FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 11 Dec 2014 21:21:00 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/11/t1418333146sagd1as4krsk3h1.htm/, Retrieved Thu, 16 May 2024 14:14:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266351, Retrieved Thu, 16 May 2024 14:14:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-11 21:21:00] [04df4205f362f56e0d1a9032a00a5d3d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
149	96	18	68	7.5
152	75	7	55	2.5
139	70	31	39	6.0
148	88	39	32	6.5
158	114	46	62	1.0
128	69	31	33	1.0
224	176	67	52	5.5
159	114	35	62	8.5
105	121	52	77	6.5
159	110	77	76	4.5
167	158	37	41	2.0
165	116	32	48	5.0
159	181	36	63	0.5
119	77	38	30	5.0
176	141	69	78	5.0
54	35	21	19	2.5
91	80	26	31	5.0
163	152	54	66	5.5
124	97	36	35	3.5
137	99	42	42	3.0
121	84	23	45	4.0
153	68	34	21	0.5
148	101	112	25	6.5
221	107	35	44	4.5
188	88	47	69	7.5
149	112	47	54	5.5
244	171	37	74	4.0
148	137	109	80	7.5
92	77	24	42	7.0
150	66	20	61	4.0
153	93	22	41	5.5
94	105	23	46	2.5
156	131	32	39	5.5
146	89	7	63	0.5
132	102	30	34	3.5
161	161	92	51	2.5
105	120	43	42	4.5
97	127	55	31	4.5
151	77	16	39	4.5
131	108	49	20	6.0
166	85	71	49	2.5
157	168	43	53	5.0
111	48	29	31	0.0
145	152	56	39	5.0
162	75	46	54	6.5
163	107	19	49	5.0
59	62	23	34	6.0
187	121	59	46	4.5
109	124	30	55	5.5
90	72	61	42	1.0
105	40	7	50	7.5
83	58	38	13	6.0
116	97	32	37	5.0
42	88	16	25	1.0
148	126	19	30	5.0
155	104	22	28	6.5
125	148	48	45	7.0
116	146	23	35	4.5
128	80	26	28	0.0
138	97	33	41	8.5
49	25	9	6	3.5
96	99	24	45	7.5
164	118	34	73	3.5
162	58	48	17	6.0
99	63	18	40	1.5
202	139	43	64	9.0
186	50	33	37	3.5
66	60	28	25	3.5
183	152	71	65	4.0
214	142	26	100	6.5
188	94	67	28	7.5
104	66	34	35	6.0
177	127	80	56	5.0
126	67	29	29	5.5
76	90	16	43	3.5
99	75	59	59	7.5
157	96	58	52	1.0
139	128	32	50	6.5
78	41	47	3	NA
162	146	43	59	6.5
108	69	38	27	6.5
159	186	29	61	7.0
74	81	36	28	3.5
110	85	32	51	1.5
96	54	35	35	4.0
116	46	21	29	7.5
87	106	29	48	4.5
97	34	12	25	0.0
127	60	37	44	3.5
106	95	37	64	5.5
80	57	47	32	5.0
74	62	51	20	4.5
91	36	32	28	2.5
133	56	21	34	7.5
74	54	13	31	7.0
114	64	14	26	0.0
140	76	-2	58	4.5
95	98	20	23	3.0
98	88	24	21	1.5
121	35	11	21	3.5
126	102	23	33	2.5
98	61	24	16	5.5
95	80	14	20	8.0
110	49	52	37	1.0
70	78	15	35	5.0
102	90	23	33	4.5
86	45	19	27	3.0
130	55	35	41	3.0
96	96	24	40	8.0
102	43	39	35	2.5
100	52	29	28	7.0
94	60	13	32	0.0
52	54	8	22	1.0
98	51	18	44	3.5
118	51	24	27	5.5
99	38	19	17	5.5
48	41	23	12	0.5
50	146	16	45	7.5
150	182	33	37	9
154	192	32	37	9.5
109	263	37	108	8.5
68	35	14	10	7
194	439	52	68	8
158	214	75	72	10
159	341	72	143	7
67	58	15	9	8.5
147	292	29	55	9
39	85	13	17	9.5
100	200	40	37	4
111	158	19	27	6
138	199	24	37	8
101	297	121	58	5.5
131	227	93	66	9.5
101	108	36	21	7.5
114	86	23	19	7
165	302	85	78	7.5
114	148	41	35	8
111	178	46	48	7
75	120	18	27	7
82	207	35	43	6
121	157	17	30	10
32	128	4	25	2.5
150	296	28	69	9
117	323	44	72	8
71	79	10	23	6
165	70	38	13	8.5
154	146	57	61	6
126	246	23	43	9
138	145	26	22	8
149	196	36	51	8
145	199	22	67	9
120	127	40	36	5.5
138	91	18	21	5
109	153	31	44	7
132	299	11	45	5.5
172	228	38	34	9
169	190	24	36	2
114	180	37	72	8.5
156	212	37	39	9
172	269	22	43	8.5
68	130	15	25	9
89	179	2	56	7.5
167	243	43	80	10
113	190	31	40	9
115	299	29	73	7.5
78	121	45	34	6
118	137	25	72	10.5
87	305	4	42	8.5
173	157	31	61	8
2	96	-4	23	10
162	183	66	74	10.5
49	52	61	16	6.5
122	238	32	66	9.5
96	40	31	9	8.5
100	226	39	41	7.5
82	190	19	57	5
100	214	31	48	8
115	145	36	51	10
141	119	42	53	7
165	222	21	29	7.5
165	222	21	29	7.5
110	159	25	55	9.5
118	165	32	54	6
158	249	26	43	10
146	125	28	51	7
49	122	32	20	3
90	186	41	79	6
121	148	29	39	7
155	274	33	61	10
104	172	17	55	7
147	84	13	30	3.5
110	168	32	55	8
108	102	30	22	10
113	106	34	37	5.5
115	2	59	2	6
61	139	13	38	6.5
60	95	23	27	6.5
109	130	10	56	8.5
68	72	5	25	4
111	141	31	39	9.5
77	113	19	33	8
73	206	32	43	8.5
151	268	30	57	5.5
89	175	25	43	7
78	77	48	23	9
110	125	35	44	8
220	255	67	54	10
65	111	15	28	8
141	132	22	36	6
117	211	18	39	8
122	92	33	16	5
63	76	46	23	9
44	171	24	40	4.5
52	83	14	24	8.5
62	119	23	29	7
131	266	12	78	9.5
101	186	38	57	8.5
42	50	12	37	7.5
152	117	28	27	7.5
107	219	41	61	5
77	246	12	27	7
154	279	31	69	8
103	148	33	34	5.5
96	137	34	44	8.5
154	130	41	21	7.5
175	181	21	34	9.5
57	98	20	39	7
112	226	44	51	8
143	234	52	34	8.5
49	138	7	31	3.5
110	85	29	13	6.5
131	66	11	12	6.5
167	236	26	51	10.5
56	106	24	24	8.5
137	135	7	19	8
86	122	60	30	10
121	218	13	81	10
149	199	20	42	9.5
168	112	52	22	9
140	278	28	85	10
88	94	25	27	7.5
168	113	39	25	4.5
94	84	9	22	4.5
51	86	19	19	0.5
48	62	13	14	6.5
145	222	60	45	4.5
66	167	19	45	5.5
85	82	34	28	5
109	207	14	51	6
63	184	17	41	4
102	83	45	31	8
162	183	66	74	10.5
128	85	24	24	8.5
86	89	48	19	6.5
114	225	29	51	8
164	237	-2	73	8.5
119	102	51	24	5.5
126	221	2	61	7
132	128	24	23	5
142	91	40	14	3.5
83	198	20	54	5
94	204	19	51	9
81	158	16	62	8.5
166	138	20	36	5
110	226	40	59	9.5
64	44	27	24	3
93	196	25	26	1.5
104	83	49	54	6
105	79	39	39	0.5
49	52	61	16	6.5
88	105	19	36	7.5
95	116	67	31	4.5
102	83	45	31	8
99	196	30	42	9
63	153	8	39	7.5
76	157	19	25	8.5
109	75	52	31	7
117	106	22	38	9.5
57	58	17	31	6.5
120	75	33	17	9.5
73	74	34	22	6
91	185	22	55	8
108	265	30	62	9.5
105	131	25	51	8
117	139	38	30	8
119	196	26	49	9
