897657 & -1.82713122976568 \tabularnewline
158 & 27.46277778 & 20.9532737463113 & 6.50950403368867 \tabularnewline
159 & 23.73305556 & 34.1177757393418 & -10.3847201793418 \tabularnewline
160 & 63.67833333 & 49.1688307403606 & 14.5095025896394 \tabularnewline
161 & 97.67194444 & 66.292161435553 & 31.379783004447 \tabularnewline
162 & 23.39083333 & 35.1167045965494 & -11.7258712665494 \tabularnewline
163 & 33.45694444 & 28.8531568071711 & 4.60378763282892 \tabularnewline
164 & 90.16611111 & 72.7379631119445 & 17.4281479980555 \tabularnewline
165 & 36.40805556 & 39.3121785379466 & -2.90412297794655 \tabularnewline
166 & 56.74194444 & 58.5251491191358 & -1.7832046791358 \tabularnewline
167 & 45.98416667 & 47.6439183556929 & -1.65975168569288 \tabularnewline
168 & 39.36722222 & 31.4325278561905 & 7.9346943638095 \tabularnewline
169 & 32.23555556 & 33.4230110772514 & -1.18745551725137 \tabularnewline
170 & 69.4575 & 34.8564628645146 & 34.6010371354854 \tabularnewline
171 & 83.27083333 & 58.8631722663003 & 24.4076610636997 \tabularnewline
172 & 54.39944444 & 65.6027202735886 & -11.2032758335886 \tabularnewline
173 & 48.12777778 & 31.4512478151306 & 16.6765299648694 \tabularnewline
174 & 70.69111111 & 72.5626342474916 & -1.87152313749164 \tabularnewline
175 & 28.99694444 & 80.471868084165 & -51.474923644165 \tabularnewline
176 & 37.80111111 & 21.9752484727715 & 15.8258626372285 \tabularnewline
177 & 55.41 & 61.9442341907138 & -6.53423419071377 \tabularnewline
178 & 25.69416667 & 23.1924092879491 & 2.50175738205093 \tabularnewline
179 & 62.31388889 & 78.8625210225754 & -16.5486321325754 \tabularnewline
180 & 37.71694444 & 27.9668615130865 & 9.75008292691352 \tabularnewline
181 & 20.66888889 & 20.4882881652497 & 0.180600724750338 \tabularnewline
182 & 22.56666667 & 35.7817975628229 & -13.2151308928229 \tabularnewline
183 & 4.08 & 5.99742750077519 & -1.91742750077519 \tabularnewline
184 & 50.45361111 & 40.6852830454086 & 9.76832806459139 \tabularnewline
185 & 75.51555556 & 62.8986005373352 & 12.6169550226647 \tabularnewline
186 & 1.999722222 & 6.48977503032483 & -4.49005280832483 \tabularnewline
187 & 12.96111111 & 11.0284242961088 & 1.9326868138912 \tabularnewline
188 & 4.874166667 & 4.99246199987214 & -0.118295332872141 \tabularnewline
189 & 37.04666667 & 27.2369611549617 & 9.8097055150383 \tabularnewline
190 & 26.45194444 & 35.3350112569096 & -8.88306681690958 \tabularnewline
191 & 42.38916667 & 38.3384500537497 & 4.05071661625029 \tabularnewline
192 & 27.26277778 & 20.1170033352876 & 7.14577444471243 \tabularnewline
193 & 22.11638889 & 25.096004650374 & -2.97961576037401 \tabularnewline
194 & 16.44277778 & 22.1307243020949 & -5.68794652209491 \tabularnewline
195 & 38.87277778 & 39.0808591999452 & -0.208081419945244 \tabularnewline
196 & 32.94777778 & 30.4029215319308 & 2.54485624806922 \tabularnewline
197 & 20.24444444 & 20.4634759824254 & -0.219031542425358 \tabularnewline
198 & 18.1875 & 22.9059712359784 & -4.71847123597844 \tabularnewline
199 & 27.67861111 & 28.8090180099918 & -1.13040689999183 \tabularnewline
200 & 19.99027778 & 26.5635773846195 & -6.57329960461951 \tabularnewline
201 & 21.46444444 & 21.5790339725739 & -0.114589532573944 \tabularnewline
202 & 13.69138889 & 21.8231622878856 & -8.13177339788563 \tabularnewline
203 & 37.53638889 & 27.1981323844161 & 10.3382565055839 \tabularnewline
204 & 30.12388889 & 24.3827992785576 & 5.7410896114424 \tabularnewline
205 & 24.92944444 & 24.5052485095975 & 0.424195930402452 \tabularnewline
206 & 12.30444444 & 19.1173809898977 & -6.81293654989775 \tabularnewline
207 & 21.56888889 & 24.1074329684418 & -2.53854407844179 \tabularnewline
208 & 50.42444444 & 26.4809046707327 & 23.9435397692673 \tabularnewline
209 & 37.2275 & 26.2287397732136 & 10.9987602267864 \tabularnewline
210 & 34.46222222 & 31.054017624347 & 3.40820459565297 \tabularnewline
211 & 25.73055556 & 18.5968591565877 & 7.13369640341227 \tabularnewline
212 & 33.84666667 & 27.5006122599491 & 6.34605441005086 \tabularnewline
213 & 14.69861111 & 21.8745174073216 & -7.1759062973216 \tabularnewline
214 & 22.74222222 & 25.129425525698 & -2.38720330569803 \tabularnewline
215 & 16.38361111 & 19.947523070533 & -3.56391196053302 \tabularnewline
216 & 14.86527778 & 17.8889837367686 & -3.02370595676862 \tabularnewline
217 & 16.89222222 & 21.1721597067535 & -4.27993748675351 \tabularnewline
218 & 15.65972222 & 18.0646472039789 & -2.40492498397892 \tabularnewline
219 & 18.19166667 & 22.5535523905309 & -4.3618857205309 \tabularnewline
220 & 22.48583333 & 17.4327610484358 & 5.05307228156424 \tabularnewline
221 & 21.195 & 26.4684993566279 & -5.27349935662786 \tabularnewline
222 & 28.89194444 & 29.6092555364683 & -0.717311096468262 \tabularnewline
223 & 27.25111111 & 32.7071273434118 & -5.45601623341181 \tabularnewline
224 & 18.88583333 & 23.8636792382195 & -4.97784590821951 \tabularnewline
225 & 8.608055556 & 14.4945874121214 & -5.88653185612143 \tabularnewline
226 & 37.62722222 & 25.7712618574361 & 11.8559603625639 \tabularnewline
227 & 20.41777778 & 18.590239563628 & 1.82753821637203 \tabularnewline
228 & 17.53416667 & 27.4422560724476 & -9.90808940244765 \tabularnewline
229 & 17.015 & 23.8713479571852 & -6.85634795718519 \tabularnewline
230 & 20.80944444 & 33.5611247075113 & -12.7516802675113 \tabularnewline
231 & 8.826111111 & 12.8991700470089 & -4.07305893600885 \tabularnewline
232 & 22.62138889 & 25.8088141905352 & -3.18742530053518 \tabularnewline
233 & 24.21833333 & 25.8909303256256 & -1.67259699562563 \tabularnewline
234 & 13.91388889 & 19.8038417760083 & -5.88995288600829 \tabularnewline
235 & 18.2625 & 26.7581755902521 & -8.49567559025214 \tabularnewline
236 & 15.73694444 & 28.0072128414132 & -12.2702684014132 \tabularnewline
237 & 43.99972222 & 23.7768597684742 & 20.2228624515258 \tabularnewline
238 & 12.90416667 & 20.6770178092564 & -7.7728511392564 \tabularnewline
239 & 20.45111111 & 24.0925163529545 & -3.64140524295453 \tabularnewline
240 & 10.66527778 & 18.8052463685246 & -8.13996858852458 \tabularnewline
241 & 25.5275 & 21.1227162183422 & 4.40478378165777 \tabularnewline
242 & 38.75722222 & 28.4744940613179 & 10.2827281586821 \tabularnewline
243 & 14.49 & 23.9443768660116 & -9.4543768660116 \tabularnewline
244 & 14.32416667 & 20.667775572834 & -6.34360890283397 \tabularnewline
245 & 19.5975 & 22.0034365565646 & -2.40593655656459 \tabularnewline
246 & 23.57111111 & 26.0920321548576 & -2.52092104485763 \tabularnewline
247 & 28.48277778 & 32.2756383181622 & -3.79286053816221 \tabularnewline
248 & 24.07722222 & 18.3914551231938 & 5.68576709680619 \tabularnewline
249 & 23.80805556 & 19.5170230954251 & 4.29103246457487 \tabularnewline
250 & 9.628333333 & 16.6249524016051 & -6.99661906860509 \tabularnewline
251 & 41.82777778 & 28.3652315019071 & 13.4625462780929 \tabularnewline
252 & 27.66972222 & 32.2843543019788 & -4.61463208197875 \tabularnewline
253 & 5.374722222 & 9.13422915112234 & -3.75950692912234 \tabularnewline
254 & 27.60361111 & 19.7888726462307 & 7.81473846376929 \tabularnewline
255 & 23.95277778 & 21.130956237671 & 2.82182154232902 \tabularnewline
256 & 8.565833333 & 8.85174198622975 & -0.285908653229754 \tabularnewline
257 & 8.807222222 & 19.9658722251706 & -11.1586500031706 \tabularnewline
258 & 24.94611111 & 23.5417466481207 & 1.40436446187926 \tabularnewline
259 & 17.24666667 & 17.6476009242964 & -0.400934254296356 \tabularnewline
260 & 11.15305556 & 15.0112858815742 & -3.85823032157425 \tabularnewline
261 & 7.676111111 & 13.2239263531477 & -5.54781524214769 \tabularnewline
262 & 21.38611111 & 28.403169973956 & -7.01705886395603 \tabularnewline
263 & 10.40555556 & 9.52317326015812 & 0.882382299841881 \tabularnewline
264 & 15.04361111 & 25.2463552494598 & -10.2027441394598 \tabularnewline
265 & 13.85055556 & 20.254632862969 & -6.40407730296903 \tabularnewline
266 & 23.42694444 & 25.7003515275663 & -2.27340708756634 \tabularnewline
267 & 17.82638889 & 27.0602730125815 & -9.23388412258147 \tabularnewline
268 & 16.495 & 22.0270375816036 & -5.53203758160355 \tabularnewline
269 & 33.14111111 & 24.6813352954006 & 8.45977581459936 \tabularnewline
270 & 21.30611111 & 30.8171168420482 & -9.51100573204824 \tabularnewline
271 & 28.72916667 & 21.5859272093698 & 7.14323946063024 \tabularnewline
272 & 19.54 & 21.4082750442006 & -1.86827504420061 \tabularnewline
273 & 12.05833333 & 7.10303616122207 & 4.95529716877793 \tabularnewline
274 & 29.12166667 & 29.7335759780559 & -0.611909308055905 \tabularnewline
275 & 17.28194444 & 18.7352763552931 & -1.45333191529311 \tabularnewline
276 & 19.25111111 & 28.6183181771469 & -9.36720706714694 \tabularnewline
277 & 14.75472222 & 14.4181297814955 & 0.336592438504459 \tabularnewline
278 & 5.49 & 8.8672643155979 & -3.3772643155979 \tabularnewline
279 & 24.07777778 & 25.1322795679286 & -1.05450178792861 \tabularnewline
280 & 23.3625 & 20.0064027079513 & 3.35609729204865 \tabularnewline
281 & 21.65138889 & 25.0522554663912 & -3.40086657639121 \tabularnewline
282 & 24.75361111 & 25.7543296920461 & -1.0007185820461 \tabularnewline
283 & 25.27916667 & 22.1502048467025 & 3.12896182329749 \tabularnewline
284 & 11.18 & 9.1823768166763 & 1.9976231833237 \tabularnewline
285 & 17.82972222 & 17.2922140234537 & 0.537508196546342 \tabularnewline
286 & 14.12694444 & 22.6372435976928 & -8.5102991576928 \tabularnewline
287 & 15.72583333 & 15.6291481212348 & 0.0966852087652423 \tabularnewline
288 & 17.44222222 & 23.6762387970302 & -6.23401657703016 \tabularnewline
289 & 20.14861111 & 19.459077731122 & 0.689533378878005 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186260&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]58.58527778[/C][C]55.9576246742933[/C][C]2.62765310570674[/C][/ROW]
[ROW][C]2[/C][C]33.60611111[/C][C]45.3612285207549[/C][C]-11.7551174107549[/C][/ROW]
[ROW][C]3[/C][C]49.03[/C][C]50.7499553046393[/C][C]-1.71995530463934[/C][/ROW]
[ROW][C]4[/C][C]49.81138889[/C][C]64.0284560872026[/C][C]-14.2170671972026[/C][/ROW]
[ROW][C]5[/C][C]34.21805556[/C][C]34.6138269191653[/C][C]-0.395771359165287[/C][/ROW]
[ROW][C]6[/C][C]14.65166667[/C][C]24.1564497224905[/C][C]-9.50478305249051[/C][/ROW]
[ROW][C]7[/C][C]107.0927778[/C][C]67.6168058993674[/C][C]39.4759719006326[/C][/ROW]
[ROW][C]8[/C][C]9.213888889[/C][C]15.6892604914575[/C][C]-6.47537160245752[/C][/ROW]
[ROW][C]9[/C][C]28.23472222[/C][C]17.6975547907132[/C][C]10.5371674292867[/C][/ROW]
[ROW][C]10[/C][C]41.40583333[/C][C]42.9203491978953[/C][C]-1.51451586789529[/C][/ROW]
[ROW][C]11[/C][C]45.95722222[/C][C]44.5121994205388[/C][C]1.44502279946118[/C][/ROW]
[ROW][C]12[/C][C]65.8925[/C][C]54.6950969198483[/C][C]11.1974030801517[/C][/ROW]
[ROW][C]13[/C][C]48.14611111[/C][C]60.7856429628409[/C][C]-12.6395318528409[/C][/ROW]
[ROW][C]14[/C][C]36.98083333[/C][C]39.0213497043504[/C][C]-2.04051637435039[/C][/ROW]
[ROW][C]15[/C][C]71.90916667[/C][C]65.4808378540033[/C][C]6.42832881599674[/C][/ROW]
[ROW][C]16[/C][C]50.02305556[/C][C]46.6329764618943[/C][C]3.39007909810575[/C][/ROW]
[ROW][C]17[/C][C]90.22194444[/C][C]87.9737315969978[/C][C]2.24821284300216[/C][/ROW]
[ROW][C]18[/C][C]64.15666667[/C][C]65.5744584655032[/C][C]-1.41779179550323[/C][/ROW]
[ROW][C]19[/C][C]65.77361111[/C][C]54.6673595397777[/C][C]11.1062515702223[/C][/ROW]
[ROW][C]20[/C][C]37.63138889[/C][C]52.1251302706354[/C][C]-14.4937413806354[/C][/ROW]
[ROW][C]21[/C][C]56.36805556[/C][C]70.6580639214981[/C][C]-14.2900083614981[/C][/ROW]
[ROW][C]22[/C][C]59.76305556[/C][C]64.5259332042936[/C][C]-4.76287764429359[/C][/ROW]
[ROW][C]23[/C][C]95.63805556[/C][C]51.5452908615554[/C][C]44.0927646984446[/C][/ROW]
[ROW][C]24[/C][C]42.75972222[/C][C]39.2934053931586[/C][C]3.46631682684141[/C][/ROW]
[ROW][C]25[/C][C]36.92861111[/C][C]60.1003008013295[/C][C]-23.1716896913295[/C][/ROW]
[ROW][C]26[/C][C]48.53444444[/C][C]67.3813358565521[/C][C]-18.8468914165521[/C][/ROW]
[ROW][C]27[/C][C]48.44861111[/C][C]51.4066654302798[/C][C]-2.95805432027977[/C][/ROW]
[ROW][C]28[/C][C]62.65222222[/C][C]54.2299046608311[/C][C]8.42231755916889[/C][/ROW]
[ROW][C]29[/C][C]62.12[/C][C]61.5247753247298[/C][C]0.595224675270159[/C][/ROW]
[ROW][C]30[/C][C]34.67138889[/C][C]34.6450660304391[/C][C]0.0263228595609374[/C][/ROW]
[ROW][C]31[/C][C]61.58277778[/C][C]62.0780241801644[/C][C]-0.495246400164443[/C][/ROW]
[ROW][C]32[/C][C]58.54638889[/C][C]63.7545289178702[/C][C]-5.20814002787024[/C][/ROW]
[ROW][C]33[/C][C]47.29611111[/C][C]46.6529204390313[/C][C]0.643190670968715[/C][/ROW]
[ROW][C]34[/C][C]72.37805556[/C][C]71.1799340919557[/C][C]1.19812146804428[/C][/ROW]
[ROW][C]35[/C][C]23.57027778[/C][C]37.5056671923153[/C][C]-13.9353894123153[/C][/ROW]
[ROW][C]36[/C][C]81.78444444[/C][C]65.2197084512252[/C][C]16.5647359887748[/C][/ROW]
[ROW][C]37[/C][C]28.05861111[/C][C]22.9771701061866[/C][C]5.08144100381336[/C][/ROW]
[ROW][C]38[/C][C]59.90027778[/C][C]48.4058765304273[/C][C]11.4944012495727[/C][/ROW]
[ROW][C]39[/C][C]90.3075[/C][C]57.0026243299805[/C][C]33.3048756700195[/C][/ROW]
[ROW][C]40[/C][C]1.993333333[/C][C]4.2343957460541[/C][C]-2.24106241305409[/C][/ROW]
[ROW][C]41[/C][C]46.53944444[/C][C]42.5714329301442[/C][C]3.96801150985583[/C][/ROW]
[ROW][C]42[/C][C]29.55777778[/C][C]24.798641866988[/C][C]4.75913591301203[/C][/ROW]
[ROW][C]43[/C][C]26.82222222[/C][C]28.289424807855[/C][C]-1.46720258785499[/C][/ROW]
[ROW][C]44[/C][C]73.82472222[/C][C]59.272069373621[/C][C]14.552652846379[/C][/ROW]
[ROW][C]45[/C][C]74.90305556[/C][C]60.09532595397[/C][C]14.80772960603[/C][/ROW]