31	78	13	16	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\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 & 9 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266351&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266351&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266351&T=0

As an alternative you can also use a QR Code:  
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 time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.4102 -0.00273704LFM[t] + 0.0180513B[t] -0.000851679PRH[t] -0.00733472CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.4102 -0.00273704LFM[t] +  0.0180513B[t] -0.000851679PRH[t] -0.00733472CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266351&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.4102 -0.00273704LFM[t] +  0.0180513B[t] -0.000851679PRH[t] -0.00733472CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266351&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266351&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.4102 -0.00273704LFM[t] + 0.0180513B[t] -0.000851679PRH[t] -0.00733472CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.41020.45779.6363.59161e-191.7958e-19
LFM-0.002737040.00400261-0.68380.4946570.247328
B0.01805130.002427987.4351.27208e-126.3604e-13
PRH-0.0008516790.00785301-0.10850.9137140.456857
CH-0.007334720.00947374-0.77420.4394540.219727

\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) & 4.4102 & 0.4577 & 9.636 & 3.59161e-19 & 1.7958e-19 \tabularnewline
LFM & -0.00273704 & 0.00400261 & -0.6838 & 0.494657 & 0.247328 \tabularnewline
B & 0.0180513 & 0.00242798 & 7.435 & 1.27208e-12 & 6.3604e-13 \tabularnewline
PRH & -0.000851679 & 0.00785301 & -0.1085 & 0.913714 & 0.456857 \tabularnewline
CH & -0.00733472 & 0.00947374 & -0.7742 & 0.439454 & 0.219727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266351&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]4.4102[/C][C]0.4577[/C][C]9.636[/C][C]3.59161e-19[/C][C]1.7958e-19[/C][/ROW]
[ROW][C]LFM[/C][C]-0.00273704[/C][C]0.00400261[/C][C]-0.6838[/C][C]0.494657[/C][C]0.247328[/C][/ROW]
[ROW][C]B[/C][C]0.0180513[/C][C]0.00242798[/C][C]7.435[/C][C]1.27208e-12[/C][C]6.3604e-13[/C][/ROW]
[ROW][C]PRH[/C][C]-0.000851679[/C][C]0.00785301[/C][C]-0.1085[/C][C]0.913714[/C][C]0.456857[/C][/ROW]
[ROW][C]CH[/C][C]-0.00733472[/C][C]0.00947374[/C][C]-0.7742[/C][C]0.439454[/C][C]0.219727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266351&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266351&T=2

As an alternative you can also use a QR Code:  
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)4.41020.45779.6363.59161e-191.7958e-19
LFM-0.002737040.00400261-0.68380.4946570.247328
B0.01805130.002427987.4351.27208e-126.3604e-13
PRH-0.0008516790.00785301-0.10850.9137140.456857
CH-0.007334720.00947374-0.77420.4394540.219727






Multiple Linear Regression - Regression Statistics
Multiple R0.451811
R-squared0.204133
Adjusted R-squared0.192804
F-TEST (value)18.0186
F-TEST (DF numerator)4
F-TEST (DF denominator)281
p-value3.47167e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29709
Sum Squared Residuals1482.73

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.451811 \tabularnewline
R-squared & 0.204133 \tabularnewline
Adjusted R-squared & 0.192804 \tabularnewline
F-TEST (value) & 18.0186 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 3.47167e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.29709 \tabularnewline
Sum Squared Residuals & 1482.73 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266351&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.451811[/C][/ROW]
[ROW][C]R-squared[/C][C]0.204133[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.192804[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.0186[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]3.47167e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.29709[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1482.73[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266351&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266351&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Regression Statistics
Multiple R0.451811
R-squared0.204133
Adjusted R-squared0.192804
F-TEST (value)18.0186
F-TEST (DF numerator)4
F-TEST (DF denominator)281
p-value3.47167e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29709
Sum Squared Residuals1482.73






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.221222.27878
22.54.93865-2.43865
364.980891.01911
46.55.325711.17429
515.54167-4.54167
615.03695-4.03695
75.56.53567-1.03567
88.55.54832.9517
96.55.697960.80204
104.55.33764-0.837639
1126.47299-4.47299
1255.67322-0.673222
130.56.74955-6.24955
1455.22204-0.222041
1555.84284-0.842843
162.54.73695-2.23695
1755.35572-0.355717
185.56.17778-0.67778
193.55.53441-2.03441
2035.47848-2.47848
2145.24568-1.24568
220.55.03594-4.53594
236.55.549550.950453
244.55.38427-0.88427
257.54.938032.56197
265.55.58803-0.0880259
2746.25486-2.25486
287.55.798541.70146
2975.219851.78015
3044.72658-0.726582
315.55.350750.149253
322.55.69132-3.19132
335.56.03464-0.534637
340.55.14911-4.64911
353.55.61522-2.11522
362.56.42337-3.92337
374.55.94429-1.44429
384.56.16301-1.66301
394.55.08718-0.58718
4065.812760.187236
412.55.07035-2.57035
4256.58774-1.58774
4304.72078-4.72078
4456.42338-1.42338
456.54.88541.6146
4655.51997-0.519972
4765.098930.90107
484.55.69494-1.19494
495.55.92127-0.421266
5015.10355-4.10355
517.54.472173.02783
5265.102290.89771
5355.54504-0.545044
5415.68677-4.68677
5556.04336-1.04336
566.55.639190.860812
5776.368720.631278
584.56.45189-1.95189
5905.27645-5.27645
608.55.454643.04536
613.54.6757-1.1757
627.55.584021.91598
633.55.52699-2.02699
6464.848211.15179
651.54.96775-3.46775
6695.860413.13959
673.54.50419-1.00419
683.55.10542-1.60542
6946.1159-2.1159
706.55.632150.867855
717.55.330032.16997
7265.031270.968735
7355.73938-0.739383
745.55.037370.462632
753.55.49779-1.99779
767.55.010092.48991
7715.28261-4.28261
786.55.946330.553669
79NANA0.367079
806.55.129741.37026
816.56.360440.139563
8278.93379-1.93379
833.57.24217-3.74217
841.52.33569-0.835695
8541.192482.80752
867.58.70875-1.20875
874.59.06487-4.56487
8801.29144-1.29144
893.53.334020.165984
905.55.445420.0545751
9155.63671-0.636713
924.56.57835-2.07835
932.5-0.2102152.71022
947.55.443992.05601
95712.0508-5.05084
9600.475207-0.475207
974.57.23348-2.73348
9837.05602-4.05602
991.52.54742-1.04742
1003.56.64493-3.14493
1012.52.105310.394693
1025.52.935672.56433
103811.678-3.67797
10411.35712-0.357122
10555.99401-0.994008
1064.56.27291-1.77291
10734.71668-1.71668
10830.5665432.43346
109810.1173-2.1173
1102.50.3450972.1549
111711.9902-4.99022
11204.07447-4.07447
11312.22453-1.22453
1143.52.789370.710628
1155.54.684310.815685
1165.59.91132-4.41132
1170.5-0.434850.93485
1187.55.485492.01451
11996.655912.34409
1209.59.035690.464308
1218.56.270612.22939
122710.2607-3.26068
12385.248752.75125
1241012.0203-2.02032
12573.695013.30499
1268.58.350730.149275
12795.202063.79794
1289.512.9413-3.44131
12944.74428-0.744276
13065.332870.667127
131811.4665-3.46653
1325.53.5861.914
1339.57.898611.60139
1347.55.991641.50836
13578.26558-1.26558
1367.55.978141.52186
13787.928280.0717225
13876.157710.842287
13978.57718-1.57718
14062.678553.32145
1411013.9464-3.94641
1422.52.312880.187115
143910.355-1.35496
14487.464710.535289
14562.594473.40553
1468.58.62822-0.128224
14765.170970.829029
14897.466421.53358
14987.135710.864294
15086.095381.90462
15199.57616-0.576156
1525.56.0058-0.505801
15354.524580.475416
154710.6068-3.60682
1555.54.273381.22662
156914.0929-5.0929
15720.2878011.7122
1588.56.992531.50747
15998.96110.0389016
1608.55.874612.62539
16198.485340.51466
1627.55.216182.28382
163108.210871.78913
164910.4326-1.43264
1657.57.59321-0.0932147
16661.510874.48913
16710.511.3663-0.866257
1688.56.796931.70307
16983.972364.02764
170106.171213.82879
17110.59.045451.45455
1726.54.861151.63885
1739.55.777093.72291
1748.58.88215-0.382151
1757.59.68125-2.18125
17654.621010.378994
17784.308153.69185
178108.747871.25213
17977.23539-0.235385
1807.57.73539-0.235385
1817.54.554582.94542
1829.510.1424-0.642367
18364.134981.86502
184108.869091.13091
185710.3044-3.3044
18633.90705-0.907048
18765.439860.56014
18875.456491.54351
189109.812480.187515
19078.79305-1.79305
1913.52.211081.28892
19283.768924.23108
1931010.214-0.214014
1945.53.566631.93337
19565.962580.0374179
1966.55.743230.756772
1976.54.039272.46073
1988.59.83615-1.33615
19940.8391683.16083
2009.57.481022.01898
20187.086320.913682
2028.511.391-2.89103
2035.55.48890.0111026
20473.377093.62291
20597.0131.987
20685.9582.042
207108.017841.98216
20888.12426-0.124265
20965.597410.402593
21088.59154-0.591543
21151.401793.59821
212911.5627-2.56271
2134.51.578182.92182
2148.57.656320.843685
21575.770961.22904
2169.58.040861.45914
2178.55.916212.58379
2187.55.884291.61571
2197.510.0882-2.58824
22056.43181-1.43181
22177.49251-0.49251
22289.02239-1.02239
2235.53.268792.23121
2248.57.146421.35358
2257.54.931242.56876
2269.58.220131.27987
22776.77170.228299
22887.449140.55086
2298.511.5338-3.03383
2303.52.523440.976561
2316.55.145651.35435
2326.53.817012.68299
23310.57.973892.52611
2348.56.826831.67317
23584.105933.89407
236107.409022.59098
237107.76952.2305
2389.56.266473.23353
23997.397981.60202
240108.146841.85316
2417.58.77359-1.27359
2424.55.5002-1.0002
2434.59.66748-5.16748
2440.5-0.7157521.21575
2456.59.63956-3.13956
2464.55.89788-1.39788
2475.55.92343-0.423432
24856.46249-1.46249
24969.244-3.244
25041.363582.63642
25184.171213.82879
25210.57.397753.10225
2538.57.601140.898857
2546.56.260950.239049
25587.205750.794247
2568.58.70626-0.206259
2575.56.10555-0.605549
25878.17034-1.17034
25957.02746-2.02746
2603.55.84408-2.34408
26153.445131.55487
26297.072231.92777
2638.59.66585-1.16585
26453.22191.7781
2659.511.3303-1.83026
26638.98172-5.98172
2671.50.6860020.813998
268610.7296-4.7296
2690.5-0.9545511.45455
2706.54.78451.7155
2717.58.9597-1.4597
2724.51.863582.63642
27386.343681.65632
27498.206750.79325
2757.55.836691.66331
2768.56.694051.80595
27773.205953.79405
2789.58.059311.44069
2796.52.282814.21719
2809.58.855870.644125
28165.078470.921526
28286.917891.08211
2839.57.592171.90783
28486.346691.65331
28586.2411.759
28699.60493-0.604929
2875NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.22122 & 2.27878 \tabularnewline
2 & 2.5 & 4.93865 & -2.43865 \tabularnewline
3 & 6 & 4.98089 & 1.01911 \tabularnewline
4 & 6.5 & 5.32571 & 1.17429 \tabularnewline