[ROW][C]46[/C][C]41.42[/C][C]45.606439090952[/C][C]-4.18643909095202[/C][/ROW]
[ROW][C]47[/C][C]48.84[/C][C]36.3520628038074[/C][C]12.4879371961926[/C][/ROW]
[ROW][C]48[/C][C]42.46416667[/C][C]45.1612820941838[/C][C]-2.6971154241838[/C][/ROW]
[ROW][C]49[/C][C]31.01805556[/C][C]35.5953840229757[/C][C]-4.57732846297573[/C][/ROW]
[ROW][C]50[/C][C]32.33555556[/C][C]41.7278849679659[/C][C]-9.39232940796586[/C][/ROW]
[ROW][C]51[/C][C]100.6391667[/C][C]55.7447607310207[/C][C]44.8944059689793[/C][/ROW]
[ROW][C]52[/C][C]21.88888889[/C][C]26.773185987[/C][C]-4.88429709699996[/C][/ROW]
[ROW][C]53[/C][C]50.87972222[/C][C]61.1007551939429[/C][C]-10.2210329739429[/C][/ROW]
[ROW][C]54[/C][C]77.2125[/C][C]74.7109487426068[/C][C]2.50155125739323[/C][/ROW]
[ROW][C]55[/C][C]41.84138889[/C][C]55.0355090855353[/C][C]-13.1941201955353[/C][/ROW]
[ROW][C]56[/C][C]46.89138889[/C][C]49.7726935149745[/C][C]-2.88130462497447[/C][/ROW]
[ROW][C]57[/C][C]6.718888889[/C][C]9.23601619603056[/C][C]-2.51712730703056[/C][/ROW]
[ROW][C]58[/C][C]91.46305556[/C][C]60.7607937319783[/C][C]30.7022618280217[/C][/ROW]
[ROW][C]59[/C][C]18.06361111[/C][C]23.0991947339955[/C][C]-5.03558362399554[/C][/ROW]
[ROW][C]60[/C][C]28.0825[/C][C]23.9078152327097[/C][C]4.17468476729028[/C][/ROW]
[ROW][C]61[/C][C]60.81833333[/C][C]51.1569412190804[/C][C]9.66139211091964[/C][/ROW]
[ROW][C]62[/C][C]67.79222222[/C][C]73.1857187394844[/C][C]-5.39349651948445[/C][/ROW]
[ROW][C]63[/C][C]94.88055556[/C][C]56.8167469036133[/C][C]38.0638086563867[/C][/ROW]
[ROW][C]64[/C][C]28.77694444[/C][C]23.0980026916445[/C][C]5.67894174835545[/C][/ROW]
[ROW][C]65[/C][C]64.81333333[/C][C]60.0127593783664[/C][C]4.8005739516336[/C][/ROW]
[ROW][C]66[/C][C]71.23944444[/C][C]71.6991063766077[/C][C]-0.459661936607715[/C][/ROW]
[ROW][C]67[/C][C]57.26694444[/C][C]49.54363091339[/C][C]7.72331352661001[/C][/ROW]
[ROW][C]68[/C][C]86.52027778[/C][C]77.6202697534572[/C][C]8.90000802654277[/C][/ROW]
[ROW][C]69[/C][C]65.5[/C][C]64.7111051217932[/C][C]0.788894878206835[/C][/ROW]
[ROW][C]70[/C][C]49.4275[/C][C]44.3219864929614[/C][C]5.10551350703856[/C][/ROW]
[ROW][C]71[/C][C]57.54888889[/C][C]46.9303190133763[/C][C]10.6185698766237[/C][/ROW]
[ROW][C]72[/C][C]54.59805556[/C][C]41.543819617816[/C][C]13.054235942184[/C][/ROW]
[ROW][C]73[/C][C]48.38444444[/C][C]45.2088218196846[/C][C]3.17562262031537[/C][/ROW]
[ROW][C]74[/C][C]39.79055556[/C][C]50.0581054687652[/C][C]-10.2675499087652[/C][/ROW]
[ROW][C]75[/C][C]52.09972222[/C][C]53.5283099104745[/C][C]-1.42858769047452[/C][/ROW]
[ROW][C]76[/C][C]52.13361111[/C][C]64.0817514776344[/C][C]-11.9481403676344[/C][/ROW]
[ROW][C]77[/C][C]33.06[/C][C]61.3796134475157[/C][C]-28.3196134475157[/C][/ROW]
[ROW][C]78[/C][C]50.60888889[/C][C]55.7704714888041[/C][C]-5.16158259880408[/C][/ROW]
[ROW][C]79[/C][C]20.435[/C][C]24.8287383409717[/C][C]-4.39373834097168[/C][/ROW]
[ROW][C]80[/C][C]54.16083333[/C][C]52.6825870742623[/C][C]1.47824625573767[/C][/ROW]
[ROW][C]81[/C][C]46.52444444[/C][C]48.7573803565658[/C][C]-2.23293591656579[/C][/ROW]
[ROW][C]82[/C][C]39.93222222[/C][C]61.6401230864038[/C][C]-21.7079008664038[/C][/ROW]
[ROW][C]83[/C][C]76.53916667[/C][C]67.203038936704[/C][C]9.33612773329596[/C][/ROW]
[ROW][C]84[/C][C]67.55527778[/C][C]56.0663080652267[/C][C]11.4889697147733[/C][/ROW]
[ROW][C]85[/C][C]50.83305556[/C][C]68.0615181926053[/C][C]-17.2284626326053[/C][/ROW]
[ROW][C]86[/C][C]37.68027778[/C][C]57.0181828974576[/C][C]-19.3379051174577[/C][/ROW]
[ROW][C]87[/C][C]42.30527778[/C][C]46.6180348556181[/C][C]-4.31275707561813[/C][/ROW]
[ROW][C]88[/C][C]33.39472222[/C][C]36.4696145176314[/C][C]-3.07489229763141[/C][/ROW]
[ROW][C]89[/C][C]96.24583333[/C][C]71.680787854701[/C][C]24.565045475299[/C][/ROW]
[ROW][C]90[/C][C]40.49722222[/C][C]30.5616863709788[/C][C]9.93553584902122[/C][/ROW]
[ROW][C]91[/C][C]53.70527778[/C][C]62.1877492305707[/C][C]-8.48247145057067[/C][/ROW]
[ROW][C]92[/C][C]22.48694444[/C][C]29.6513733533023[/C][C]-7.16442891330235[/C][/ROW]
[ROW][C]93[/C][C]34.10388889[/C][C]25.256134102751[/C][C]8.84775478724897[/C][/ROW]
[ROW][C]94[/C][C]36.27361111[/C][C]49.8449510289583[/C][C]-13.5713399189583[/C][/ROW]
[ROW][C]95[/C][C]31.28083333[/C][C]31.4363052307566[/C][C]-0.155471900756565[/C][/ROW]
[ROW][C]96[/C][C]79.57444444[/C][C]46.0550725581581[/C][C]33.5193718818418[/C][/ROW]
[ROW][C]97[/C][C]66.96277778[/C][C]57.300988045822[/C][C]9.661789734178[/C][/ROW]
[ROW][C]98[/C][C]41.235[/C][C]78.8059231489266[/C][C]-37.5709231489266[/C][/ROW]
[ROW][C]99[/C][C]56.86472222[/C][C]46.3866212982112[/C][C]10.4781009217888[/C][/ROW]
[ROW][C]100[/C][C]50.5775[/C][C]70.7849679657504[/C][C]-20.2074679657504[/C][/ROW]
[ROW][C]101[/C][C]38.98444444[/C][C]32.4060305835614[/C][C]6.57841385643855[/C][/ROW]
[ROW][C]102[/C][C]61.25444444[/C][C]57.0135614251857[/C][C]4.2408830148143[/C][/ROW]
[ROW][C]103[/C][C]67.51666667[/C][C]48.7190025597192[/C][C]18.7976641102808[/C][/ROW]
[ROW][C]104[/C][C]45.2125[/C][C]52.3137102398854[/C][C]-7.10121023988536[/C][/ROW]
[ROW][C]105[/C][C]50.72583333[/C][C]58.3993218559956[/C][C]-7.67348852599556[/C][/ROW]
[ROW][C]106[/C][C]64.48277778[/C][C]78.2632713121663[/C][C]-13.7804935321663[/C][/ROW]
[ROW][C]107[/C][C]73.69944444[/C][C]77.0683648413026[/C][C]-3.3689204013026[/C][/ROW]
[ROW][C]108[/C][C]23.77055556[/C][C]28.8007281474571[/C][C]-5.03017258745711[/C][/ROW]
[ROW][C]109[/C][C]86.34416667[/C][C]74.6282326671821[/C][C]11.7159340028179[/C][/ROW]
[ROW][C]110[/C][C]62.51666667[/C][C]65.5807987726849[/C][C]-3.06413210268493[/C][/ROW]
[ROW][C]111[/C][C]64.5325[/C][C]71.7317145901189[/C][C]-7.19921459011893[/C][/ROW]
[ROW][C]112[/C][C]40.26833333[/C][C]36.2624280260891[/C][C]4.00590530391091[/C][/ROW]
[ROW][C]113[/C][C]12.02416667[/C][C]22.2282929979839[/C][C]-10.2041263279839[/C][/ROW]
[ROW][C]114[/C][C]43.265[/C][C]41.8424816032652[/C][C]1.4225183967348[/C][/ROW]
[ROW][C]115[/C][C]45.7525[/C][C]54.48940900996[/C][C]-8.73690900996004[/C][/ROW]
[ROW][C]116[/C][C]56.09444444[/C][C]63.2159095605945[/C][C]-7.12146512059451[/C][/ROW]
[ROW][C]117[/C][C]65.40388889[/C][C]77.4610926749679[/C][C]-12.0572037849679[/C][/ROW]
[ROW][C]118[/C][C]61.33361111[/C][C]33.9226837384253[/C][C]27.4109273715747[/C][/ROW]
[ROW][C]119[/C][C]27.62944444[/C][C]44.7573568931618[/C][C]-17.1279124531618[/C][/ROW]
[ROW][C]120[/C][C]25.73916667[/C][C]28.9488220101261[/C][C]-3.20965534012606[/C][/ROW]
[ROW][C]121[/C][C]37.03555556[/C][C]36.1304206697225[/C][C]0.905134890277491[/C][/ROW]
[ROW][C]122[/C][C]17.04472222[/C][C]20.0145364506251[/C][C]-2.96981423062511[/C][/ROW]
[ROW][C]123[/C][C]34.98055556[/C][C]27.6906822346175[/C][C]7.28987332538249[/C][/ROW]
[ROW][C]124[/C][C]27.98611111[/C][C]60.262908594378[/C][C]-32.276797484378[/C][/ROW]
[ROW][C]125[/C][C]62.37472222[/C][C]49.3671176997647[/C][C]13.0076045202353[/C][/ROW]
[ROW][C]126[/C][C]22.86555556[/C][C]19.8706603970225[/C][C]2.99489516297747[/C][/ROW]
[ROW][C]127[/C][C]28.33611111[/C][C]24.1163535356463[/C][C]4.21975757435374[/C][/ROW]
[ROW][C]128[/C][C]28.20083333[/C][C]40.2081510725115[/C][C]-12.0073177425115[/C][/ROW]
[ROW][C]129[/C][C]67.64194444[/C][C]77.9278619622523[/C][C]-10.2859175222523[/C][/ROW]
[ROW][C]130[/C][C]6.371666667[/C][C]8.52629868034388[/C][C]-2.15463201334388[/C][/ROW]
[ROW][C]131[/C][C]11.54611111[/C][C]9.94890421936882[/C][C]1.59720689063118[/C][/ROW]
[ROW][C]132[/C][C]42.35388889[/C][C]60.5996247146961[/C][C]-18.2457358246961[/C][/ROW]
[ROW][C]133[/C][C]17.1825[/C][C]19.5044911411566[/C][C]-2.32199114115664[/C][/ROW]
[ROW][C]134[/C][C]27.75638889[/C][C]33.8588679879052[/C][C]-6.1024790979052[/C][/ROW]
[ROW][C]135[/C][C]36.80194444[/C][C]48.7784339804851[/C][C]-11.9764895404851[/C][/ROW]
[ROW][C]136[/C][C]88.165[/C][C]66.035244374835[/C][C]22.129755625165[/C][/ROW]
[ROW][C]137[/C][C]5.848333333[/C][C]5.44958498594744[/C][C]0.398748347052562[/C][/ROW]
[ROW][C]138[/C][C]58.23361111[/C][C]45.967677430746[/C][C]12.265933679254[/C][/ROW]
[ROW][C]139[/C][C]6.291111111[/C][C]19.0154914491215[/C][C]-12.7243803381215[/C][/ROW]
[ROW][C]140[/C][C]8.726111111[/C][C]15.2610954659671[/C][C]-6.53498435496711[/C][/ROW]
[ROW][C]141[/C][C]12.97166667[/C][C]16.0435585539387[/C][C]-3.07189188393875[/C][/ROW]
[ROW][C]142[/C][C]36.58277778[/C][C]39.5328332130684[/C][C]-2.95005543306837[/C][/ROW]
[ROW][C]143[/C][C]25.48194444[/C][C]16.9404563404711[/C][C]8.54148809952894[/C][/ROW]
[ROW][C]144[/C][C]67.98583333[/C][C]59.7156841572209[/C][C]8.27014917277913[/C][/ROW]
[ROW][C]145[/C][C]51.25277778[/C][C]55.9321514606087[/C][C]-4.67937368060872[/C][/ROW]
[ROW][C]146[/C][C]22.18416667[/C][C]27.2456593079822[/C][C]-5.06149263798217[/C][/ROW]
[ROW][C]147[/C][C]35.67305556[/C][C]42.8369500053184[/C][C]-7.16389444531838[/C][/ROW]
[ROW][C]148[/C][C]27.1775[/C][C]33.9282046253826[/C][C]-6.75070462538256[/C][/ROW]
[ROW][C]149[/C][C]10.615[/C][C]14.057001265731[/C][C]-3.44200126573101[/C][/ROW]
[ROW][C]150[/C][C]41.9725[/C][C]45.4546741669359[/C][C]-3.48217416693595[/C][/ROW]
[ROW][C]151[/C][C]75.68277778[/C][C]67.1010467318911[/C][C]8.5817310481089[/C][/ROW]
[ROW][C]152[/C][C]47.915[/C][C]49.1275171772722[/C][C]-1.21251717727222[/C][/ROW]
[ROW][C]153[/C][C]30.01194444[/C][C]28.9929001549243[/C][C]1.01904428507571[/C][/ROW]
[ROW][C]154[/C][C]91.14083333[/C][C]76.6059115016489[/C][C]14.5349218283511[/C][/ROW]
[ROW][C]155[/C][C]69.60527778[/C][C]75.2281933900291[/C][C]-5.62291561002913[/C][/ROW]
[ROW][C]156[/C][C]97.51861111[/C][C]92.2724576862064[/C][C]5.24615342379359[/C][/ROW]
[ROW][C]157[/C][C]43.89305556[/C][C]45.7201867897657[/C][C]-1.82713122976568[/C][/ROW]
[ROW][C]158[/C][C]27.46277778[/C][C]20.9532737463113[/C][C]6.50950403368867[/C][/ROW]
[ROW][C]159[/C][C]23.73305556[/C][C]34.1177757393418[/C][C]-10.3847201793418[/C][/ROW]
[ROW][C]160[/C][C]63.67833333[/C][C]49.1688307403606[/C][C]14.5095025896394[/C][/ROW]
[ROW][C]161[/C][C]97.67194444[/C][C]66.292161435553[/C][C]31.379783004447[/C][/ROW]
[ROW][C]162[/C][C]23.39083333[/C][C]35.1167045965494[/C][C]-11.7258712665494[/C][/ROW]
[ROW][C]163[/C][C]33.45694444[/C][C]28.8531568071711[/C][C]4.60378763282892[/C][/ROW]
[ROW][C]164[/C][C]90.16611111[/C][C]72.7379631119445[/C][C]17.4281479980555[/C][/ROW]
[ROW][C]165[/C][C]36.40805556[/C][C]39.3121785379466[/C][C]-2.90412297794655[/C][/ROW]
[ROW][C]166[/C][C]56.74194444[/C][C]58.5251491191358[/C][C]-1.7832046791358[/C][/ROW]
[ROW][C]167[/C][C]45.98416667[/C][C]47.6439183556929[/C][C]-1.65975168569288[/C][/ROW]
[ROW][C]168[/C][C]39.36722222[/C][C]31.4325278561905[/C][C]7.9346943638095[/C][/ROW]
[ROW][C]169[/C][C]32.23555556[/C][C]33.4230110772514[/C][C]-1.18745551725137[/C][/ROW]
[ROW][C]170[/C][C]69.4575[/C][C]34.8564628645146[/C][C]34.6010371354854[/C][/ROW]
[ROW][C]171[/C][C]83.27083333[/C][C]58.8631722663003[/C][C]24.4076610636997[/C][/ROW]
[ROW][C]172[/C][C]54.39944444[/C][C]65.6027202735886[/C][C]-11.2032758335886[/C][/ROW]
[ROW][C]173[/C][C]48.12777778[/C][C]31.4512478151306[/C][C]16.6765299648694[/C][/ROW]
[ROW][C]174[/C][C]70.69111111[/C][C]72.5626342474916[/C][C]-1.87152313749164[/C][/ROW]
[ROW][C]175[/C][C]28.99694444[/C][C]80.471868084165[/C][C]-51.474923644165[/C][/ROW]
[ROW][C]176[/C][C]37.80111111[/C][C]21.9752484727715[/C][C]15.8258626372285[/C][/ROW]
[ROW][C]177[/C][C]55.41[/C][C]61.9442341907138[/C][C]-6.53423419071377[/C][/ROW]
[ROW][C]178[/C][C]25.69416667[/C][C]23.1924092879491[/C][C]2.50175738205093[/C][/ROW]
[ROW][C]179[/C][C]62.31388889[/C][C]78.8625210225754[/C][C]-16.5486321325754[/C][/ROW]
[ROW][C]180[/C][C]37.71694444[/C][C]27.9668615130865[/C][C]9.75008292691352[/C][/ROW]
[ROW][C]181[/C][C]20.66888889[/C][C]20.4882881652497[/C][C]0.180600724750338[/C][/ROW]
[ROW][C]182[/C][C]22.56666667[/C][C]35.7817975628229[/C][C]-13.2151308928229[/C][/ROW]
[ROW][C]183[/C][C]4.08[/C][C]5.99742750077519[/C][C]-1.91742750077519[/C][/ROW]
[ROW][C]184[/C][C]50.45361111[/C][C]40.6852830454086[/C][C]9.76832806459139[/C][/ROW]
[ROW][C]185[/C][C]75.51555556[/C][C]62.8986005373352[/C][C]12.6169550226647[/C][/ROW]
[ROW][C]186[/C][C]1.999722222[/C][C]6.48977503032483[/C][C]-4.49005280832483[/C][/ROW]
[ROW][C]187[/C][C]12.96111111[/C][C]11.0284242961088[/C][C]1.9326868138912[/C][/ROW]
[ROW][C]188[/C][C]4.874166667[/C][C]4.99246199987214[/C][C]-0.118295332872141[/C][/ROW]
[ROW][C]189[/C][C]37.04666667[/C][C]27.2369611549617[/C][C]9.8097055150383[/C][/ROW]
[ROW][C]190[/C][C]26.45194444[/C][C]35.3350112569096[/C][C]-8.88306681690958[/C][/ROW]
[ROW][C]191[/C][C]42.38916667[/C][C]38.3384500537497[/C][C]4.05071661625029[/C][/ROW]
[ROW][C]192[/C][C]27.26277778[/C][C]20.1170033352876[/C][C]7.14577444471243[/C][/ROW]
[ROW][C]193[/C][C]22.11638889[/C][C]25.096004650374[/C][C]-2.97961576037401[/C][/ROW]
[ROW][C]194[/C][C]16.44277778[/C][C]22.1307243020949[/C][C]-5.68794652209491[/C][/ROW]
[ROW][C]195[/C][C]38.87277778[/C][C]39.0808591999452[/C][C]-0.208081419945244[/C][/ROW]
[ROW][C]196[/C][C]32.94777778[/C][C]30.4029215319308[/C][C]2.54485624806922[/C][/ROW]
[ROW][C]197[/C][C]20.24444444[/C][C]20.4634759824254[/C][C]-0.219031542425358[/C][/ROW]
[ROW][C]198[/C][C]18.1875[/C][C]22.9059712359784[/C][C]-4.71847123597844[/C][/ROW]
[ROW][C]199[/C][C]27.67861111[/C][C]28.8090180099918[/C][C]-1.13040689999183[/C][/ROW]
[ROW][C]200[/C][C]19.99027778[/C][C]26.5635773846195[/C][C]-6.57329960461951[/C][/ROW]
[ROW][C]201[/C][C]21.46444444[/C][C]21.5790339725739[/C][C]-0.114589532573944[/C][/ROW]
[ROW][C]202[/C][C]13.69138889[/C][C]21.8231622878856[/C][C]-8.13177339788563[/C][/ROW]