5 & 1 & 5.54167 & -4.54167 \tabularnewline
6 & 1 & 5.03695 & -4.03695 \tabularnewline
7 & 5.5 & 6.53567 & -1.03567 \tabularnewline
8 & 8.5 & 5.5483 & 2.9517 \tabularnewline
9 & 6.5 & 5.69796 & 0.80204 \tabularnewline
10 & 4.5 & 5.33764 & -0.837639 \tabularnewline
11 & 2 & 6.47299 & -4.47299 \tabularnewline
12 & 5 & 5.67322 & -0.673222 \tabularnewline
13 & 0.5 & 6.74955 & -6.24955 \tabularnewline
14 & 5 & 5.22204 & -0.222041 \tabularnewline
15 & 5 & 5.84284 & -0.842843 \tabularnewline
16 & 2.5 & 4.73695 & -2.23695 \tabularnewline
17 & 5 & 5.35572 & -0.355717 \tabularnewline
18 & 5.5 & 6.17778 & -0.67778 \tabularnewline
19 & 3.5 & 5.53441 & -2.03441 \tabularnewline
20 & 3 & 5.47848 & -2.47848 \tabularnewline
21 & 4 & 5.24568 & -1.24568 \tabularnewline
22 & 0.5 & 5.03594 & -4.53594 \tabularnewline
23 & 6.5 & 5.54955 & 0.950453 \tabularnewline
24 & 4.5 & 5.38427 & -0.88427 \tabularnewline
25 & 7.5 & 4.93803 & 2.56197 \tabularnewline
26 & 5.5 & 5.58803 & -0.0880259 \tabularnewline
27 & 4 & 6.25486 & -2.25486 \tabularnewline
28 & 7.5 & 5.79854 & 1.70146 \tabularnewline
29 & 7 & 5.21985 & 1.78015 \tabularnewline
30 & 4 & 4.72658 & -0.726582 \tabularnewline
31 & 5.5 & 5.35075 & 0.149253 \tabularnewline
32 & 2.5 & 5.69132 & -3.19132 \tabularnewline
33 & 5.5 & 6.03464 & -0.534637 \tabularnewline
34 & 0.5 & 5.14911 & -4.64911 \tabularnewline
35 & 3.5 & 5.61522 & -2.11522 \tabularnewline
36 & 2.5 & 6.42337 & -3.92337 \tabularnewline
37 & 4.5 & 5.94429 & -1.44429 \tabularnewline
38 & 4.5 & 6.16301 & -1.66301 \tabularnewline
39 & 4.5 & 5.08718 & -0.58718 \tabularnewline
40 & 6 & 5.81276 & 0.187236 \tabularnewline
41 & 2.5 & 5.07035 & -2.57035 \tabularnewline
42 & 5 & 6.58774 & -1.58774 \tabularnewline
43 & 0 & 4.72078 & -4.72078 \tabularnewline
44 & 5 & 6.42338 & -1.42338 \tabularnewline
45 & 6.5 & 4.8854 & 1.6146 \tabularnewline
46 & 5 & 5.51997 & -0.519972 \tabularnewline
47 & 6 & 5.09893 & 0.90107 \tabularnewline
48 & 4.5 & 5.69494 & -1.19494 \tabularnewline
49 & 5.5 & 5.92127 & -0.421266 \tabularnewline
50 & 1 & 5.10355 & -4.10355 \tabularnewline
51 & 7.5 & 4.47217 & 3.02783 \tabularnewline
52 & 6 & 5.10229 & 0.89771 \tabularnewline
53 & 5 & 5.54504 & -0.545044 \tabularnewline
54 & 1 & 5.68677 & -4.68677 \tabularnewline
55 & 5 & 6.04336 & -1.04336 \tabularnewline
56 & 6.5 & 5.63919 & 0.860812 \tabularnewline
57 & 7 & 6.36872 & 0.631278 \tabularnewline
58 & 4.5 & 6.45189 & -1.95189 \tabularnewline
59 & 0 & 5.27645 & -5.27645 \tabularnewline
60 & 8.5 & 5.45464 & 3.04536 \tabularnewline
61 & 3.5 & 4.6757 & -1.1757 \tabularnewline
62 & 7.5 & 5.58402 & 1.91598 \tabularnewline
63 & 3.5 & 5.52699 & -2.02699 \tabularnewline
64 & 6 & 4.84821 & 1.15179 \tabularnewline
65 & 1.5 & 4.96775 & -3.46775 \tabularnewline
66 & 9 & 5.86041 & 3.13959 \tabularnewline
67 & 3.5 & 4.50419 & -1.00419 \tabularnewline
68 & 3.5 & 5.10542 & -1.60542 \tabularnewline
69 & 4 & 6.1159 & -2.1159 \tabularnewline
70 & 6.5 & 5.63215 & 0.867855 \tabularnewline
71 & 7.5 & 5.33003 & 2.16997 \tabularnewline
72 & 6 & 5.03127 & 0.968735 \tabularnewline
73 & 5 & 5.73938 & -0.739383 \tabularnewline
74 & 5.5 & 5.03737 & 0.462632 \tabularnewline
75 & 3.5 & 5.49779 & -1.99779 \tabularnewline
76 & 7.5 & 5.01009 & 2.48991 \tabularnewline
77 & 1 & 5.28261 & -4.28261 \tabularnewline
78 & 6.5 & 5.94633 & 0.553669 \tabularnewline
79 & NA & NA & 0.367079 \tabularnewline
80 & 6.5 & 5.12974 & 1.37026 \tabularnewline
81 & 6.5 & 6.36044 & 0.139563 \tabularnewline
82 & 7 & 8.93379 & -1.93379 \tabularnewline
83 & 3.5 & 7.24217 & -3.74217 \tabularnewline
84 & 1.5 & 2.33569 & -0.835695 \tabularnewline
85 & 4 & 1.19248 & 2.80752 \tabularnewline
86 & 7.5 & 8.70875 & -1.20875 \tabularnewline
87 & 4.5 & 9.06487 & -4.56487 \tabularnewline
88 & 0 & 1.29144 & -1.29144 \tabularnewline
89 & 3.5 & 3.33402 & 0.165984 \tabularnewline
90 & 5.5 & 5.44542 & 0.0545751 \tabularnewline
91 & 5 & 5.63671 & -0.636713 \tabularnewline
92 & 4.5 & 6.57835 & -2.07835 \tabularnewline
93 & 2.5 & -0.210215 & 2.71022 \tabularnewline
94 & 7.5 & 5.44399 & 2.05601 \tabularnewline
95 & 7 & 12.0508 & -5.05084 \tabularnewline
96 & 0 & 0.475207 & -0.475207 \tabularnewline
97 & 4.5 & 7.23348 & -2.73348 \tabularnewline
98 & 3 & 7.05602 & -4.05602 \tabularnewline
99 & 1.5 & 2.54742 & -1.04742 \tabularnewline
100 & 3.5 & 6.64493 & -3.14493 \tabularnewline
101 & 2.5 & 2.10531 & 0.394693 \tabularnewline
102 & 5.5 & 2.93567 & 2.56433 \tabularnewline
103 & 8 & 11.678 & -3.67797 \tabularnewline
104 & 1 & 1.35712 & -0.357122 \tabularnewline
105 & 5 & 5.99401 & -0.994008 \tabularnewline
106 & 4.5 & 6.27291 & -1.77291 \tabularnewline
107 & 3 & 4.71668 & -1.71668 \tabularnewline
108 & 3 & 0.566543 & 2.43346 \tabularnewline
109 & 8 & 10.1173 & -2.1173 \tabularnewline
110 & 2.5 & 0.345097 & 2.1549 \tabularnewline
111 & 7 & 11.9902 & -4.99022 \tabularnewline
112 & 0 & 4.07447 & -4.07447 \tabularnewline
113 & 1 & 2.22453 & -1.22453 \tabularnewline
114 & 3.5 & 2.78937 & 0.710628 \tabularnewline
115 & 5.5 & 4.68431 & 0.815685 \tabularnewline
116 & 5.5 & 9.91132 & -4.41132 \tabularnewline
117 & 0.5 & -0.43485 & 0.93485 \tabularnewline
118 & 7.5 & 5.48549 & 2.01451 \tabularnewline
119 & 9 & 6.65591 & 2.34409 \tabularnewline
120 & 9.5 & 9.03569 & 0.464308 \tabularnewline
121 & 8.5 & 6.27061 & 2.22939 \tabularnewline
122 & 7 & 10.2607 & -3.26068 \tabularnewline
123 & 8 & 5.24875 & 2.75125 \tabularnewline
124 & 10 & 12.0203 & -2.02032 \tabularnewline
125 & 7 & 3.69501 & 3.30499 \tabularnewline
126 & 8.5 & 8.35073 & 0.149275 \tabularnewline
127 & 9 & 5.20206 & 3.79794 \tabularnewline
128 & 9.5 & 12.9413 & -3.44131 \tabularnewline
129 & 4 & 4.74428 & -0.744276 \tabularnewline
130 & 6 & 5.33287 & 0.667127 \tabularnewline
131 & 8 & 11.4665 & -3.46653 \tabularnewline
132 & 5.5 & 3.586 & 1.914 \tabularnewline
133 & 9.5 & 7.89861 & 1.60139 \tabularnewline
134 & 7.5 & 5.99164 & 1.50836 \tabularnewline
135 & 7 & 8.26558 & -1.26558 \tabularnewline
136 & 7.5 & 5.97814 & 1.52186 \tabularnewline
137 & 8 & 7.92828 & 0.0717225 \tabularnewline
138 & 7 & 6.15771 & 0.842287 \tabularnewline
139 & 7 & 8.57718 & -1.57718 \tabularnewline
140 & 6 & 2.67855 & 3.32145 \tabularnewline
141 & 10 & 13.9464 & -3.94641 \tabularnewline
142 & 2.5 & 2.31288 & 0.187115 \tabularnewline
143 & 9 & 10.355 & -1.35496 \tabularnewline
144 & 8 & 7.46471 & 0.535289 \tabularnewline
145 & 6 & 2.59447 & 3.40553 \tabularnewline
146 & 8.5 & 8.62822 & -0.128224 \tabularnewline
147 & 6 & 5.17097 & 0.829029 \tabularnewline
148 & 9 & 7.46642 & 1.53358 \tabularnewline
149 & 8 & 7.13571 & 0.864294 \tabularnewline
150 & 8 & 6.09538 & 1.90462 \tabularnewline
151 & 9 & 9.57616 & -0.576156 \tabularnewline
152 & 5.5 & 6.0058 & -0.505801 \tabularnewline
153 & 5 & 4.52458 & 0.475416 \tabularnewline
154 & 7 & 10.6068 & -3.60682 \tabularnewline
155 & 5.5 & 4.27338 & 1.22662 \tabularnewline
156 & 9 & 14.0929 & -5.0929 \tabularnewline
157 & 2 & 0.287801 & 1.7122 \tabularnewline
158 & 8.5 & 6.99253 & 1.50747 \tabularnewline
159 & 9 & 8.9611 & 0.0389016 \tabularnewline
160 & 8.5 & 5.87461 & 2.62539 \tabularnewline
161 & 9 & 8.48534 & 0.51466 \tabularnewline
162 & 7.5 & 5.21618 & 2.28382 \tabularnewline
163 & 10 & 8.21087 & 1.78913 \tabularnewline
164 & 9 & 10.4326 & -1.43264 \tabularnewline
165 & 7.5 & 7.59321 & -0.0932147 \tabularnewline
166 & 6 & 1.51087 & 4.48913 \tabularnewline
167 & 10.5 & 11.3663 & -0.866257 \tabularnewline
168 & 8.5 & 6.79693 & 1.70307 \tabularnewline
169 & 8 & 3.97236 & 4.02764 \tabularnewline
170 & 10 & 6.17121 & 3.82879 \tabularnewline
171 & 10.5 & 9.04545 & 1.45455 \tabularnewline
172 & 6.5 & 4.86115 & 1.63885 \tabularnewline
173 & 9.5 & 5.77709 & 3.72291 \tabularnewline
174 & 8.5 & 8.88215 & -0.382151 \tabularnewline
175 & 7.5 & 9.68125 & -2.18125 \tabularnewline
176 & 5 & 4.62101 & 0.378994 \tabularnewline
177 & 8 & 4.30815 & 3.69185 \tabularnewline
178 & 10 & 8.74787 & 1.25213 \tabularnewline
179 & 7 & 7.23539 & -0.235385 \tabularnewline
180 & 7.5 & 7.73539 & -0.235385 \tabularnewline
181 & 7.5 & 4.55458 & 2.94542 \tabularnewline
182 & 9.5 & 10.1424 & -0.642367 \tabularnewline
183 & 6 & 4.13498 & 1.86502 \tabularnewline
184 & 10 & 8.86909 & 1.13091 \tabularnewline
185 & 7 & 10.3044 & -3.3044 \tabularnewline
186 & 3 & 3.90705 & -0.907048 \tabularnewline
187 & 6 & 5.43986 & 0.56014 \tabularnewline
188 & 7 & 5.45649 & 1.54351 \tabularnewline
189 & 10 & 9.81248 & 0.187515 \tabularnewline
190 & 7 & 8.79305 & -1.79305 \tabularnewline
191 & 3.5 & 2.21108 & 1.28892 \tabularnewline
192 & 8 & 3.76892 & 4.23108 \tabularnewline
193 & 10 & 10.214 & -0.214014 \tabularnewline
194 & 5.5 & 3.56663 & 1.93337 \tabularnewline
195 & 6 & 5.96258 & 0.0374179 \tabularnewline
196 & 6.5 & 5.74323 & 0.756772 \tabularnewline
197 & 6.5 & 4.03927 & 2.46073 \tabularnewline
198 & 8.5 & 9.83615 & -1.33615 \tabularnewline
199 & 4 & 0.839168 & 3.16083 \tabularnewline
200 & 9.5 & 7.48102 & 2.01898 \tabularnewline
201 & 8 & 7.08632 & 0.913682 \tabularnewline
202 & 8.5 & 11.391 & -2.89103 \tabularnewline
203 & 5.5 & 5.4889 & 0.0111026 \tabularnewline
204 & 7 & 3.37709 & 3.62291 \tabularnewline
205 & 9 & 7.013 & 1.987 \tabularnewline
206 & 8 & 5.958 & 2.042 \tabularnewline
207 & 10 & 8.01784 & 1.98216 \tabularnewline
208 & 8 & 8.12426 & -0.124265 \tabularnewline
209 & 6 & 5.59741 & 0.402593 \tabularnewline
210 & 8 & 8.59154 & -0.591543 \tabularnewline
211 & 5 & 1.40179 & 3.59821 \tabularnewline
212 & 9 & 11.5627 & -2.56271 \tabularnewline
213 & 4.5 & 1.57818 & 2.92182 \tabularnewline
214 & 8.5 & 7.65632 & 0.843685 \tabularnewline
215 & 7 & 5.77096 & 1.22904 \tabularnewline
216 & 9.5 & 8.04086 & 1.45914 \tabularnewline
217 & 8.5 & 5.91621 & 2.58379 \tabularnewline
218 & 7.5 & 5.88429 & 1.61571 \tabularnewline
219 & 7.5 & 10.0882 & -2.58824 \tabularnewline
220 & 5 & 6.43181 & -1.43181 \tabularnewline
221 & 7 & 7.49251 & -0.49251 \tabularnewline
222 & 8 & 9.02239 & -1.02239 \tabularnewline
223 & 5.5 & 3.26879 & 2.23121 \tabularnewline
224 & 8.5 & 7.14642 & 1.35358 \tabularnewline
225 & 7.5 & 4.93124 & 2.56876 \tabularnewline
226 & 9.5 & 8.22013 & 1.27987 \tabularnewline
227 & 7 & 6.7717 & 0.228299 \tabularnewline
228 & 8 & 7.44914 & 0.55086 \tabularnewline
229 & 8.5 & 11.5338 & -3.03383 \tabularnewline
230 & 3.5 & 2.52344 & 0.976561 \tabularnewline
231 & 6.5 & 5.14565 & 1.35435 \tabularnewline
232 & 6.5 & 3.81701 & 2.68299 \tabularnewline
233 & 10.5 & 7.97389 & 2.52611 \tabularnewline
234 & 8.5 & 6.82683 & 1.67317 \tabularnewline