[ROW][C]203[/C][C]37.53638889[/C][C]27.1981323844161[/C][C]10.3382565055839[/C][/ROW]
[ROW][C]204[/C][C]30.12388889[/C][C]24.3827992785576[/C][C]5.7410896114424[/C][/ROW]
[ROW][C]205[/C][C]24.92944444[/C][C]24.5052485095975[/C][C]0.424195930402452[/C][/ROW]
[ROW][C]206[/C][C]12.30444444[/C][C]19.1173809898977[/C][C]-6.81293654989775[/C][/ROW]
[ROW][C]207[/C][C]21.56888889[/C][C]24.1074329684418[/C][C]-2.53854407844179[/C][/ROW]
[ROW][C]208[/C][C]50.42444444[/C][C]26.4809046707327[/C][C]23.9435397692673[/C][/ROW]
[ROW][C]209[/C][C]37.2275[/C][C]26.2287397732136[/C][C]10.9987602267864[/C][/ROW]
[ROW][C]210[/C][C]34.46222222[/C][C]31.054017624347[/C][C]3.40820459565297[/C][/ROW]
[ROW][C]211[/C][C]25.73055556[/C][C]18.5968591565877[/C][C]7.13369640341227[/C][/ROW]
[ROW][C]212[/C][C]33.84666667[/C][C]27.5006122599491[/C][C]6.34605441005086[/C][/ROW]
[ROW][C]213[/C][C]14.69861111[/C][C]21.8745174073216[/C][C]-7.1759062973216[/C][/ROW]
[ROW][C]214[/C][C]22.74222222[/C][C]25.129425525698[/C][C]-2.38720330569803[/C][/ROW]
[ROW][C]215[/C][C]16.38361111[/C][C]19.947523070533[/C][C]-3.56391196053302[/C][/ROW]
[ROW][C]216[/C][C]14.86527778[/C][C]17.8889837367686[/C][C]-3.02370595676862[/C][/ROW]
[ROW][C]217[/C][C]16.89222222[/C][C]21.1721597067535[/C][C]-4.27993748675351[/C][/ROW]
[ROW][C]218[/C][C]15.65972222[/C][C]18.0646472039789[/C][C]-2.40492498397892[/C][/ROW]
[ROW][C]219[/C][C]18.19166667[/C][C]22.5535523905309[/C][C]-4.3618857205309[/C][/ROW]
[ROW][C]220[/C][C]22.48583333[/C][C]17.4327610484358[/C][C]5.05307228156424[/C][/ROW]
[ROW][C]221[/C][C]21.195[/C][C]26.4684993566279[/C][C]-5.27349935662786[/C][/ROW]
[ROW][C]222[/C][C]28.89194444[/C][C]29.6092555364683[/C][C]-0.717311096468262[/C][/ROW]
[ROW][C]223[/C][C]27.25111111[/C][C]32.7071273434118[/C][C]-5.45601623341181[/C][/ROW]
[ROW][C]224[/C][C]18.88583333[/C][C]23.8636792382195[/C][C]-4.97784590821951[/C][/ROW]
[ROW][C]225[/C][C]8.608055556[/C][C]14.4945874121214[/C][C]-5.88653185612143[/C][/ROW]
[ROW][C]226[/C][C]37.62722222[/C][C]25.7712618574361[/C][C]11.8559603625639[/C][/ROW]
[ROW][C]227[/C][C]20.41777778[/C][C]18.590239563628[/C][C]1.82753821637203[/C][/ROW]
[ROW][C]228[/C][C]17.53416667[/C][C]27.4422560724476[/C][C]-9.90808940244765[/C][/ROW]
[ROW][C]229[/C][C]17.015[/C][C]23.8713479571852[/C][C]-6.85634795718519[/C][/ROW]
[ROW][C]230[/C][C]20.80944444[/C][C]33.5611247075113[/C][C]-12.7516802675113[/C][/ROW]
[ROW][C]231[/C][C]8.826111111[/C][C]12.8991700470089[/C][C]-4.07305893600885[/C][/ROW]
[ROW][C]232[/C][C]22.62138889[/C][C]25.8088141905352[/C][C]-3.18742530053518[/C][/ROW]
[ROW][C]233[/C][C]24.21833333[/C][C]25.8909303256256[/C][C]-1.67259699562563[/C][/ROW]
[ROW][C]234[/C][C]13.91388889[/C][C]19.8038417760083[/C][C]-5.88995288600829[/C][/ROW]
[ROW][C]235[/C][C]18.2625[/C][C]26.7581755902521[/C][C]-8.49567559025214[/C][/ROW]
[ROW][C]236[/C][C]15.73694444[/C][C]28.0072128414132[/C][C]-12.2702684014132[/C][/ROW]
[ROW][C]237[/C][C]43.99972222[/C][C]23.7768597684742[/C][C]20.2228624515258[/C][/ROW]
[ROW][C]238[/C][C]12.90416667[/C][C]20.6770178092564[/C][C]-7.7728511392564[/C][/ROW]
[ROW][C]239[/C][C]20.45111111[/C][C]24.0925163529545[/C][C]-3.64140524295453[/C][/ROW]
[ROW][C]240[/C][C]10.66527778[/C][C]18.8052463685246[/C][C]-8.13996858852458[/C][/ROW]
[ROW][C]241[/C][C]25.5275[/C][C]21.1227162183422[/C][C]4.40478378165777[/C][/ROW]
[ROW][C]242[/C][C]38.75722222[/C][C]28.4744940613179[/C][C]10.2827281586821[/C][/ROW]
[ROW][C]243[/C][C]14.49[/C][C]23.9443768660116[/C][C]-9.4543768660116[/C][/ROW]
[ROW][C]244[/C][C]14.32416667[/C][C]20.667775572834[/C][C]-6.34360890283397[/C][/ROW]
[ROW][C]245[/C][C]19.5975[/C][C]22.0034365565646[/C][C]-2.40593655656459[/C][/ROW]
[ROW][C]246[/C][C]23.57111111[/C][C]26.0920321548576[/C][C]-2.52092104485763[/C][/ROW]
[ROW][C]247[/C][C]28.48277778[/C][C]32.2756383181622[/C][C]-3.79286053816221[/C][/ROW]
[ROW][C]248[/C][C]24.07722222[/C][C]18.3914551231938[/C][C]5.68576709680619[/C][/ROW]
[ROW][C]249[/C][C]23.80805556[/C][C]19.5170230954251[/C][C]4.29103246457487[/C][/ROW]
[ROW][C]250[/C][C]9.628333333[/C][C]16.6249524016051[/C][C]-6.99661906860509[/C][/ROW]
[ROW][C]251[/C][C]41.82777778[/C][C]28.3652315019071[/C][C]13.4625462780929[/C][/ROW]
[ROW][C]252[/C][C]27.66972222[/C][C]32.2843543019788[/C][C]-4.61463208197875[/C][/ROW]
[ROW][C]253[/C][C]5.374722222[/C][C]9.13422915112234[/C][C]-3.75950692912234[/C][/ROW]
[ROW][C]254[/C][C]27.60361111[/C][C]19.7888726462307[/C][C]7.81473846376929[/C][/ROW]
[ROW][C]255[/C][C]23.95277778[/C][C]21.130956237671[/C][C]2.82182154232902[/C][/ROW]
[ROW][C]256[/C][C]8.565833333[/C][C]8.85174198622975[/C][C]-0.285908653229754[/C][/ROW]
[ROW][C]257[/C][C]8.807222222[/C][C]19.9658722251706[/C][C]-11.1586500031706[/C][/ROW]
[ROW][C]258[/C][C]24.94611111[/C][C]23.5417466481207[/C][C]1.40436446187926[/C][/ROW]
[ROW][C]259[/C][C]17.24666667[/C][C]17.6476009242964[/C][C]-0.400934254296356[/C][/ROW]
[ROW][C]260[/C][C]11.15305556[/C][C]15.0112858815742[/C][C]-3.85823032157425[/C][/ROW]
[ROW][C]261[/C][C]7.676111111[/C][C]13.2239263531477[/C][C]-5.54781524214769[/C][/ROW]
[ROW][C]262[/C][C]21.38611111[/C][C]28.403169973956[/C][C]-7.01705886395603[/C][/ROW]
[ROW][C]263[/C][C]10.40555556[/C][C]9.52317326015812[/C][C]0.882382299841881[/C][/ROW]
[ROW][C]264[/C][C]15.04361111[/C][C]25.2463552494598[/C][C]-10.2027441394598[/C][/ROW]
[ROW][C]265[/C][C]13.85055556[/C][C]20.254632862969[/C][C]-6.40407730296903[/C][/ROW]
[ROW][C]266[/C][C]23.42694444[/C][C]25.7003515275663[/C][C]-2.27340708756634[/C][/ROW]
[ROW][C]267[/C][C]17.82638889[/C][C]27.0602730125815[/C][C]-9.23388412258147[/C][/ROW]
[ROW][C]268[/C][C]16.495[/C][C]22.0270375816036[/C][C]-5.53203758160355[/C][/ROW]
[ROW][C]269[/C][C]33.14111111[/C][C]24.6813352954006[/C][C]8.45977581459936[/C][/ROW]
[ROW][C]270[/C][C]21.30611111[/C][C]30.8171168420482[/C][C]-9.51100573204824[/C][/ROW]
[ROW][C]271[/C][C]28.72916667[/C][C]21.5859272093698[/C][C]7.14323946063024[/C][/ROW]
[ROW][C]272[/C][C]19.54[/C][C]21.4082750442006[/C][C]-1.86827504420061[/C][/ROW]
[ROW][C]273[/C][C]12.05833333[/C][C]7.10303616122207[/C][C]4.95529716877793[/C][/ROW]
[ROW][C]274[/C][C]29.12166667[/C][C]29.7335759780559[/C][C]-0.611909308055905[/C][/ROW]
[ROW][C]275[/C][C]17.28194444[/C][C]18.7352763552931[/C][C]-1.45333191529311[/C][/ROW]
[ROW][C]276[/C][C]19.25111111[/C][C]28.6183181771469[/C][C]-9.36720706714694[/C][/ROW]
[ROW][C]277[/C][C]14.75472222[/C][C]14.4181297814955[/C][C]0.336592438504459[/C][/ROW]
[ROW][C]278[/C][C]5.49[/C][C]8.8672643155979[/C][C]-3.3772643155979[/C][/ROW]
[ROW][C]279[/C][C]24.07777778[/C][C]25.1322795679286[/C][C]-1.05450178792861[/C][/ROW]
[ROW][C]280[/C][C]23.3625[/C][C]20.0064027079513[/C][C]3.35609729204865[/C][/ROW]
[ROW][C]281[/C][C]21.65138889[/C][C]25.0522554663912[/C][C]-3.40086657639121[/C][/ROW]
[ROW][C]282[/C][C]24.75361111[/C][C]25.7543296920461[/C][C]-1.0007185820461[/C][/ROW]
[ROW][C]283[/C][C]25.27916667[/C][C]22.1502048467025[/C][C]3.12896182329749[/C][/ROW]
[ROW][C]284[/C][C]11.18[/C][C]9.1823768166763[/C][C]1.9976231833237[/C][/ROW]
[ROW][C]285[/C][C]17.82972222[/C][C]17.2922140234537[/C][C]0.537508196546342[/C][/ROW]
[ROW][C]286[/C][C]14.12694444[/C][C]22.6372435976928[/C][C]-8.5102991576928[/C][/ROW]
[ROW][C]287[/C][C]15.72583333[/C][C]15.6291481212348[/C][C]0.0966852087652423[/C][/ROW]
[ROW][C]288[/C][C]17.44222222[/C][C]23.6762387970302[/C][C]-6.23401657703016[/C][/ROW]
[ROW][C]289[/C][C]20.14861111[/C][C]19.459077731122[/C][C]0.689533378878005[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186260&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186260&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
158.5852777855.95762467429332.62765310570674
233.6061111145.3612285207549-11.7551174107549
349.0350.7499553046393-1.71995530463934
449.8113888964.0284560872026-14.2170671972026
534.2180555634.6138269191653-0.395771359165287
614.6516666724.1564497224905-9.50478305249051
7107.092777867.616805899367439.4759719006326
89.21388888915.6892604914575-6.47537160245752
928.2347222217.697554790713210.5371674292867
1041.4058333342.9203491978953-1.51451586789529
1145.9572222244.51219942053881.44502279946118
1265.892554.695096919848311.1974030801517
1348.1461111160.7856429628409-12.6395318528409
1436.9808333339.0213497043504-2.04051637435039
1571.9091666765.48083785400336.42832881599674
1650.0230555646.63297646189433.39007909810575
1790.2219444487.97373159699782.24821284300216
1864.1566666765.5744584655032-1.41779179550323
1965.7736111154.667359539777711.1062515702223
2037.6313888952.1251302706354-14.4937413806354
2156.3680555670.6580639214981-14.2900083614981
2259.7630555664.5259332042936-4.76287764429359
2395.6380555651.545290861555444.0927646984446
2442.7597222239.29340539315863.46631682684141
2536.9286111160.1003008013295-23.1716896913295
2648.5344444467.3813358565521-18.8468914165521
2748.4486111151.4066654302798-2.95805432027977
2862.6522222254.22990466083118.42231755916889
2962.1261.52477532472980.595224675270159
3034.6713888934.64506603043910.0263228595609374
3161.5827777862.0780241801644-0.495246400164443
3258.5463888963.7545289178702-5.20814002787024
3347.2961111146.65292043903130.643190670968715
3472.3780555671.17993409195571.19812146804428
3523.5702777837.5056671923153-13.9353894123153
3681.7844444465.219708451225216.5647359887748
3728.0586111122.97717010618665.08144100381336
3859.9002777848.405876530427311.4944012495727
3990.307557.002624329980533.3048756700195
401.9933333334.2343957460541-2.24106241305409
4146.5394444442.57143293014423.96801150985583
4229.5577777824.7986418669884.75913591301203
4326.8222222228.289424807855-1.46720258785499
4473.8247222259.27206937362114.552652846379
4574.9030555660.0953259539714.80772960603
4641.4245.606439090952-4.18643909095202
4748.8436.352062803807412.4879371961926
4842.4641666745.1612820941838-2.6971154241838
4931.0180555635.5953840229757-4.57732846297573
5032.3355555641.7278849679659-9.39232940796586
51100.639166755.744760731020744.8944059689793
5221.8888888926.773185987-4.88429709699996
5350.8797222261.1007551939429-10.2210329739429
5477.212574.71094874260682.50155125739323
5541.8413888955.0355090855353-13.1941201955353
5646.8913888949.7726935149745-2.88130462497447
576.7188888899.23601619603056-2.51712730703056
5891.4630555660.760793731978330.7022618280217
5918.0636111123.0991947339955-5.03558362399554
6028.082523.90781523270974.17468476729028
6160.8183333351.15694121908049.66139211091964
6267.7922222273.1857187394844-5.39349651948445
6394.8805555656.816746903613338.0638086563867
6428.7769444423.09800269164455.67894174835545
6564.8133333360.01275937836644.8005739516336
6671.2394444471.6991063766077-0.459661936607715
6757.2669444449.543630913397.72331352661001
6886.5202777877.62026975345728.90000802654277
6965.564.71110512179320.788894878206835
7049.427544.32198649296145.10551350703856
7157.5488888946.930319013376310.6185698766237
7254.5980555641.54381961781613.054235942184
7348.3844444445.20882181968463.17562262031537
7439.7905555650.0581054687652-10.2675499087652
7552.0997222253.5283099104745-1.42858769047452
7652.1336111164.0817514776344-11.9481403676344
7733.0661.3796134475157-28.3196134475157
7850.6088888955.7704714888041-5.16158259880408
7920.43524.8287383409717-4.39373834097168
8054.1608333352.68258707426231.47824625573767
8146.5244444448.7573803565658-2.23293591656579
8239.9322222261.6401230864038-21.7079008664038
8376.5391666767.2030389367049.33612773329596
8467.5552777856.066308065226711.4889697147733
8550.8330555668.0615181926053-17.2284626326053
8637.6802777857.0181828974576-19.3379051174577
8742.3052777846.6180348556181-4.31275707561813
8833.3947222236.4696145176314-3.07489229763141
8996.2458333371.68078785470124.565045475299
9040.4972222230.56168637097889.93553584902122
9153.7052777862.1877492305707-8.48247145057067
9222.4869444429.6513733533023-7.16442891330235
9334.1038888925.2561341027518.84775478724897
9436.2736111149.8449510289583-13.5713399189583
9531.2808333331.4363052307566-0.155471900756565
9679.5744444446.055072558158133.5193718818418
9766.9627777857.3009880458229.661789734178
9841.23578.8059231489266-37.5709231489266
9956.8647222246.386621298211210.4781009217888
10050.577570.7849679657504-20.2074679657504
10138.9844444432.40603058356146.57841385643855
10261.2544444457.01356142518574.2408830148143
10367.5166666748.719002559719218.7976641102808
10445.212552.3137102398854-7.10121023988536
10550.7258333358.3993218559956-7.67348852599556
10664.4827777878.2632713121663-13.7804935321663
10773.6994444477.0683648413026-3.3689204013026
10823.7705555628.8007281474571-5.03017258745711
10986.3441666774.628232667182111.7159340028179
11062.5166666765.5807987726849-3.06413210268493
11164.532571.7317145901189-7.19921459011893
11240.2683333336.26242802608914.00590530391091
11312.0241666722.2282929979839-10.2041263279839
11443.26541.84248160326521.4225183967348
11545.752554.48940900996-8.73690900996004
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11765.4038888977.4610926749679-12.0572037849679
11861.3336111133.922683738425327.4109273715747
11927.6294444444.7573568931618-17.1279124531618
12025.7391666728.9488220101261-3.20965534012606
12137.0355555636.13042066972250.905134890277491
12217.0447222220.0145364506251-2.96981423062511
12334.9805555627.69068223461757.28987332538249
12427.9861111160.262908594378-32.276797484378
12562.3747222249.367117699764713.0076045202353