235 & 8 & 4.10593 & 3.89407 \tabularnewline
236 & 10 & 7.40902 & 2.59098 \tabularnewline
237 & 10 & 7.7695 & 2.2305 \tabularnewline
238 & 9.5 & 6.26647 & 3.23353 \tabularnewline
239 & 9 & 7.39798 & 1.60202 \tabularnewline
240 & 10 & 8.14684 & 1.85316 \tabularnewline
241 & 7.5 & 8.77359 & -1.27359 \tabularnewline
242 & 4.5 & 5.5002 & -1.0002 \tabularnewline
243 & 4.5 & 9.66748 & -5.16748 \tabularnewline
244 & 0.5 & -0.715752 & 1.21575 \tabularnewline
245 & 6.5 & 9.63956 & -3.13956 \tabularnewline
246 & 4.5 & 5.89788 & -1.39788 \tabularnewline
247 & 5.5 & 5.92343 & -0.423432 \tabularnewline
248 & 5 & 6.46249 & -1.46249 \tabularnewline
249 & 6 & 9.244 & -3.244 \tabularnewline
250 & 4 & 1.36358 & 2.63642 \tabularnewline
251 & 8 & 4.17121 & 3.82879 \tabularnewline
252 & 10.5 & 7.39775 & 3.10225 \tabularnewline
253 & 8.5 & 7.60114 & 0.898857 \tabularnewline
254 & 6.5 & 6.26095 & 0.239049 \tabularnewline
255 & 8 & 7.20575 & 0.794247 \tabularnewline
256 & 8.5 & 8.70626 & -0.206259 \tabularnewline
257 & 5.5 & 6.10555 & -0.605549 \tabularnewline
258 & 7 & 8.17034 & -1.17034 \tabularnewline
259 & 5 & 7.02746 & -2.02746 \tabularnewline
260 & 3.5 & 5.84408 & -2.34408 \tabularnewline
261 & 5 & 3.44513 & 1.55487 \tabularnewline
262 & 9 & 7.07223 & 1.92777 \tabularnewline
263 & 8.5 & 9.66585 & -1.16585 \tabularnewline
264 & 5 & 3.2219 & 1.7781 \tabularnewline
265 & 9.5 & 11.3303 & -1.83026 \tabularnewline
266 & 3 & 8.98172 & -5.98172 \tabularnewline
267 & 1.5 & 0.686002 & 0.813998 \tabularnewline
268 & 6 & 10.7296 & -4.7296 \tabularnewline
269 & 0.5 & -0.954551 & 1.45455 \tabularnewline
270 & 6.5 & 4.7845 & 1.7155 \tabularnewline
271 & 7.5 & 8.9597 & -1.4597 \tabularnewline
272 & 4.5 & 1.86358 & 2.63642 \tabularnewline
273 & 8 & 6.34368 & 1.65632 \tabularnewline
274 & 9 & 8.20675 & 0.79325 \tabularnewline
275 & 7.5 & 5.83669 & 1.66331 \tabularnewline
276 & 8.5 & 6.69405 & 1.80595 \tabularnewline
277 & 7 & 3.20595 & 3.79405 \tabularnewline
278 & 9.5 & 8.05931 & 1.44069 \tabularnewline
279 & 6.5 & 2.28281 & 4.21719 \tabularnewline
280 & 9.5 & 8.85587 & 0.644125 \tabularnewline
281 & 6 & 5.07847 & 0.921526 \tabularnewline
282 & 8 & 6.91789 & 1.08211 \tabularnewline
283 & 9.5 & 7.59217 & 1.90783 \tabularnewline
284 & 8 & 6.34669 & 1.65331 \tabularnewline
285 & 8 & 6.241 & 1.759 \tabularnewline
286 & 9 & 9.60493 & -0.604929 \tabularnewline
287 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266351&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]7.5[/C][C]5.22122[/C][C]2.27878[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]4.93865[/C][C]-2.43865[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]4.98089[/C][C]1.01911[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]5.32571[/C][C]1.17429[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.54167[/C][C]-4.54167[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]5.03695[/C][C]-4.03695[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]6.53567[/C][C]-1.03567[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]5.5483[/C][C]2.9517[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]5.69796[/C][C]0.80204[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]5.33764[/C][C]-0.837639[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]6.47299[/C][C]-4.47299[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]5.67322[/C][C]-0.673222[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]6.74955[/C][C]-6.24955[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]5.22204[/C][C]-0.222041[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]5.84284[/C][C]-0.842843[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]4.73695[/C][C]-2.23695[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]5.35572[/C][C]-0.355717[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]6.17778[/C][C]-0.67778[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]5.53441[/C][C]-2.03441[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]5.47848[/C][C]-2.47848[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]5.24568[/C][C]-1.24568[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]5.03594[/C][C]-4.53594[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]5.54955[/C][C]0.950453[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]5.38427[/C][C]-0.88427[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]4.93803[/C][C]2.56197[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]5.58803[/C][C]-0.0880259[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]6.25486[/C][C]-2.25486[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]5.79854[/C][C]1.70146[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]5.21985[/C][C]1.78015[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]4.72658[/C][C]-0.726582[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]5.35075[/C][C]0.149253[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]5.69132[/C][C]-3.19132[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]6.03464[/C][C]-0.534637[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]5.14911[/C][C]-4.64911[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]5.61522[/C][C]-2.11522[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]6.42337[/C][C]-3.92337[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.94429[/C][C]-1.44429[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]6.16301[/C][C]-1.66301[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]5.08718[/C][C]-0.58718[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.81276[/C][C]0.187236[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]5.07035[/C][C]-2.57035[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.58774[/C][C]-1.58774[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]4.72078[/C][C]-4.72078[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.42338[/C][C]-1.42338[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]4.8854[/C][C]1.6146[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]5.51997[/C][C]-0.519972[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]5.09893[/C][C]0.90107[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]5.69494[/C][C]-1.19494[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]5.92127[/C][C]-0.421266[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]5.10355[/C][C]-4.10355[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]4.47217[/C][C]3.02783[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]5.10229[/C][C]0.89771[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.54504[/C][C]-0.545044[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]5.68677[/C][C]-4.68677[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]6.04336[/C][C]-1.04336[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]5.63919[/C][C]0.860812[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]6.36872[/C][C]0.631278[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]6.45189[/C][C]-1.95189[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]5.27645[/C][C]-5.27645[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]5.45464[/C][C]3.04536[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.6757[/C][C]-1.1757[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]5.58402[/C][C]1.91598[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]5.52699[/C][C]-2.02699[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]4.84821[/C][C]1.15179[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]4.96775[/C][C]-3.46775[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]5.86041[/C][C]3.13959[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]4.50419[/C][C]-1.00419[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]5.10542[/C][C]-1.60542[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]6.1159[/C][C]-2.1159[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]5.63215[/C][C]0.867855[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]5.33003[/C][C]2.16997[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]5.03127[/C][C]0.968735[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]5.73938[/C][C]-0.739383[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]5.03737[/C][C]0.462632[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]5.49779[/C][C]-1.99779[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]5.01009[/C][C]2.48991[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]5.28261[/C][C]-4.28261[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.94633[/C][C]0.553669[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]0.367079[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]5.12974[/C][C]1.37026[/C][/ROW]
[ROW][C]81[/C][C]6.5[/C][C]6.36044[/C][C]0.139563[/C][/ROW]
[ROW][C]82[/C][C]7[/C][C]8.93379[/C][C]-1.93379[/C][/ROW]
[ROW][C]83[/C][C]3.5[/C][C]7.24217[/C][C]-3.74217[/C][/ROW]
[ROW][C]84[/C][C]1.5[/C][C]2.33569[/C][C]-0.835695[/C][/ROW]
[ROW][C]85[/C][C]4[/C][C]1.19248[/C][C]2.80752[/C][/ROW]
[ROW][C]86[/C][C]7.5[/C][C]8.70875[/C][C]-1.20875[/C][/ROW]
[ROW][C]87[/C][C]4.5[/C][C]9.06487[/C][C]-4.56487[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]1.29144[/C][C]-1.29144[/C][/ROW]
[ROW][C]89[/C][C]3.5[/C][C]3.33402[/C][C]0.165984[/C][/ROW]
[ROW][C]90[/C][C]5.5[/C][C]5.44542[/C][C]0.0545751[/C][/ROW]
[ROW][C]91[/C][C]5[/C][C]5.63671[/C][C]-0.636713[/C][/ROW]
[ROW][C]92[/C][C]4.5[/C][C]6.57835[/C][C]-2.07835[/C][/ROW]
[ROW][C]93[/C][C]2.5[/C][C]-0.210215[/C][C]2.71022[/C][/ROW]
[ROW][C]94[/C][C]7.5[/C][C]5.44399[/C][C]2.05601[/C][/ROW]
[ROW][C]95[/C][C]7[/C][C]12.0508[/C][C]-5.05084[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.475207[/C][C]-0.475207[/C][/ROW]
[ROW][C]97[/C][C]4.5[/C][C]7.23348[/C][C]-2.73348[/C][/ROW]
[ROW][C]98[/C][C]3[/C][C]7.05602[/C][C]-4.05602[/C][/ROW]
[ROW][C]99[/C][C]1.5[/C][C]2.54742[/C][C]-1.04742[/C][/ROW]
[ROW][C]100[/C][C]3.5[/C][C]6.64493[/C][C]-3.14493[/C][/ROW]
[ROW][C]101[/C][C]2.5[/C][C]2.10531[/C][C]0.394693[/C][/ROW]
[ROW][C]102[/C][C]5.5[/C][C]2.93567[/C][C]2.56433[/C][/ROW]
[ROW][C]103[/C][C]8[/C][C]11.678[/C][C]-3.67797[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]1.35712[/C][C]-0.357122[/C][/ROW]
[ROW][C]105[/C][C]5[/C][C]5.99401[/C][C]-0.994008[/C][/ROW]
[ROW][C]106[/C][C]4.5[/C][C]6.27291[/C][C]-1.77291[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]4.71668[/C][C]-1.71668[/C][/ROW]
[ROW][C]108[/C][C]3[/C][C]0.566543[/C][C]2.43346[/C][/ROW]
[ROW][C]109[/C][C]8[/C][C]10.1173[/C][C]-2.1173[/C][/ROW]
[ROW][C]110[/C][C]2.5[/C][C]0.345097[/C][C]2.1549[/C][/ROW]