12622.8655555619.87066039702252.99489516297747
12728.3361111124.11635353564634.21975757435374
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12967.6419444477.9278619622523-10.2859175222523
1306.3716666678.52629868034388-2.15463201334388
13111.546111119.948904219368821.59720689063118
13242.3538888960.5996247146961-18.2457358246961
13317.182519.5044911411566-2.32199114115664
13427.7563888933.8588679879052-6.1024790979052
13536.8019444448.7784339804851-11.9764895404851
13688.16566.03524437483522.129755625165
1375.8483333335.449584985947440.398748347052562
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1396.29111111119.0154914491215-12.7243803381215
1408.72611111115.2610954659671-6.53498435496711
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14622.1841666727.2456593079822-5.06149263798217
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15247.91549.1275171772722-1.21251717727222
15330.0119444428.99290015492431.01904428507571
15491.1408333376.605911501648914.5349218283511
15569.6052777875.2281933900291-5.62291561002913
15697.5186111192.27245768620645.24615342379359
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15827.4627777820.95327374631136.50950403368867
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16063.6783333349.168830740360614.5095025896394
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16333.4569444428.85315680717114.60378763282892
16490.1661111172.737963111944517.4281479980555
16536.4080555639.3121785379466-2.90412297794655
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16745.9841666747.6439183556929-1.65975168569288
16839.3672222231.43252785619057.9346943638095
16932.2355555633.4230110772514-1.18745551725137
17069.457534.856462864514634.6010371354854
17183.2708333358.863172266300324.4076610636997
17254.3994444465.6027202735886-11.2032758335886
17348.1277777831.451247815130616.6765299648694
17470.6911111172.5626342474916-1.87152313749164
17528.9969444480.471868084165-51.474923644165
17637.8011111121.975248472771515.8258626372285
17755.4161.9442341907138-6.53423419071377
17825.6941666723.19240928794912.50175738205093
17962.3138888978.8625210225754-16.5486321325754
18037.7169444427.96686151308659.75008292691352
18120.6688888920.48828816524970.180600724750338
18222.5666666735.7817975628229-13.2151308928229
1834.085.99742750077519-1.91742750077519
18450.4536111140.68528304540869.76832806459139
18575.5155555662.898600537335212.6169550226647
1861.9997222226.48977503032483-4.49005280832483
18712.9611111111.02842429610881.9326868138912
1884.8741666674.99246199987214-0.118295332872141
18937.0466666727.23696115496179.8097055150383
19026.4519444435.3350112569096-8.88306681690958
19142.3891666738.33845005374974.05071661625029
19227.2627777820.11700333528767.14577444471243
19322.1163888925.096004650374-2.97961576037401
19416.4427777822.1307243020949-5.68794652209491
19538.8727777839.0808591999452-0.208081419945244
19632.9477777830.40292153193082.54485624806922
19720.2444444420.4634759824254-0.219031542425358
19818.187522.9059712359784-4.71847123597844
19927.6786111128.8090180099918-1.13040689999183
20019.9902777826.5635773846195-6.57329960461951
20121.4644444421.5790339725739-0.114589532573944
20213.6913888921.8231622878856-8.13177339788563
20337.5363888927.198132384416110.3382565055839
20430.1238888924.38279927855765.7410896114424
20524.9294444424.50524850959750.424195930402452
20612.3044444419.1173809898977-6.81293654989775
20721.5688888924.1074329684418-2.53854407844179
20850.4244444426.480904670732723.9435397692673
20937.227526.228739773213610.9987602267864
21034.4622222231.0540176243473.40820459565297
21125.7305555618.59685915658777.13369640341227
21233.8466666727.50061225994916.34605441005086
21314.6986111121.8745174073216-7.1759062973216
21422.7422222225.129425525698-2.38720330569803
21516.3836111119.947523070533-3.56391196053302
21614.8652777817.8889837367686-3.02370595676862
21716.8922222221.1721597067535-4.27993748675351
21815.6597222218.0646472039789-2.40492498397892
21918.1916666722.5535523905309-4.3618857205309
22022.4858333317.43276104843585.05307228156424
22121.19526.4684993566279-5.27349935662786
22228.8919444429.6092555364683-0.717311096468262
22327.2511111132.7071273434118-5.45601623341181
22418.8858333323.8636792382195-4.97784590821951
2258.60805555614.4945874121214-5.88653185612143
22637.6272222225.771261857436111.8559603625639
22720.4177777818.5902395636281.82753821637203
22817.5341666727.4422560724476-9.90808940244765
22917.01523.8713479571852-6.85634795718519
23020.8094444433.5611247075113-12.7516802675113
2318.82611111112.8991700470089-4.07305893600885
23222.6213888925.8088141905352-3.18742530053518
23324.2183333325.8909303256256-1.67259699562563
23413.9138888919.8038417760083-5.88995288600829
23518.262526.7581755902521-8.49567559025214
23615.7369444428.0072128414132-12.2702684014132
23743.9997222223.776859768474220.2228624515258
23812.9041666720.6770178092564-7.7728511392564
23920.4511111124.0925163529545-3.64140524295453
24010.6652777818.8052463685246-8.13996858852458
24125.527521.12271621834224.40478378165777
24238.7572222228.474494061317910.2827281586821
24314.4923.9443768660116-9.4543768660116
24414.3241666720.667775572834-6.34360890283397
24519.597522.0034365565646-2.40593655656459
24623.5711111126.0920321548576-2.52092104485763
24728.4827777832.2756383181622-3.79286053816221
24824.0772222218.39145512319385.68576709680619
24923.8080555619.51702309542514.29103246457487
2509.62833333316.6249524016051-6.99661906860509
25141.8277777828.365231501907113.4625462780929
25227.6697222232.2843543019788-4.61463208197875
2535.3747222229.13422915112234-3.75950692912234
25427.6036111119.78887264623077.81473846376929
25523.9527777821.1309562376712.82182154232902
2568.5658333338.85174198622975-0.285908653229754
2578.80722222219.9658722251706-11.1586500031706
25824.9461111123.54174664812071.40436446187926
25917.2466666717.6476009242964-0.400934254296356
26011.1530555615.0112858815742-3.85823032157425
2617.67611111113.2239263531477-5.54781524214769
26221.3861111128.403169973956-7.01705886395603
26310.405555569.523173260158120.882382299841881
26415.0436111125.2463552494598-10.2027441394598
26513.8505555620.254632862969-6.40407730296903
26623.4269444425.7003515275663-2.27340708756634
26717.8263888927.0602730125815-9.23388412258147
26816.49522.0270375816036-5.53203758160355
26933.1411111124.68133529540068.45977581459936
27021.3061111130.8171168420482-9.51100573204824
27128.7291666721.58592720936987.14323946063024
27219.5421.4082750442006-1.86827504420061
27312.058333337.103036161222074.95529716877793
27429.1216666729.7335759780559-0.611909308055905
27517.2819444418.7352763552931-1.45333191529311
27619.2511111128.6183181771469-9.36720706714694
27714.7547222214.41812978149550.336592438504459
2785.498.8672643155979-3.3772643155979
27924.0777777825.1322795679286-1.05450178792861
28023.362520.00640270795133.35609729204865
28121.6513888925.0522554663912-3.40086657639121
28224.7536111125.7543296920461-1.0007185820461
28325.2791666722.15020484670253.12896182329749
28411.189.18237681667631.9976231833237
28517.8297222217.29221402345370.537508196546342
28614.1269444422.6372435976928-8.5102991576928
28715.7258333315.62914812123480.0966852087652423
28817.4422222223.6762387970302-6.23401657703016
28920.1486111119.4590777311220.689533378878005







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.9633272950389530.07334540992209410.0366727049610471
80.9257278719698450.148544256060310.0742721280301548
90.8768804218282650.246239156343470.123119578171735
100.8200440944803940.3599118110392120.179955905519606
110.7383029620567220.5233940758865560.261697037943278
120.8112905144407370.3774189711185250.188709485559263
130.7594717171269940.4810565657460110.240528282873006
140.6868834637296840.6262330725406330.313116536270316
150.6200816606859570.7598366786280850.379918339314043
160.5574093092555460.8851813814889080.442590690744454
170.4975217044178910.9950434088357830.502478295582109
180.4600968271987680.9201936543975360.539903172801232
190.4376140690944980.8752281381889970.562385930905501
200.6120534072361450.7758931855277110.387946592763855
210.6763611649158890.6472776701682220.323638835084111
220.6224309472136410.7551381055727190.377569052786359
230.9700738786697050.05985224266058970.0299261213302948
240.9581349330985830.08373013380283440.0418650669014172
250.971065430073740.05786913985252080.0289345699262604
260.9904115224295790.01917695514084130.00958847757042065
270.9861806974424610.02763860511507850.0138193025575392
280.9827730935856340.03445381282873240.0172269064143662
290.976168396970430.047663206059140.02383160302957
300.9675974783456250.06480504330875020.0324025216543751
310.957018727007380.0859625459852390.0429812729926195
320.9441225345352980.1117549309294040.0558774654647019
330.9387014420926180.1225971158147640.0612985579073822
340.9223383556435420.1553232887129150.0776616443564575
350.9193412962989720.1613174074020570.0806587037010284
360.9272756437750090.1454487124499820.0727243562249912
370.9087922203505650.1824155592988690.0912077796494347
380.9046413028410360.1907173943179280.0953586971589642
390.9805305420149830.03893891597003460.0194694579850173
400.9775208571329690.04495828573406230.0224791428670311
410.9707514236463880.05849715270722410.029248576353612
420.9622261790341060.07554764193178840.0377738209658942
430.9535637455788750.09287250884225080.0464362544211254
440.9528895153410920.09422096931781650.0471104846589083
450.9493446725039440.1013106549921110.0506553274960556
460.9369970724263790.1260058551472410.0630029275736205
470.9299415605742390.1401168788515220.0700584394257612
480.9142876995621430.1714246008757140.0857123004378569
490.8971647608597580.2056704782804850.102835239140242
500.8797055794691070.2405888410617860.120294420530893
510.9940340652606590.01193186947868270.00596593473934134
520.9921492898439650.01570142031206950.00785071015603473
530.9916068229402570.01678635411948620.0083931770597431
540.9889502947074480.02209941058510350.0110497052925517
550.9902235773793940.01955284524121190.00977642262060597
560.9877638052532880.02447238949342460.0122361947467123
570.984980607384950.03003878523010060.0150193926150503
580.9964426680872020.007114663825595680.00355733191279784
590.9954114781371120.009177043725776870.00458852186288843
600.9939691570891980.01206168582160390.00603084291080194
610.9928775573641270.01424488527174620.00712244263587309
620.9914190228499170.01716195430016640.00858097715008321
630.9984558538330810.003088292333838120.00154414616691906
640.9979858515565470.004028296886906360.00201414844345318
650.9974259153222670.005148169355466360.00257408467773318
660.9968412083278760.006317583344248650.00315879167212433
670.9960796411688770.007840717662245850.00392035883112292
680.9952935693094980.009412861381003920.00470643069050196
690.9949849826944960.01003003461100760.00501501730550381
700.9939767403253610.01204651934927780.00602325967463891
710.9935483270614350.012903345877130.00645167293856501
720.9936621210416240.01267575791675160.00633787895837582
730.9918799303582880.01624013928342320.0081200696417116
740.9922838829390550.015432234121890.00771611706094498
750.990085033754340.0198299324913210.00991496624566048
760.9920043701687790.01599125966244130.00799562983122066
770.9983734176498870.003253164700225840.00162658235011292
780.9979052614059450.004189477188109250.00209473859405462
790.997295805761970.005408388476059640.00270419423802982
800.9964460477375690.007107904524861710.00355395226243086
810.9954686001160380.009062799767924750.00453139988396238
820.997526565140170.004946869719659480.00247343485982974
830.9971924835290540.005615032941891320.00280751647094566
840.9969937233666970.00601255326660520.0030062766333026
850.9982258015712520.003548396857495920.00177419842874796
860.9989451295411870.002109740917626650.00105487045881333
870.9986283358843160.002743328231368660.00137166411568433
880.9982162680287020.003567463942596480.00178373197129824
890.9992817277304480.001436544539103380.00071827226955169
900.9992102483916840.00157950321663150.000789751608315751
910.9990926343572450.001814731285510260.000907365642755128
920.9989593751511990.002081249697602850.00104062484880143
930.9988095358340940.002380928331812460.00119046416590623
940.998919308504320.002161382991360080.00108069149568004
950.9985567836175970.002886432764806550.00144321638240328
960.9998211477750780.0003577044498437330.000178852224921867
970.9998046537320160.0003906925359675660.000195346267983783
980.999991755547761.64889044800592e-058.24445224002961e-06
990.999991073666031.78526679391225e-058.92633396956126e-06
1000.9999955578948528.88421029538365e-064.44210514769182e-06
1010.9999940785480871.18429038252323e-055.92145191261613e-06
1020.9999917383939141.65232121712319e-058.26160608561596e-06
1030.9999953785159329.24296813605275e-064.62148406802637e-06
1040.9999941226200651.17547598702416e-055.87737993512082e-06
1050.9999926459815981.47080368039995e-057.35401840199975e-06
1060.9999933552582371.32894835268643e-056.64474176343215e-06
1070.9999903811917691.92376164624486e-059.61880823122432e-06
1080.9999871016348762.5796730248409e-051.28983651242045e-05
1090.9999872223395362.55553209284098e-051.27776604642049e-05
1100.9999817377566343.65244867329521e-051.82622433664761e-05
1110.9999764845801074.70308397864401e-052.351541989322e-05
1120.999967717555266.45648894806125e-053.22824447403063e-05
1130.999965980146986.8039706039082e-053.4019853019541e-05
1140.9999517258779649.65482440713469e-054.82741220356734e-05
1150.9999429376879090.0001141246241828935.70623120914466e-05
1160.999928064907390.0001438701852195517.19350926097754e-05
1170.9999276550665920.0001446898668157227.23449334078611e-05
1180.9999843366863263.13266273481603e-051.56633136740801e-05
1190.9999907463756571.85072486854373e-059.25362434271864e-06
1200.9999870652740812.58694518389367e-051.29347259194684e-05
1210.9999813377487973.73245024057266e-051.86622512028633e-05
1220.9999741893493765.16213012487394e-052.58106506243697e-05
1230.9999675292466816.49415066383352e-053.24707533191676e-05
1240.9999981179108083.76417838486408e-061.88208919243204e-06
1250.9999981644692753.67106145054718e-061.83553072527359e-06
1260.9999972983012835.40339743371016e-062.70169871685508e-06
1270.9999960895632747.82087345168637e-063.91043672584318e-06
1280.9999963715565887.25688682366359e-063.6284434118318e-06
1290.9999959359197478.12816050548132e-064.06408025274066e-06
1300.9999941973867221.16052265569351e-055.80261327846754e-06
1310.9999915403619761.69192760477778e-058.45963802388891e-06
1320.9999953141694139.37166117409714e-064.68583058704857e-06
1330.9999932705511371.34588977265723e-056.72944886328617e-06
1340.999991093830781.78123384393922e-058.90616921969611e-06
1350.9999910106020961.7978795807187e-058.98939790359349e-06
1360.9999966821694256.63566114983664e-063.31783057491832e-06
1370.9999950859289319.82814213779864e-064.91407106889932e-06
1380.9999950944977269.81100454906873e-064.90550227453437e-06
1390.9999957917834348.4164331326036e-064.2082165663018e-06
1400.9999946044190181.07911619635595e-055.39558098177973e-06
1410.9999922689185751.54621628492044e-057.73108142460218e-06
1420.9999890657502192.18684995626474e-051.09342497813237e-05
1430.9999874257861642.51484276730518e-051.25742138365259e-05
1440.9999851891194622.9621761076352e-051.4810880538176e-05
1450.9999798750648564.0249870287435e-052.01249351437175e-05
1460.9999727804893175.44390213656377e-052.72195106828188e-05
1470.9999663485734666.73028530685924e-053.36514265342962e-05
1480.9999602954913617.94090172774768e-053.97045086387384e-05
1490.9999453433881130.0001093132237732375.46566118866183e-05
1500.9999255525777850.0001488948444303327.44474222151659e-05
1510.9999164815693460.0001670368613089658.35184306544826e-05
1520.9998829452722810.000234109455438760.00011705472771938
1530.9998371737825990.0003256524348027650.000162826217401383
1540.9998808479529290.0002383040941414560.000119152047070728
1550.9998417333705030.0003165332589938530.000158266629496927
1560.9997894892649770.000421021470045320.00021051073502266
1570.999711123969680.0005777520606403910.000288876030320195
1580.9996440140635510.0007119718728989990.0003559859364495
1590.9996270089834070.0007459820331860860.000372991016593043
1600.9996886480759010.0006227038481978870.000311351924098944
1610.9999771169751454.57660497095944e-052.28830248547972e-05
1620.9999817960523863.6407895227332e-051.8203947613666e-05
1630.9999748754417275.02491165468222e-052.51245582734111e-05
1640.9999890515246712.18969506574677e-051.09484753287339e-05
1650.9999840322554023.19354891959398e-051.59677445979699e-05
1660.9999776024775274.47950449451914e-052.23975224725957e-05
1670.9999683932340576.32135318854951e-053.16067659427476e-05
1680.9999611506701447.76986597121409e-053.88493298560705e-05
1690.9999445013830880.000110997233823675.5498616911835e-05
1700.9999987465163512.50696729834051e-061.25348364917026e-06
1710.9999999526993799.46012409972245e-084.73006204986122e-08
1720.9999999334463221.3310735573719e-076.65536778685951e-08
1730.99999997826854.34630006302342e-082.17315003151171e-08
1740.9999999754566324.90867364392678e-082.45433682196339e-08
1750.9999999999995828.3677393876052e-134.1838696938026e-13
1760.9999999999998882.23706230466363e-131.11853115233181e-13
1770.999999999999813.80487891574041e-131.9024394578702e-13
1780.9999999999996536.93434894378382e-133.46717447189191e-13
1790.9999999999999381.23982528468322e-136.19912642341608e-14
1800.9999999999999431.14111334230166e-135.70556671150828e-14
1810.9999999999998832.33070752106638e-131.16535376053319e-13
1820.9999999999999558.93727751753242e-144.46863875876621e-14
1830.9999999999999091.81294912664155e-139.06474563320777e-14
1840.9999999999999121.75091147025343e-138.75455735126716e-14
1850.9999999999999627.5596496521726e-143.7798248260863e-14
1860.9999999999999371.25809069623446e-136.29045348117229e-14
1870.9999999999998742.529539500837e-131.2647697504185e-13
1880.999999999999745.19572722328528e-132.59786361164264e-13
1890.9999999999998023.95938096126997e-131.97969048063498e-13
1900.9999999999996916.17498782410105e-133.08749391205053e-13
1910.9999999999994691.06210464477055e-125.31052322385274e-13
1920.9999999999993991.20149890284172e-126.0074945142086e-13
1930.9999999999988222.35553145089091e-121.17776572544546e-12
1940.999999999997924.16058742627044e-122.08029371313522e-12
1950.9999999999958118.37863233094815e-124.18931616547407e-12
1960.9999999999924581.50832023770206e-117.54160118851032e-12
1970.9999999999852492.95023378306147e-111.47511689153073e-11
1980.9999999999787214.25583500163467e-112.12791750081734e-11
1990.9999999999584088.31843420985898e-114.15921710492949e-11
2000.9999999999419691.16062847281678e-105.80314236408388e-11
2010.9999999998875962.24808515524812e-101.12404257762406e-10
2020.999999999823373.53260265616906e-101.76630132808453e-10
2030.9999999998762562.47487922994794e-101.23743961497397e-10
2040.999999999817143.65720603611663e-101.82860301805831e-10
2050.999999999660266.79480521826621e-103.3974026091331e-10
2060.9999999994743811.05123867439622e-095.2561933719811e-10
2070.9999999990013461.99730846601644e-099.98654233008219e-10
2080.9999999999908281.83433220944766e-119.17166104723831e-12
2090.9999999999965626.87556274474945e-123.43778137237473e-12
2100.9999999999959348.13095508574826e-124.06547754287413e-12
2110.9999999999959058.19054471037674e-124.09527235518837e-12
2120.9999999999965886.82310959556792e-123.41155479778396e-12
2130.9999999999945111.09784836925592e-115.48924184627958e-12
2140.9999999999883222.33551284922519e-111.1677564246126e-11
2150.9999999999791664.16689670847099e-112.0834483542355e-11
2160.9999999999579158.41690814639878e-114.20845407319939e-11
2170.9999999999162021.67595897395896e-108.37979486979481e-11
2180.9999999998408183.18363597595089e-101.59181798797544e-10
2190.9999999996827616.34477816905945e-103.17238908452972e-10
2200.9999999995263449.47312385743795e-104.73656192871897e-10
2210.9999999990991381.80172313492287e-099.00861567461433e-10
2220.999999998166663.66668043327773e-091.83334021663887e-09
2230.9999999964125267.17494791393291e-093.58747395696645e-09
2240.9999999935681761.28636474397476e-086.43182371987381e-09
2250.9999999900011581.99976845839296e-089.99884229196478e-09
2260.9999999986569142.68617188173245e-091.34308594086623e-09
2270.9999999974949445.01011208376771e-092.50505604188385e-09
2280.9999999967995966.4008080031769e-093.20040400158845e-09
2290.9999999937862821.24274356548856e-086.2137178274428e-09
2300.9999999971128465.77430831474119e-092.8871541573706e-09
2310.9999999954324939.13501430517413e-094.56750715258706e-09
2320.9999999906763781.86472439046532e-089.3236219523266e-09
2330.9999999810430513.79138984615643e-081.89569492307821e-08
2340.9999999719494085.61011836359265e-082.80505918179633e-08
2350.9999999714026255.71947502326927e-082.85973751163464e-08
2360.9999999724568915.50862174490822e-082.75431087245411e-08
2370.9999999995796248.40751729327732e-104.20375864663866e-10
2380.9999999993873121.22537527929043e-096.12687639645214e-10
2390.9999999985914932.81701342941498e-091.40850671470749e-09
2400.9999999986086232.78275315992767e-091.39137657996383e-09
2410.999999997410625.17876074664336e-092.58938037332168e-09
2420.9999999988529472.29410678148063e-091.14705339074032e-09
2430.9999999985125742.97485137506992e-091.48742568753496e-09
2440.9999999976280544.74389152949746e-092.37194576474873e-09
2450.999999994420091.11598203953965e-085.57991019769827e-09
2460.9999999868802642.62394712528969e-081.31197356264485e-08
2470.9999999714941695.70116626128556e-082.85058313064278e-08
2480.9999999526480049.47039920051909e-084.73519960025954e-08
2490.9999999362347071.27530586297238e-076.37652931486191e-08
2500.9999998927839672.14432066034808e-071.07216033017404e-07
2510.9999999927947461.44105074203441e-087.20525371017203e-09
2520.999999981644373.67112590549196e-081.83556295274598e-08
2530.9999999609441767.8111648353456e-083.9055824176728e-08
2540.9999999720810395.58379220667962e-082.79189610333981e-08
2550.9999999538767599.22464812174882e-084.61232406087441e-08
2560.9999998829811252.34037750561084e-071.17018875280542e-07
2570.9999999375256851.24948630697525e-076.24743153487623e-08
2580.9999998839038582.32192283932965e-071.16096141966483e-07
2590.9999997006103155.98779370539602e-072.99389685269801e-07
2600.9999993773314851.24533702971648e-066.2266851485824e-07
2610.9999991607065731.67858685444053e-068.39293427220264e-07
2620.9999980253492283.94930154482514e-061.97465077241257e-06
2630.999995095874729.80825055946026e-064.90412527973013e-06
2640.999994806813961.03863720795928e-055.1931860397964e-06
2650.9999917722237051.64555525897943e-058.22777629489716e-06
2660.9999791302796814.17394406378606e-052.08697203189303e-05
2670.9999733449343095.33101313814632e-052.66550656907316e-05
2680.9999505812829179.8837434166807e-054.94187170834035e-05
2690.9999869160370122.61679259769769e-051.30839629884885e-05
2700.9999811520583343.76958833327079e-051.8847941666354e-05
2710.9999944076644521.11846710965202e-055.5923355482601e-06
2720.9999810469388123.79061223766285e-051.89530611883143e-05
2730.9999482673099290.0001034653801415735.17326900707863e-05
2740.9998815978175050.0002368043649902160.000118402182495108
2750.999625034253390.0007499314932209760.000374965746610488
2760.9995306127912430.0009387744175134380.000469387208756719
2770.9985530715862360.002893856827528170.00144692841376409
2780.9983877995439720.003224400912055920.00161220045602796
2790.9946113257893980.0107773484212030.00538867421060152
2800.9932988986252710.01340220274945730.00670110137472866
2810.976970396947410.04605920610518060.0230296030525903
2820.937095758338760.125808483322480.0629042416612398

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.963327295038953 & 0.0733454099220941 & 0.0366727049610471 \tabularnewline
8 & 0.925727871969845 & 0.14854425606031 & 0.0742721280301548 \tabularnewline
9 & 0.876880421828265 & 0.24623915634347 & 0.123119578171735 \tabularnewline
10 & 0.820044094480394 & 0.359911811039212 & 0.179955905519606 \tabularnewline
11 & 0.738302962056722 & 0.523394075886556 & 0.261697037943278 \tabularnewline
12 & 0.811290514440737 & 0.377418971118525 & 0.188709485559263 \tabularnewline
13 & 0.759471717126994 & 0.481056565746011 & 0.240528282873006 \tabularnewline
14 & 0.686883463729684 & 0.626233072540633 & 0.313116536270316 \tabularnewline
15 & 0.620081660685957 & 0.759836678628085 & 0.379918339314043 \tabularnewline
16 & 0.557409309255546 & 0.885181381488908 & 0.442590690744454 \tabularnewline
17 & 0.497521704417891 & 0.995043408835783 & 0.502478295582109 \tabularnewline
18 & 0.460096827198768 & 0.920193654397536 & 0.539903172801232 \tabularnewline
19 & 0.437614069094498 & 0.875228138188997 & 0.562385930905501 \tabularnewline
20 & 0.612053407236145 & 0.775893185527711 & 0.387946592763855 \tabularnewline
21 & 0.676361164915889 & 0.647277670168222 & 0.323638835084111 \tabularnewline
22 & 0.622430947213641 & 0.755138105572719 & 0.377569052786359 \tabularnewline
23 & 0.970073878669705 & 0.0598522426605897 & 0.0299261213302948 \tabularnewline
24 & 0.958134933098583 & 0.0837301338028344 & 0.0418650669014172 \tabularnewline
25 & 0.97106543007374 & 0.0578691398525208 & 0.0289345699262604 \tabularnewline
26 & 0.990411522429579 & 0.0191769551408413 & 0.00958847757042065 \tabularnewline
27 & 0.986180697442461 & 0.0276386051150785 & 0.0138193025575392 \tabularnewline
28 & 0.982773093585634 & 0.0344538128287324 & 0.0172269064143662 \tabularnewline
29 & 0.97616839697043 & 0.04766320605914 & 0.02383160302957 \tabularnewline
30 & 0.967597478345625 & 0.0648050433087502 & 0.0324025216543751 \tabularnewline
31 & 0.95701872700738 & 0.085962545985239 & 0.0429812729926195 \tabularnewline
32 & 0.944122534535298 & 0.111754930929404 & 0.0558774654647019 \tabularnewline
33 & 0.938701442092618 & 0.122597115814764 & 0.0612985579073822 \tabularnewline
34 & 0.922338355643542 & 0.155323288712915 & 0.0776616443564575 \tabularnewline
35 & 0.919341296298972 & 0.161317407402057 & 0.0806587037010284 \tabularnewline
36 & 0.927275643775009 & 0.145448712449982 & 0.0727243562249912 \tabularnewline
37 & 0.908792220350565 & 0.182415559298869 & 0.0912077796494347 \tabularnewline
38 & 0.904641302841036 & 0.190717394317928 & 0.0953586971589642 \tabularnewline
39 & 0.980530542014983 & 0.0389389159700346 & 0.0194694579850173 \tabularnewline
40 & 0.977520857132969 & 0.0449582857340623 & 0.0224791428670311 \tabularnewline
41 & 0.970751423646388 & 0.0584971527072241 & 0.029248576353612 \tabularnewline
42 & 0.962226179034106 & 0.0755476419317884 & 0.0377738209658942 \tabularnewline
43 & 0.953563745578875 & 0.0928725088422508 & 0.0464362544211254 \tabularnewline
44 & 0.952889515341092 & 0.0942209693178165 & 0.0471104846589083 \tabularnewline
45 & 0.949344672503944 & 0.101310654992111 & 0.0506553274960556 \tabularnewline
46 & 0.936997072426379 & 0.126005855147241 & 0.0630029275736205 \tabularnewline
47 & 0.929941560574239 & 0.140116878851522 & 0.0700584394257612 \tabularnewline
48 & 0.914287699562143 & 0.171424600875714 & 0.0857123004378569 \tabularnewline
49 & 0.897164760859758 & 0.205670478280485 & 0.102835239140242 \tabularnewline
50 & 0.879705579469107 & 0.240588841061786 & 0.120294420530893 \tabularnewline
51 & 0.994034065260659 & 0.0119318694786827 & 0.00596593473934134 \tabularnewline
52 & 0.992149289843965 & 0.0157014203120695 & 0.00785071015603473 \tabularnewline
53 & 0.991606822940257 & 0.0167863541194862 & 0.0083931770597431 \tabularnewline
54 & 0.988950294707448 & 0.0220994105851035 & 0.0110497052925517 \tabularnewline
55 & 0.990223577379394 & 0.0195528452412119 & 0.00977642262060597 \tabularnewline
56 & 0.987763805253288 & 0.0244723894934246 & 0.0122361947467123 \tabularnewline
57 & 0.98498060738495 & 0.0300387852301006 & 0.0150193926150503 \tabularnewline
58 & 0.996442668087202 & 0.00711466382559568 & 0.00355733191279784 \tabularnewline
59 & 0.995411478137112 & 0.00917704372577687 & 0.00458852186288843 \tabularnewline
60 & 0.993969157089198 & 0.0120616858216039 & 0.00603084291080194 \tabularnewline
61 & 0.992877557364127 & 0.0142448852717462 & 0.00712244263587309 \tabularnewline
62 & 0.991419022849917 & 0.0171619543001664 & 0.00858097715008321 \tabularnewline
63 & 0.998455853833081 & 0.00308829233383812 & 0.00154414616691906 \tabularnewline
64 & 0.997985851556547 & 0.00402829688690636 & 0.00201414844345318 \tabularnewline
65 & 0.997425915322267 & 0.00514816935546636 & 0.00257408467773318 \tabularnewline
66 & 0.996841208327876 & 0.00631758334424865 & 0.00315879167212433 \tabularnewline
67 & 0.996079641168877 & 0.00784071766224585 & 0.00392035883112292 \tabularnewline
68 & 0.995293569309498 & 0.00941286138100392 & 0.00470643069050196 \tabularnewline
69 & 0.994984982694496 & 0.0100300346110076 & 0.00501501730550381 \tabularnewline
70 & 0.993976740325361 & 0.0120465193492778 & 0.00602325967463891 \tabularnewline
71 & 0.993548327061435 & 0.01290334587713 & 0.00645167293856501 \tabularnewline
72 & 0.993662121041624 & 0.0126757579167516 & 0.00633787895837582 \tabularnewline
73 & 0.991879930358288 & 0.0162401392834232 & 0.0081200696417116 \tabularnewline
74 & 0.992283882939055 & 0.01543223412189 & 0.00771611706094498 \tabularnewline
75 & 0.99008503375434 & 0.019829932491321 & 0.00991496624566048 \tabularnewline
76 & 0.992004370168779 & 0.0159912596624413 & 0.00799562983122066 \tabularnewline
77 & 0.998373417649887 & 0.00325316470022584 & 0.00162658235011292 \tabularnewline
78 & 0.997905261405945 & 0.00418947718810925 & 0.00209473859405462 \tabularnewline
79 & 0.99729580576197 & 0.00540838847605964 & 0.00270419423802982 \tabularnewline
80 & 0.996446047737569 & 0.00710790452486171 & 0.00355395226243086 \tabularnewline
81 & 0.995468600116038 & 0.00906279976792475 & 0.00453139988396238 \tabularnewline
82 & 0.99752656514017 & 0.00494686971965948 & 0.00247343485982974 \tabularnewline
83 & 0.997192483529054 & 0.00561503294189132 & 0.00280751647094566 \tabularnewline
84 & 0.996993723366697 & 0.0060125532666052 & 0.0030062766333026 \tabularnewline
85 & 0.998225801571252 & 0.00354839685749592 & 0.00177419842874796 \tabularnewline
86 & 0.998945129541187 & 0.00210974091762665 & 0.00105487045881333 \tabularnewline
87 & 0.998628335884316 & 0.00274332823136866 & 0.00137166411568433 \tabularnewline
88 & 0.998216268028702 & 0.00356746394259648 & 0.00178373197129824 \tabularnewline
89 & 0.999281727730448 & 0.00143654453910338 & 0.00071827226955169 \tabularnewline
90 & 0.999210248391684 & 0.0015795032166315 & 0.000789751608315751 \tabularnewline
91 & 0.999092634357245 & 0.00181473128551026 & 0.000907365642755128 \tabularnewline
92 & 0.998959375151199 & 0.00208124969760285 & 0.00104062484880143 \tabularnewline
93 & 0.998809535834094 & 0.00238092833181246 & 0.00119046416590623 \tabularnewline
94 & 0.99891930850432 & 0.00216138299136008 & 0.00108069149568004 \tabularnewline
95 & 0.998556783617597 & 0.00288643276480655 & 0.00144321638240328 \tabularnewline
96 & 0.999821147775078 & 0.000357704449843733 & 0.000178852224921867 \tabularnewline
97 & 0.999804653732016 & 0.000390692535967566 & 0.000195346267983783 \tabularnewline
98 & 0.99999175554776 & 1.64889044800592e-05 & 8.24445224002961e-06 \tabularnewline
99 & 0.99999107366603 & 1.78526679391225e-05 & 8.92633396956126e-06 \tabularnewline
100 & 0.999995557894852 & 8.88421029538365e-06 & 4.44210514769182e-06 \tabularnewline
101 & 0.999994078548087 & 1.18429038252323e-05 & 5.92145191261613e-06 \tabularnewline
102 & 0.999991738393914 & 1.65232121712319e-05 & 8.26160608561596e-06 \tabularnewline
103 & 0.999995378515932 & 9.24296813605275e-06 & 4.62148406802637e-06 \tabularnewline
104 & 0.999994122620065 & 1.17547598702416e-05 & 5.87737993512082e-06 \tabularnewline
105 & 0.999992645981598 & 1.47080368039995e-05 & 7.35401840199975e-06 \tabularnewline
106 & 0.999993355258237 & 1.32894835268643e-05 & 6.64474176343215e-06 \tabularnewline
107 & 0.999990381191769 & 1.92376164624486e-05 & 9.61880823122432e-06 \tabularnewline
108 & 0.999987101634876 & 2.5796730248409e-05 & 1.28983651242045e-05 \tabularnewline
109 & 0.999987222339536 & 2.55553209284098e-05 & 1.27776604642049e-05 \tabularnewline
110 & 0.999981737756634 & 3.65244867329521e-05 & 1.82622433664761e-05 \tabularnewline
111 & 0.999976484580107 & 4.70308397864401e-05 & 2.351541989322e-05 \tabularnewline
112 & 0.99996771755526 & 6.45648894806125e-05 & 3.22824447403063e-05 \tabularnewline
113 & 0.99996598014698 & 6.8039706039082e-05 & 3.4019853019541e-05 \tabularnewline
114 & 0.999951725877964 & 9.65482440713469e-05 & 4.82741220356734e-05 \tabularnewline
115 & 0.999942937687909 & 0.000114124624182893 & 5.70623120914466e-05 \tabularnewline
116 & 0.99992806490739 & 0.000143870185219551 & 7.19350926097754e-05 \tabularnewline
117 & 0.999927655066592 & 0.000144689866815722 & 7.23449334078611e-05 \tabularnewline
118 & 0.999984336686326 & 3.13266273481603e-05 & 1.56633136740801e-05 \tabularnewline
119 & 0.999990746375657 & 1.85072486854373e-05 & 9.25362434271864e-06 \tabularnewline
120 & 0.999987065274081 & 2.58694518389367e-05 & 1.29347259194684e-05 \tabularnewline
121 & 0.999981337748797 & 3.73245024057266e-05 & 1.86622512028633e-05 \tabularnewline
122 & 0.999974189349376 & 5.16213012487394e-05 & 2.58106506243697e-05 \tabularnewline
123 & 0.999967529246681 & 6.49415066383352e-05 & 3.24707533191676e-05 \tabularnewline
124 & 0.999998117910808 & 3.76417838486408e-06 & 1.88208919243204e-06 \tabularnewline
125 & 0.999998164469275 & 3.67106145054718e-06 & 1.83553072527359e-06 \tabularnewline
126 & 0.999997298301283 & 5.40339743371016e-06 & 2.70169871685508e-06 \tabularnewline
127 & 0.999996089563274 & 7.82087345168637e-06 & 3.91043672584318e-06 \tabularnewline
128 & 0.999996371556588 & 7.25688682366359e-06 & 3.6284434118318e-06 \tabularnewline
129 & 0.999995935919747 & 8.12816050548132e-06 & 4.06408025274066e-06 \tabularnewline
130 & 0.999994197386722 & 1.16052265569351e-05 & 5.80261327846754e-06 \tabularnewline
131 & 0.999991540361976 & 1.69192760477778e-05 & 8.45963802388891e-06 \tabularnewline
132 & 0.999995314169413 & 9.37166117409714e-06 & 4.68583058704857e-06 \tabularnewline
133 & 0.999993270551137 & 1.34588977265723e-05 & 6.72944886328617e-06 \tabularnewline
134 & 0.99999109383078 & 1.78123384393922e-05 & 8.90616921969611e-06 \tabularnewline
135 & 0.999991010602096 & 1.7978795807187e-05 & 8.98939790359349e-06 \tabularnewline
136 & 0.999996682169425 & 6.63566114983664e-06 & 3.31783057491832e-06 \tabularnewline
137 & 0.999995085928931 & 9.82814213779864e-06 & 4.91407106889932e-06 \tabularnewline
138 & 0.999995094497726 & 9.81100454906873e-06 & 4.90550227453437e-06 \tabularnewline
139 & 0.999995791783434 & 8.4164331326036e-06 & 4.2082165663018e-06 \tabularnewline
140 & 0.999994604419018 & 1.07911619635595e-05 & 5.39558098177973e-06 \tabularnewline
141 & 0.999992268918575 & 1.54621628492044e-05 & 7.73108142460218e-06 \tabularnewline
142 & 0.999989065750219 & 2.18684995626474e-05 & 1.09342497813237e-05 \tabularnewline
143 & 0.999987425786164 & 2.51484276730518e-05 & 1.25742138365259e-05 \tabularnewline
144 & 0.999985189119462 & 2.9621761076352e-05 & 1.4810880538176e-05 \tabularnewline
145 & 0.999979875064856 & 4.0249870287435e-05 & 2.01249351437175e-05 \tabularnewline
146 & 0.999972780489317 & 5.44390213656377e-05 & 2.72195106828188e-05 \tabularnewline
147 & 0.999966348573466 & 6.73028530685924e-05 & 3.36514265342962e-05 \tabularnewline
148 & 0.999960295491361 & 7.94090172774768e-05 & 3.97045086387384e-05 \tabularnewline
149 & 0.999945343388113 & 0.000109313223773237 & 5.46566118866183e-05 \tabularnewline
150 & 0.999925552577785 & 0.000148894844430332 & 7.44474222151659e-05 \tabularnewline
151 & 0.999916481569346 & 0.000167036861308965 & 8.35184306544826e-05 \tabularnewline
152 & 0.999882945272281 & 0.00023410945543876 & 0.00011705472771938 \tabularnewline
153 & 0.999837173782599 & 0.000325652434802765 & 0.000162826217401383 \tabularnewline
154 & 0.999880847952929 & 0.000238304094141456 & 0.000119152047070728 \tabularnewline
155 & 0.999841733370503 & 0.000316533258993853 & 0.000158266629496927 \tabularnewline
156 & 0.999789489264977 & 0.00042102147004532 & 0.00021051073502266 \tabularnewline
157 & 0.99971112396968 & 0.000577752060640391 & 0.000288876030320195 \tabularnewline
158 & 0.999644014063551 & 0.000711971872898999 & 0.0003559859364495 \tabularnewline
159 & 0.999627008983407 & 0.000745982033186086 & 0.000372991016593043 \tabularnewline
160 & 0.999688648075901 & 0.000622703848197887 & 0.000311351924098944 \tabularnewline
161 & 0.999977116975145 & 4.57660497095944e-05 & 2.28830248547972e-05 \tabularnewline
162 & 0.999981796052386 & 3.6407895227332e-05 & 1.8203947613666e-05 \tabularnewline
163 & 0.999974875441727 & 5.02491165468222e-05 & 2.51245582734111e-05 \tabularnewline
164 & 0.999989051524671 & 2.18969506574677e-05 & 1.09484753287339e-05 \tabularnewline
165 & 0.999984032255402 & 3.19354891959398e-05 & 1.59677445979699e-05 \tabularnewline
166 & 0.999977602477527 & 4.47950449451914e-05 & 2.23975224725957e-05 \tabularnewline
167 & 0.999968393234057 & 6.32135318854951e-05 & 3.16067659427476e-05 \tabularnewline
168 & 0.999961150670144 & 7.76986597121409e-05 & 3.88493298560705e-05 \tabularnewline
169 & 0.999944501383088 & 0.00011099723382367 & 5.5498616911835e-05 \tabularnewline
170 & 0.999998746516351 & 2.50696729834051e-06 & 1.25348364917026e-06 \tabularnewline
171 & 0.999999952699379 & 9.46012409972245e-08 & 4.73006204986122e-08 \tabularnewline
172 & 0.999999933446322 & 1.3310735573719e-07 & 6.65536778685951e-08 \tabularnewline
173 & 0.9999999782685 & 4.34630006302342e-08 & 2.17315003151171e-08 \tabularnewline
174 & 0.999999975456632 & 4.90867364392678e-08 & 2.45433682196339e-08 \tabularnewline
175 & 0.999999999999582 & 8.3677393876052e-13 & 4.1838696938026e-13 \tabularnewline
176 & 0.999999999999888 & 2.23706230466363e-13 & 1.11853115233181e-13 \tabularnewline
177 & 0.99999999999981 & 3.80487891574041e-13 & 1.9024394578702e-13 \tabularnewline
178 & 0.999999999999653 & 6.93434894378382e-13 & 3.46717447189191e-13 \tabularnewline
179 & 0.999999999999938 & 1.23982528468322e-13 & 6.19912642341608e-14 \tabularnewline
180 & 0.999999999999943 & 1.14111334230166e-13 & 5.70556671150828e-14 \tabularnewline
181 & 0.999999999999883 & 2.33070752106638e-13 & 1.16535376053319e-13 \tabularnewline
182 & 0.999999999999955 & 8.93727751753242e-14 & 4.46863875876621e-14 \tabularnewline
183 & 0.999999999999909 & 1.81294912664155e-13 & 9.06474563320777e-14 \tabularnewline
184 & 0.999999999999912 & 1.75091147025343e-13 & 8.75455735126716e-14 \tabularnewline
185 & 0.999999999999962 & 7.5596496521726e-14 & 3.7798248260863e-14 \tabularnewline
186 & 0.999999999999937 & 1.25809069623446e-13 & 6.29045348117229e-14 \tabularnewline
187 & 0.999999999999874 & 2.529539500837e-13 & 1.2647697504185e-13 \tabularnewline
188 & 0.99999999999974 & 5.19572722328528e-13 & 2.59786361164264e-13 \tabularnewline
189 & 0.999999999999802 & 3.95938096126997e-13 & 1.97969048063498e-13 \tabularnewline
190 & 0.999999999999691 & 6.17498782410105e-13 & 3.08749391205053e-13 \tabularnewline
191 & 0.999999999999469 & 1.06210464477055e-12 & 5.31052322385274e-13 \tabularnewline
192 & 0.999999999999399 & 1.20149890284172e-12 & 6.0074945142086e-13 \tabularnewline
193 & 0.999999999998822 & 2.35553145089091e-12 & 1.17776572544546e-12 \tabularnewline
194 & 0.99999999999792 & 4.16058742627044e-12 & 2.08029371313522e-12 \tabularnewline
195 & 0.999999999995811 & 8.37863233094815e-12 & 4.18931616547407e-12 \tabularnewline
196 & 0.999999999992458 & 1.50832023770206e-11 & 7.54160118851032e-12 \tabularnewline
197 & 0.999999999985249 & 2.95023378306147e-11 & 1.47511689153073e-11 \tabularnewline
198 & 0.999999999978721 & 4.25583500163467e-11 & 2.12791750081734e-11 \tabularnewline
199 & 0.999999999958408 & 8.31843420985898e-11 & 4.15921710492949e-11 \tabularnewline
200 & 0.999999999941969 & 1.16062847281678e-10 & 5.80314236408388e-11 \tabularnewline
201 & 0.999999999887596 & 2.24808515524812e-10 & 1.12404257762406e-10 \tabularnewline
202 & 0.99999999982337 & 3.53260265616906e-10 & 1.76630132808453e-10 \tabularnewline
203 & 0.999999999876256 & 2.47487922994794e-10 & 1.23743961497397e-10 \tabularnewline
204 & 0.99999999981714 & 3.65720603611663e-10 & 1.82860301805831e-10 \tabularnewline
205 & 0.99999999966026 & 6.79480521826621e-10 & 3.3974026091331e-10 \tabularnewline
206 & 0.999999999474381 & 1.05123867439622e-09 & 5.2561933719811e-10 \tabularnewline
207 & 0.999999999001346 & 1.99730846601644e-09 & 9.98654233008219e-10 \tabularnewline
208 & 0.999999999990828 & 1.83433220944766e-11 & 9.17166104723831e-12 \tabularnewline
209 & 0.999999999996562 & 6.87556274474945e-12 & 3.43778137237473e-12 \tabularnewline
210 & 0.999999999995934 & 8.13095508574826e-12 & 4.06547754287413e-12 \tabularnewline
211 & 0.999999999995905 & 8.19054471037674e-12 & 4.09527235518837e-12 \tabularnewline
212 & 0.999999999996588 & 6.82310959556792e-12 & 3.41155479778396e-12 \tabularnewline
213 & 0.999999999994511 & 1.09784836925592e-11 & 5.48924184627958e-12 \tabularnewline
214 & 0.999999999988322 & 2.33551284922519e-11 & 1.1677564246126e-11 \tabularnewline
215 & 0.999999999979166 & 4.16689670847099e-11 & 2.0834483542355e-11 \tabularnewline
216 & 0.999999999957915 & 8.41690814639878e-11 & 4.20845407319939e-11 \tabularnewline
217 & 0.999999999916202 & 1.67595897395896e-10 & 8.37979486979481e-11 \tabularnewline
218 & 0.999999999840818 & 3.18363597595089e-10 & 1.59181798797544e-10 \tabularnewline
219 & 0.999999999682761 & 6.34477816905945e-10 & 3.17238908452972e-10 \tabularnewline
220 & 0.999999999526344 & 9.47312385743795e-10 & 4.73656192871897e-10 \tabularnewline
221 & 0.999999999099138 & 1.80172313492287e-09 & 9.00861567461433e-10 \tabularnewline
222 & 0.99999999816666 & 3.66668043327773e-09 & 1.83334021663887e-09 \tabularnewline
223 & 0.999999996412526 & 7.17494791393291e-09 & 3.58747395696645e-09 \tabularnewline
224 & 0.999999993568176 & 1.28636474397476e-08 & 6.43182371987381e-09 \tabularnewline
225 & 0.999999990001158 & 1.99976845839296e-08 & 9.99884229196478e-09 \tabularnewline
226 & 0.999999998656914 & 2.68617188173245e-09 & 1.34308594086623e-09 \tabularnewline
227 & 0.999999997494944 & 5.01011208376771e-09 & 2.50505604188385e-09 \tabularnewline
228 & 0.999999996799596 & 6.4008080031769e-09 & 3.20040400158845e-09 \tabularnewline
229 & 0.999999993786282 & 1.24274356548856e-08 & 6.2137178274428e-09 \tabularnewline
230 & 0.999999997112846 & 5.77430831474119e-09 & 2.8871541573706e-09 \tabularnewline
231 & 0.999999995432493 & 9.13501430517413e-09 & 4.56750715258706e-09 \tabularnewline
232 & 0.999999990676378 & 1.86472439046532e-08 & 9.3236219523266e-09 \tabularnewline
233 & 0.999999981043051 & 3.79138984615643e-08 & 1.89569492307821e-08 \tabularnewline
234 & 0.999999971949408 & 5.61011836359265e-08 & 2.80505918179633e-08 \tabularnewline
235 & 0.999999971402625 & 5.71947502326927e-08 & 2.85973751163464e-08 \tabularnewline
236 & 0.999999972456891 & 5.50862174490822e-08 & 2.75431087245411e-08 \tabularnewline
237 & 0.999999999579624 & 8.40751729327732e-10 & 4.20375864663866e-10 \tabularnewline
238 & 0.999999999387312 & 1.22537527929043e-09 & 6.12687639645214e-10 \tabularnewline
239 & 0.999999998591493 & 2.81701342941498e-09 & 1.40850671470749e-09 \tabularnewline
240 & 0.999999998608623 & 2.78275315992767e-09 & 1.39137657996383e-09 \tabularnewline
241 & 0.99999999741062 & 5.17876074664336e-09 & 2.58938037332168e-09 \tabularnewline
242 & 0.999999998852947 & 2.29410678148063e-09 & 1.14705339074032e-09 \tabularnewline
243 & 0.999999998512574 & 2.97485137506992e-09 & 1.48742568753496e-09 \tabularnewline
244 & 0.999999997628054 & 4.74389152949746e-09 & 2.37194576474873e-09 \tabularnewline
245 & 0.99999999442009 & 1.11598203953965e-08 & 5.57991019769827e-09 \tabularnewline
246 & 0.999999986880264 & 2.62394712528969e-08 & 1.31197356264485e-08 \tabularnewline
247 & 0.999999971494169 & 5.70116626128556e-08 & 2.85058313064278e-08 \tabularnewline
248 & 0.999999952648004 & 9.47039920051909e-08 & 4.73519960025954e-08 \tabularnewline
249 & 0.999999936234707 & 1.27530586297238e-07 & 6.37652931486191e-08 \tabularnewline
250 & 0.999999892783967 & 2.14432066034808e-07 & 1.07216033017404e-07 \tabularnewline
251 & 0.999999992794746 & 1.44105074203441e-08 & 7.20525371017203e-09 \tabularnewline
252 & 0.99999998164437 & 3.67112590549196e-08 & 1.83556295274598e-08 \tabularnewline
253 & 0.999999960944176 & 7.8111648353456e-08 & 3.9055824176728e-08 \tabularnewline
254 & 0.999999972081039 & 5.58379220667962e-08 & 2.79189610333981e-08 \tabularnewline
255 & 0.999999953876759 & 9.22464812174882e-08 & 4.61232406087441e-08 \tabularnewline
256 & 0.999999882981125 & 2.34037750561084e-07 & 1.17018875280542e-07 \tabularnewline
257 & 0.999999937525685 & 1.24948630697525e-07 & 6.24743153487623e-08 \tabularnewline
258 & 0.999999883903858 & 2.32192283932965e-07 & 1.16096141966483e-07 \tabularnewline
259 & 0.999999700610315 & 5.98779370539602e-07 & 2.99389685269801e-07 \tabularnewline
260 & 0.999999377331485 & 1.24533702971648e-06 & 6.2266851485824e-07 \tabularnewline
261 & 0.999999160706573 & 1.67858685444053e-06 & 8.39293427220264e-07 \tabularnewline
262 & 0.999998025349228 & 3.94930154482514e-06 & 1.97465077241257e-06 \tabularnewline
263 & 0.99999509587472 & 9.80825055946026e-06 & 4.90412527973013e-06 \tabularnewline
264 & 0.99999480681396 & 1.03863720795928e-05 & 5.1931860397964e-06 \tabularnewline
265 & 0.999991772223705 & 1.64555525897943e-05 & 8.22777629489716e-06 \tabularnewline
266 & 0.999979130279681 & 4.17394406378606e-05 & 2.08697203189303e-05 \tabularnewline
267 & 0.999973344934309 & 5.33101313814632e-05 & 2.66550656907316e-05 \tabularnewline
268 & 0.999950581282917 & 9.8837434166807e-05 & 4.94187170834035e-05 \tabularnewline
269 & 0.999986916037012 & 2.61679259769769e-05 & 1.30839629884885e-05 \tabularnewline
270 & 0.999981152058334 & 3.76958833327079e-05 & 1.8847941666354e-05 \tabularnewline
271 & 0.999994407664452 & 1.11846710965202e-05 & 5.5923355482601e-06 \tabularnewline
272 & 0.999981046938812 & 3.79061223766285e-05 & 1.89530611883143e-05 \tabularnewline
273 & 0.999948267309929 & 0.000103465380141573 & 5.17326900707863e-05 \tabularnewline
274 & 0.999881597817505 & 0.000236804364990216 & 0.000118402182495108 \tabularnewline
275 & 0.99962503425339 & 0.000749931493220976 & 0.000374965746610488 \tabularnewline
276 & 0.999530612791243 & 0.000938774417513438 & 0.000469387208756719 \tabularnewline
277 & 0.998553071586236 & 0.00289385682752817 & 0.00144692841376409 \tabularnewline
278 & 0.998387799543972 & 0.00322440091205592 & 0.00161220045602796 \tabularnewline
279 & 0.994611325789398 & 0.010777348421203 & 0.00538867421060152 \tabularnewline
280 & 0.993298898625271 & 0.0134022027494573 & 0.00670110137472866 \tabularnewline
281 & 0.97697039694741 & 0.0460592061051806 & 0.0230296030525903 \tabularnewline
282 & 0.93709575833876 & 0.12580848332248 & 0.0629042416612398 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186260&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]7[/C][C]0.963327295038953[/C][C]0.0733454099220941[/C][C]0.0366727049610471[/C][/ROW]
[ROW][C]8[/C][C]0.925727871969845[/C][C]0.14854425606031[/C][C]0.0742721280301548[/C][/ROW]
[ROW][C]9[/C][C]0.876880421828265[/C][C]0.24623915634347[/C][C]0.123119578171735[/C][/ROW]
[ROW][C]10[/C][C]0.820044094480394[/C][C]0.359911811039212[/C][C]0.179955905519606[/C][/ROW]
[ROW][C]11[/C][C]0.738302962056722[/C][C]0.523394075886556[/C][C]0.261697037943278[/C][/ROW]
[ROW][C]12[/C][C]0.811290514440737[/C][C]0.377418971118525[/C][C]0.188709485559263[/C][/ROW]
[ROW][C]13[/C][C]0.759471717126994[/C][C]0.481056565746011[/C][C]0.240528282873006[/C][/ROW]
[ROW][C]14[/C][C]0.686883463729684[/C][C]0.626233072540633[/C][C]0.313116536270316[/C][/ROW]
[ROW][C]15[/C][C]0.620081660685957[/C][C]0.759836678628085[/C][C]0.379918339314043[/C][/ROW]
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[ROW][C]98[/C][C]0.99999175554776[/C][C]1.64889044800592e-05[/C][C]8.24445224002961e-06[/C][/ROW]
[ROW][C]99[/C][C]0.99999107366603[/C][C]1.78526679391225e-05[/C][C]8.92633396956126e-06[/C][/ROW]
[ROW][C]100[/C][C]0.999995557894852[/C][C]8.88421029538365e-06[/C][C]4.44210514769182e-06[/C][/ROW]
[ROW][C]101[/C][C]0.999994078548087[/C][C]1.18429038252323e-05[/C][C]5.92145191261613e-06[/C][/ROW]
[ROW][C]102[/C][C]0.999991738393914[/C][C]1.65232121712319e-05[/C][C]8.26160608561596e-06[/C][/ROW]
[ROW][C]103[/C][C]0.999995378515932[/C][C]9.24296813605275e-06[/C][C]4.62148406802637e-06[/C][/ROW]
[ROW][C]104[/C][C]0.999994122620065[/C][C]1.17547598702416e-05[/C][C]5.87737993512082e-06[/C][/ROW]
[ROW][C]105[/C][C]0.999992645981598[/C][C]1.47080368039995e-05[/C][C]7.35401840199975e-06[/C][/ROW]
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[ROW][C]107[/C][C]0.999990381191769[/C][C]1.92376164624486e-05[/C][C]9.61880823122432e-06[/C][/ROW]
[ROW][C]108[/C][C]0.999987101634876[/C][C]2.5796730248409e-05[/C][C]1.28983651242045e-05[/C][/ROW]
[ROW][C]109[/C][C]0.999987222339536[/C][C]2.55553209284098e-05[/C][C]1.27776604642049e-05[/C][/ROW]
[ROW][C]110[/C][C]0.999981737756634[/C][C]3.65244867329521e-05[/C][C]1.82622433664761e-05[/C][/ROW]
[ROW][C]111[/C][C]0.999976484580107[/C][C]4.70308397864401e-05[/C][C]2.351541989322e-05[/C][/ROW]
[ROW][C]112[/C][C]0.99996771755526[/C][C]6.45648894806125e-05[/C][C]3.22824447403063e-05[/C][/ROW]
[ROW][C]113[/C][C]0.99996598014698[/C][C]6.8039706039082e-05[/C][C]3.4019853019541e-05[/C][/ROW]
[ROW][C]114[/C][C]0.999951725877964[/C][C]9.65482440713469e-05[/C][C]4.82741220356734e-05[/C][/ROW]
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[ROW][C]116[/C][C]0.99992806490739[/C][C]0.000143870185219551[/C][C]7.19350926097754e-05[/C][/ROW]
[ROW][C]117[/C][C]0.999927655066592[/C][C]0.000144689866815722[/C][C]7.23449334078611e-05[/C][/ROW]
[ROW][C]118[/C][C]0.999984336686326[/C][C]3.13266273481603e-05[/C][C]1.56633136740801e-05[/C][/ROW]
[ROW][C]119[/C][C]0.999990746375657[/C][C]1.85072486854373e-05[/C][C]9.25362434271864e-06[/C][/ROW]
[ROW][C]120[/C][C]0.999987065274081[/C][C]2.58694518389367e-05[/C][C]1.29347259194684e-05[/C][/ROW]
[ROW][C]121[/C][C]0.999981337748797[/C][C]3.73245024057266e-05[/C][C]1.86622512028633e-05[/C][/ROW]
[ROW][C]122[/C][C]0.999974189349376[/C][C]5.16213012487394e-05[/C][C]2.58106506243697e-05[/C][/ROW]
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[ROW][C]124[/C][C]0.999998117910808[/C][C]3.76417838486408e-06[/C][C]1.88208919243204e-06[/C][/ROW]
[ROW][C]125[/C][C]0.999998164469275[/C][C]3.67106145054718e-06[/C][C]1.83553072527359e-06[/C][/ROW]
[ROW][C]126[/C][C]0.999997298301283[/C][C]5.40339743371016e-06[/C][C]2.70169871685508e-06[/C][/ROW]
[ROW][C]127[/C][C]0.999996089563274[/C][C]7.82087345168637e-06[/C][C]3.91043672584318e-06[/C][/ROW]
[ROW][C]128[/C][C]0.999996371556588[/C][C]7.25688682366359e-06[/C][C]3.6284434118318e-06[/C][/ROW]
[ROW][C]129[/C][C]0.999995935919747[/C][C]8.12816050548132e-06[/C][C]4.06408025274066e-06[/C][/ROW]
[ROW][C]130[/C][C]0.999994197386722[/C][C]1.16052265569351e-05[/C][C]5.80261327846754e-06[/C][/ROW]
[ROW][C]131[/C][C]0.999991540361976[/C][C]1.69192760477778e-05[/C][C]8.45963802388891e-06[/C][/ROW]
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[ROW][C]137[/C][C]0.999995085928931[/C][C]9.82814213779864e-06[/C][C]4.91407106889932e-06[/C][/ROW]
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[ROW][C]148[/C][C]0.999960295491361[/C][C]7.94090172774768e-05[/C][C]3.97045086387384e-05[/C][/ROW]
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[ROW][C]157[/C][C]0.99971112396968[/C][C]0.000577752060640391[/C][C]0.000288876030320195[/C][/ROW]
[ROW][C]158[/C][C]0.999644014063551[/C][C]0.000711971872898999[/C][C]0.0003559859364495[/C][/ROW]
[ROW][C]159[/C][C]0.999627008983407[/C][C]0.000745982033186086[/C][C]0.000372991016593043[/C][/ROW]
[ROW][C]160[/C][C]0.999688648075901[/C][C]0.000622703848197887[/C][C]0.000311351924098944[/C][/ROW]
[ROW][C]161[/C][C]0.999977116975145[/C][C]4.57660497095944e-05[/C][C]2.28830248547972e-05[/C][/ROW]
[ROW][C]162[/C][C]0.999981796052386[/C][C]3.6407895227332e-05[/C][C]1.8203947613666e-05[/C][/ROW]
[ROW][C]163[/C][C]0.999974875441727[/C][C]5.02491165468222e-05[/C][C]2.51245582734111e-05[/C][/ROW]
[ROW][C]164[/C][C]0.999989051524671[/C][C]2.18969506574677e-05[/C][C]1.09484753287339e-05[/C][/ROW]
[ROW][C]165[/C][C]0.999984032255402[/C][C]3.19354891959398e-05[/C][C]1.59677445979699e-05[/C][/ROW]
[ROW][C]166[/C][C]0.999977602477527[/C][C]4.47950449451914e-05[/C][C]2.23975224725957e-05[/C][/ROW]
[ROW][C]167[/C][C]0.999968393234057[/C][C]6.32135318854951e-05[/C][C]3.16067659427476e-05[/C][/ROW]
[ROW][C]168[/C][C]0.999961150670144[/C][C]7.76986597121409e-05[/C][C]3.88493298560705e-05[/C][/ROW]
[ROW][C]169[/C][C]0.999944501383088[/C][C]0.00011099723382367[/C][C]5.5498616911835e-05[/C][/ROW]
[ROW][C]170[/C][C]0.999998746516351[/C][C]2.50696729834051e-06[/C][C]1.25348364917026e-06[/C][/ROW]
[ROW][C]171[/C][C]0.999999952699379[/C][C]9.46012409972245e-08[/C][C]4.73006204986122e-08[/C][/ROW]
[ROW][C]172[/C][C]0.999999933446322[/C][C]1.3310735573719e-07[/C][C]6.65536778685951e-08[/C][/ROW]
[ROW][C]173[/C][C]0.9999999782685[/C][C]4.34630006302342e-08[/C][C]2.17315003151171e-08[/C][/ROW]
[ROW][C]174[/C][C]0.999999975456632[/C][C]4.90867364392678e-08[/C][C]2.45433682196339e-08[/C][/ROW]
[ROW][C]175[/C][C]0.999999999999582[/C][C]8.3677393876052e-13[/C][C]4.1838696938026e-13[/C][/ROW]
[ROW][C]176[/C][C]0.999999999999888[/C][C]2.23706230466363e-13[/C][C]1.11853115233181e-13[/C][/ROW]
[ROW][C]177[/C][C]0.99999999999981[/C][C]3.80487891574041e-13[/C][C]1.9024394578702e-13[/C][/ROW]
[ROW][C]178[/C][C]0.999999999999653[/C][C]6.93434894378382e-13[/C][C]3.46717447189191e-13[/C][/ROW]
[ROW][C]179[/C][C]0.999999999999938[/C][C]1.23982528468322e-13[/C][C]6.19912642341608e-14[/C][/ROW]
[ROW][C]180[/C][C]0.999999999999943[/C][C]1.14111334230166e-13[/C][C]5.70556671150828e-14[/C][/ROW]
[ROW][C]181[/C][C]0.999999999999883[/C][C]2.33070752106638e-13[/C][C]1.16535376053319e-13[/C][/ROW]
[ROW][C]182[/C][C]0.999999999999955[/C][C]8.93727751753242e-14[/C][C]4.46863875876621e-14[/C][/ROW]
[ROW][C]183[/C][C]0.999999999999909[/C][C]1.81294912664155e-13[/C][C]9.06474563320777e-14[/C][/ROW]
[ROW][C]184[/C][C]0.999999999999912[/C][C]1.75091147025343e-13[/C][C]8.75455735126716e-14[/C][/ROW]
[ROW][C]185[/C][C]0.999999999999962[/C][C]7.5596496521726e-14[/C][C]3.7798248260863e-14[/C][/ROW]
[ROW][C]186[/C][C]0.999999999999937[/C][C]1.25809069623446e-13[/C][C]6.29045348117229e-14[/C][/ROW]
[ROW][C]187[/C][C]0.999999999999874[/C][C]2.529539500837e-13[/C][C]1.2647697504185e-13[/C][/ROW]
[ROW][C]188[/C][C]0.99999999999974[/C][C]5.19572722328528e-13[/C][C]2.59786361164264e-13[/C][/ROW]
[ROW][C]189[/C][C]0.999999999999802[/C][C]3.95938096126997e-13[/C][C]1.97969048063498e-13[/C][/ROW]
[ROW][C]190[/C][C]0.999999999999691[/C][C]6.17498782410105e-13[/C][C]3.08749391205053e-13[/C][/ROW]
[ROW][C]191[/C][C]0.999999999999469[/C][C]1.06210464477055e-12[/C][C]5.31052322385274e-13[/C][/ROW]
[ROW][C]192[/C][C]0.999999999999399[/C][C]1.20149890284172e-12[/C][C]6.0074945142086e-13[/C][/ROW]
[ROW][C]193[/C][C]0.999999999998822[/C][C]2.35553145089091e-12[/C][C]1.17776572544546e-12[/C][/ROW]
[ROW][C]194[/C][C]0.99999999999792[/C][C]4.16058742627044e-12[/C][C]2.08029371313522e-12[/C][/ROW]
[ROW][C]195[/C][C]0.999999999995811[/C][C]8.37863233094815e-12[/C][C]4.18931616547407e-12[/C][/ROW]
[ROW][C]196[/C][C]0.999999999992458[/C][C]1.50832023770206e-11[/C][C]7.54160118851032e-12[/C][/ROW]
[ROW][C]197[/C][C]0.999999999985249[/C][C]2.95023378306147e-11[/C][C]1.47511689153073e-11[/C][/ROW]
[ROW][C]198[/C][C]0.999999999978721[/C][C]4.25583500163467e-11[/C][C]2.12791750081734e-11[/C][/ROW]
[ROW][C]199[/C][C]0.999999999958408[/C][C]8.31843420985898e-11[/C][C]4.15921710492949e-11[/C][/ROW]
[ROW][C]200[/C][C]0.999999999941969[/C][C]1.16062847281678e-10[/C][C]5.80314236408388e-11[/C][/ROW]
[ROW][C]201[/C][C]0.999999999887596[/C][C]2.24808515524812e-10[/C][C]1.12404257762406e-10[/C][/ROW]
[ROW][C]202[/C][C]0.99999999982337[/C][C]3.53260265616906e-10[/C][C]1.76630132808453e-10[/C][/ROW]
[ROW][C]203[/C][C]0.999999999876256[/C][C]2.47487922994794e-10[/C][C]1.23743961497397e-10[/C][/ROW]
[ROW][C]204[/C][C]0.99999999981714[/C][C]3.65720603611663e-10[/C][C]1.82860301805831e-10[/C][/ROW]
[ROW][C]205[/C][C]0.99999999966026[/C][C]6.79480521826621e-10[/C][C]3.3974026091331e-10[/C][/ROW]
[ROW][C]206[/C][C]0.999999999474381[/C][C]1.05123867439622e-09[/C][C]5.2561933719811e-10[/C][/ROW]
[ROW][C]207[/C][C]0.999999999001346[/C][C]1.99730846601644e-09[/C][C]9.98654233008219e-10[/C][/ROW]
[ROW][C]208[/C][C]0.999999999990828[/C][C]1.83433220944766e-11[/C][C]9.17166104723831e-12[/C][/ROW]
[ROW][C]209[/C][C]0.999999999996562[/C][C]6.87556274474945e-12[/C][C]3.43778137237473e-12[/C][/ROW]
[ROW][C]210[/C][C]0.999999999995934[/C][C]8.13095508574826e-12[/C][C]4.06547754287413e-12[/C][/ROW]
[ROW][C]211[/C][C]0.999999999995905[/C][C]8.19054471037674e-12[/C][C]4.09527235518837e-12[/C][/ROW]
[ROW][C]212[/C][C]0.999999999996588[/C][C]6.82310959556792e-12[/C][C]3.41155479778396e-12[/C][/ROW]
[ROW][C]213[/C][C]0.999999999994511[/C][C]1.09784836925592e-11[/C][C]5.48924184627958e-12[/C][/ROW]
[ROW][C]214[/C][C]0.999999999988322[/C][C]2.33551284922519e-11[/C][C]1.1677564246126e-11[/C][/ROW]
[ROW][C]215[/C][C]0.999999999979166[/C][C]4.16689670847099e-11[/C][C]2.0834483542355e-11[/C][/ROW]
[ROW][C]216[/C][C]0.999999999957915[/C][C]8.41690814639878e-11[/C][C]4.20845407319939e-11[/C][/ROW]
[ROW][C]217[/C][C]0.999999999916202[/C][C]1.67595897395896e-10[/C][C]8.37979486979481e-11[/C][/ROW]
[ROW][C]218[/C][C]0.999999999840818[/C][C]3.18363597595089e-10[/C][C]1.59181798797544e-10[/C][/ROW]
[ROW][C]219[/C][C]0.999999999682761[/C][C]6.34477816905945e-10[/C][C]3.17238908452972e-10[/C][/ROW]
[ROW][C]220[/C][C]0.999999999526344[/C][C]9.47312385743795e-10[/C][C]4.73656192871897e-10[/C][/ROW]
[ROW][C]221[/C][C]0.999999999099138[/C][C]1.80172313492287e-09[/C][C]9.00861567461433e-10[/C][/ROW]
[ROW][C]222[/C][C]0.99999999816666[/C][C]3.66668043327773e-09[/C][C]1.83334021663887e-09[/C][/ROW]
[ROW][C]223[/C][C]0.999999996412526[/C][C]7.17494791393291e-09[/C][C]3.58747395696645e-09[/C][/ROW]
[ROW][C]224[/C][C]0.999999993568176[/C][C]1.28636474397476e-08[/C][C]6.43182371987381e-09[/C][/ROW]
[ROW][C]225[/C][C]0.999999990001158[/C][C]1.99976845839296e-08[/C][C]9.99884229196478e-09[/C][/ROW]
[ROW][C]226[/C][C]0.999999998656914[/C][C]2.68617188173245e-09[/C][C]1.34308594086623e-09[/C][/ROW]
[ROW][C]227[/C][C]0.999999997494944[/C][C]5.01011208376771e-09[/C][C]2.50505604188385e-09[/C][/ROW]
[ROW][C]228[/C][C]0.999999996799596[/C][C]6.4008080031769e-09[/C][C]3.20040400158845e-09[/C][/ROW]
[ROW][C]229[/C][C]0.999999993786282[/C][C]1.24274356548856e-08[/C][C]6.2137178274428e-09[/C][/ROW]
[ROW][C]230[/C][C]0.999999997112846[/C][C]5.77430831474119e-09[/C][C]2.8871541573706e-09[/C][/ROW]
[ROW][C]231[/C][C]0.999999995432493[/C][C]9.13501430517413e-09[/C][C]4.56750715258706e-09[/C][/ROW]
[ROW][C]232[/C][C]0.999999990676378[/C][C]1.86472439046532e-08[/C][C]9.3236219523266e-09[/C][/ROW]
[ROW][C]233[/C][C]0.999999981043051[/C][C]3.79138984615643e-08[/C][C]1.89569492307821e-08[/C][/ROW]
[ROW][C]234[/C][C]0.999999971949408[/C][C]5.61011836359265e-08[/C][C]2.80505918179633e-08[/C][/ROW]
[ROW][C]235[/C][C]0.999999971402625[/C][C]5.71947502326927e-08[/C][C]2.85973751163464e-08[/C][/ROW]
[ROW][C]236[/C][C]0.999999972456891[/C][C]5.50862174490822e-08[/C][C]2.75431087245411e-08[/C][/ROW]
[ROW][C]237[/C][C]0.999999999579624[/C][C]8.40751729327732e-10[/C][C]4.20375864663866e-10[/C][/ROW]
[ROW][C]238[/C][C]0.999999999387312[/C][C]1.22537527929043e-09[/C][C]6.12687639645214e-10[/C][/ROW]
[ROW][C]239[/C][C]0.999999998591493[/C][C]2.81701342941498e-09[/C][C]1.40850671470749e-09[/C][/ROW]
[ROW][C]240[/C][C]0.999999998608623[/C][C]2.78275315992767e-09[/C][C]1.39137657996383e-09[/C][/ROW]
[ROW][C]241[/C][C]0.99999999741062[/C][C]5.17876074664336e-09[/C][C]2.58938037332168e-09[/C][/ROW]
[ROW][C]242[/C][C]0.999999998852947[/C][C]2.29410678148063e-09[/C][C]1.14705339074032e-09[/C][/ROW]
[ROW][C]243[/C][C]0.999999998512574[/C][C]2.97485137506992e-09[/C][C]1.48742568753496e-09[/C][/ROW]
[ROW][C]244[/C][C]0.999999997628054[/C][C]4.74389152949746e-09[/C][C]2.37194576474873e-09[/C][/ROW]
[ROW][C]245[/C][C]0.99999999442009[/C][C]1.11598203953965e-08[/C][C]5.57991019769827e-09[/C][/ROW]
[ROW][C]246[/C][C]0.999999986880264[/C][C]2.62394712528969e-08[/C][C]1.31197356264485e-08[/C][/ROW]
[ROW][C]247[/C][C]0.999999971494169[/C][C]5.70116626128556e-08[/C][C]2.85058313064278e-08[/C][/ROW]
[ROW][C]248[/C][C]0.999999952648004[/C][C]9.47039920051909e-08[/C][C]4.73519960025954e-08[/C][/ROW]
[ROW][C]249[/C][C]0.999999936234707[/C][C]1.27530586297238e-07[/C][C]6.37652931486191e-08[/C][/ROW]
[ROW][C]250[/C][C]0.999999892783967[/C][C]2.14432066034808e-07[/C][C]1.07216033017404e-07[/C][/ROW]
[ROW][C]251[/C][C]0.999999992794746[/C][C]1.44105074203441e-08[/C][C]7.20525371017203e-09[/C][/ROW]
[ROW][C]252[/C][C]0.99999998164437[/C][C]3.67112590549196e-08[/C][C]1.83556295274598e-08[/C][/ROW]
[ROW][C]253[/C][C]0.999999960944176[/C][C]7.8111648353456e-08[/C][C]3.9055824176728e-08[/C][/ROW]
[ROW][C]254[/C][C]0.999999972081039[/C][C]5.58379220667962e-08[/C][C]2.79189610333981e-08[/C][/ROW]
[ROW][C]255[/C][C]0.999999953876759[/C][C]9.22464812174882e-08[/C][C]4.61232406087441e-08[/C][/ROW]
[ROW][C]256[/C][C]0.999999882981125[/C][C]2.34037750561084e-07[/C][C]1.17018875280542e-07[/C][/ROW]
[ROW][C]257[/C][C]0.999999937525685[/C][C]1.24948630697525e-07[/C][C]6.24743153487623e-08[/C][/ROW]
[ROW][C]258[/C][C]0.999999883903858[/C][C]2.32192283932965e-07[/C][C]1.16096141966483e-07[/C][/ROW]
[ROW][C]259[/C][C]0.999999700610315[/C][C]5.98779370539602e-07[/C][C]2.99389685269801e-07[/C][/ROW]
[ROW][C]260[/C][C]0.999999377331485[/C][C]1.24533702971648e-06[/C][C]6.2266851485824e-07[/C][/ROW]
[ROW][C]261[/C][C]0.999999160706573[/C][C]1.67858685444053e-06[/C][C]8.39293427220264e-07[/C][/ROW]
[ROW][C]262[/C][C]0.999998025349228[/C][C]3.94930154482514e-06[/C][C]1.97465077241257e-06[/C][/ROW]
[ROW][C]263[/C][C]0.99999509587472[/C][C]9.80825055946026e-06[/C][C]4.90412527973013e-06[/C][/ROW]
[ROW][C]264[/C][C]0.99999480681396[/C][C]1.03863720795928e-05[/C][C]5.1931860397964e-06[/C][/ROW]
[ROW][C]265[/C][C]0.999991772223705[/C][C]1.64555525897943e-05[/C][C]8.22777629489716e-06[/C][/ROW]
[ROW][C]266[/C][C]0.999979130279681[/C][C]4.17394406378606e-05[/C][C]2.08697203189303e-05[/C][/ROW]
[ROW][C]267[/C][C]0.999973344934309[/C][C]5.33101313814632e-05[/C][C]2.66550656907316e-05[/C][/ROW]
[ROW][C]268[/C][C]0.999950581282917[/C][C]9.8837434166807e-05[/C][C]4.94187170834035e-05[/C][/ROW]
[ROW][C]269[/C][C]0.999986916037012[/C][C]2.61679259769769e-05[/C][C]1.30839629884885e-05[/C][/ROW]
[ROW][C]270[/C][C]0.999981152058334[/C][C]3.76958833327079e-05[/C][C]1.8847941666354e-05[/C][/ROW]
[ROW][C]271[/C][C]0.999994407664452[/C][C]1.11846710965202e-05[/C][C]5.5923355482601e-06[/C][/ROW]
[ROW][C]272[/C][C]0.999981046938812[/C][C]3.79061223766285e-05[/C][C]1.89530611883143e-05[/C][/ROW]
[ROW][C]273[/C][C]0.999948267309929[/C][C]0.000103465380141573[/C][C]5.17326900707863e-05[/C][/ROW]
[ROW][C]274[/C][C]0.999881597817505[/C][C]0.000236804364990216[/C][C]0.000118402182495108[/C][/ROW]
[ROW][C]275[/C][C]0.99962503425339[/C][C]0.000749931493220976[/C][C]0.000374965746610488[/C][/ROW]
[ROW][C]276[/C][C]0.999530612791243[/C][C]0.000938774417513438[/C][C]0.000469387208756719[/C][/ROW]
[ROW][C]277[/C][C]0.998553071586236[/C][C]0.00289385682752817[/C][C]0.00144692841376409[/C][/ROW]
[ROW][C]278[/C][C]0.998387799543972[/C][C]0.00322440091205592[/C][C]0.00161220045602796[/C][/ROW]
[ROW][C]279[/C][C]0.994611325789398[/C][C]0.010777348421203[/C][C]0.00538867421060152[/C][/ROW]
[ROW][C]280[/C][C]0.993298898625271[/C][C]0.0134022027494573[/C][C]0.00670110137472866[/C][/ROW]
[ROW][C]281[/C][C]0.97697039694741[/C][C]0.0460592061051806[/C][C]0.0230296030525903[/C][/ROW]
[ROW][C]282[/C][C]0.93709575833876[/C][C]0.12580848332248[/C][C]0.0629042416612398[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186260&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186260&T=5

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.9633272950389530.07334540992209410.0366727049610471
80.9257278719698450.148544256060310.0742721280301548
90.8768804218282650.246239156343470.123119578171735
100.8200440944803940.3599118110392120.179955905519606
110.7383029620567220.5233940758865560.261697037943278
120.8112905144407370.3774189711185250.188709485559263
130.7594717171269940.4810565657460110.240528282873006
140.6868834637296840.6262330725406330.313116536270316
150.6200816606859570.7598366786280850.379918339314043
160.5574093092555460.8851813814889080.442590690744454
170.4975217044178910.9950434088357830.502478295582109
180.4600968271987680.9201936543975360.539903172801232
190.4376140690944980.8752281381889970.562385930905501
200.6120534072361450.7758931855277110.387946592763855
210.6763611649158890.6472776701682220.323638835084111
220.6224309472136410.7551381055727190.377569052786359
230.9700738786697050.05985224266058970.0299261213302948
240.9581349330985830.08373013380283440.0418650669014172
250.971065430073740.05786913985252080.0289345699262604
260.9904115224295790.01917695514084130.00958847757042065
270.9861806974424610.02763860511507850.0138193025575392
280.9827730935856340.03445381282873240.0172269064143662
290.976168396970430.047663206059140.02383160302957
300.9675974783456250.06480504330875020.0324025216543751
310.957018727007380.0859625459852390.0429812729926195
320.9441225345352980.1117549309294040.0558774654647019
330.9387014420926180.1225971158147640.0612985579073822
340.9223383556435420.1553232887129150.0776616443564575
350.9193412962989720.1613174074020570.0806587037010284
360.9272756437750090.1454487124499820.0727243562249912
370.9087922203505650.1824155592988690.0912077796494347
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Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level2100.760869565217391NOK
5% type I error level2370.858695652173913NOK
10% type I error level2470.894927536231884NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 210 & 0.760869565217391 & NOK \tabularnewline
5% type I error level & 237 & 0.858695652173913 & NOK \tabularnewline
10% type I error level & 247 & 0.894927536231884 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186260&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]210[/C][C]0.760869565217391[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]237[/C][C]0.858695652173913[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]247[/C][C]0.894927536231884[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186260&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186260&T=6

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level2100.760869565217391NOK
5% type I error level2370.858695652173913NOK
10% type I error level2470.894927536231884NOK



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}