[ROW][C]111[/C][C]7[/C][C]11.9902[/C][C]-4.99022[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]4.07447[/C][C]-4.07447[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]2.22453[/C][C]-1.22453[/C][/ROW]
[ROW][C]114[/C][C]3.5[/C][C]2.78937[/C][C]0.710628[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]4.68431[/C][C]0.815685[/C][/ROW]
[ROW][C]116[/C][C]5.5[/C][C]9.91132[/C][C]-4.41132[/C][/ROW]
[ROW][C]117[/C][C]0.5[/C][C]-0.43485[/C][C]0.93485[/C][/ROW]
[ROW][C]118[/C][C]7.5[/C][C]5.48549[/C][C]2.01451[/C][/ROW]
[ROW][C]119[/C][C]9[/C][C]6.65591[/C][C]2.34409[/C][/ROW]
[ROW][C]120[/C][C]9.5[/C][C]9.03569[/C][C]0.464308[/C][/ROW]
[ROW][C]121[/C][C]8.5[/C][C]6.27061[/C][C]2.22939[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]10.2607[/C][C]-3.26068[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]5.24875[/C][C]2.75125[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]12.0203[/C][C]-2.02032[/C][/ROW]
[ROW][C]125[/C][C]7[/C][C]3.69501[/C][C]3.30499[/C][/ROW]
[ROW][C]126[/C][C]8.5[/C][C]8.35073[/C][C]0.149275[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]5.20206[/C][C]3.79794[/C][/ROW]
[ROW][C]128[/C][C]9.5[/C][C]12.9413[/C][C]-3.44131[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]4.74428[/C][C]-0.744276[/C][/ROW]
[ROW][C]130[/C][C]6[/C][C]5.33287[/C][C]0.667127[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]11.4665[/C][C]-3.46653[/C][/ROW]
[ROW][C]132[/C][C]5.5[/C][C]3.586[/C][C]1.914[/C][/ROW]
[ROW][C]133[/C][C]9.5[/C][C]7.89861[/C][C]1.60139[/C][/ROW]
[ROW][C]134[/C][C]7.5[/C][C]5.99164[/C][C]1.50836[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]8.26558[/C][C]-1.26558[/C][/ROW]
[ROW][C]136[/C][C]7.5[/C][C]5.97814[/C][C]1.52186[/C][/ROW]
[ROW][C]137[/C][C]8[/C][C]7.92828[/C][C]0.0717225[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]6.15771[/C][C]0.842287[/C][/ROW]
[ROW][C]139[/C][C]7[/C][C]8.57718[/C][C]-1.57718[/C][/ROW]
[ROW][C]140[/C][C]6[/C][C]2.67855[/C][C]3.32145[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.9464[/C][C]-3.94641[/C][/ROW]
[ROW][C]142[/C][C]2.5[/C][C]2.31288[/C][C]0.187115[/C][/ROW]
[ROW][C]143[/C][C]9[/C][C]10.355[/C][C]-1.35496[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]7.46471[/C][C]0.535289[/C][/ROW]
[ROW][C]145[/C][C]6[/C][C]2.59447[/C][C]3.40553[/C][/ROW]
[ROW][C]146[/C][C]8.5[/C][C]8.62822[/C][C]-0.128224[/C][/ROW]
[ROW][C]147[/C][C]6[/C][C]5.17097[/C][C]0.829029[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]7.46642[/C][C]1.53358[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]7.13571[/C][C]0.864294[/C][/ROW]
[ROW][C]150[/C][C]8[/C][C]6.09538[/C][C]1.90462[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]9.57616[/C][C]-0.576156[/C][/ROW]
[ROW][C]152[/C][C]5.5[/C][C]6.0058[/C][C]-0.505801[/C][/ROW]
[ROW][C]153[/C][C]5[/C][C]4.52458[/C][C]0.475416[/C][/ROW]
[ROW][C]154[/C][C]7[/C][C]10.6068[/C][C]-3.60682[/C][/ROW]
[ROW][C]155[/C][C]5.5[/C][C]4.27338[/C][C]1.22662[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]14.0929[/C][C]-5.0929[/C][/ROW]
[ROW][C]157[/C][C]2[/C][C]0.287801[/C][C]1.7122[/C][/ROW]
[ROW][C]158[/C][C]8.5[/C][C]6.99253[/C][C]1.50747[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.9611[/C][C]0.0389016[/C][/ROW]
[ROW][C]160[/C][C]8.5[/C][C]5.87461[/C][C]2.62539[/C][/ROW]
[ROW][C]161[/C][C]9[/C][C]8.48534[/C][C]0.51466[/C][/ROW]
[ROW][C]162[/C][C]7.5[/C][C]5.21618[/C][C]2.28382[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]8.21087[/C][C]1.78913[/C][/ROW]
[ROW][C]164[/C][C]9[/C][C]10.4326[/C][C]-1.43264[/C][/ROW]
[ROW][C]165[/C][C]7.5[/C][C]7.59321[/C][C]-0.0932147[/C][/ROW]
[ROW][C]166[/C][C]6[/C][C]1.51087[/C][C]4.48913[/C][/ROW]
[ROW][C]167[/C][C]10.5[/C][C]11.3663[/C][C]-0.866257[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]6.79693[/C][C]1.70307[/C][/ROW]
[ROW][C]169[/C][C]8[/C][C]3.97236[/C][C]4.02764[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]6.17121[/C][C]3.82879[/C][/ROW]
[ROW][C]171[/C][C]10.5[/C][C]9.04545[/C][C]1.45455[/C][/ROW]
[ROW][C]172[/C][C]6.5[/C][C]4.86115[/C][C]1.63885[/C][/ROW]
[ROW][C]173[/C][C]9.5[/C][C]5.77709[/C][C]3.72291[/C][/ROW]
[ROW][C]174[/C][C]8.5[/C][C]8.88215[/C][C]-0.382151[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]9.68125[/C][C]-2.18125[/C][/ROW]
[ROW][C]176[/C][C]5[/C][C]4.62101[/C][C]0.378994[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]4.30815[/C][C]3.69185[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.74787[/C][C]1.25213[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]7.23539[/C][C]-0.235385[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]7.73539[/C][C]-0.235385[/C][/ROW]
[ROW][C]181[/C][C]7.5[/C][C]4.55458[/C][C]2.94542[/C][/ROW]
[ROW][C]182[/C][C]9.5[/C][C]10.1424[/C][C]-0.642367[/C][/ROW]
[ROW][C]183[/C][C]6[/C][C]4.13498[/C][C]1.86502[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]8.86909[/C][C]1.13091[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]10.3044[/C][C]-3.3044[/C][/ROW]
[ROW][C]186[/C][C]3[/C][C]3.90705[/C][C]-0.907048[/C][/ROW]
[ROW][C]187[/C][C]6[/C][C]5.43986[/C][C]0.56014[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]5.45649[/C][C]1.54351[/C][/ROW]
[ROW][C]189[/C][C]10[/C][C]9.81248[/C][C]0.187515[/C][/ROW]
[ROW][C]190[/C][C]7[/C][C]8.79305[/C][C]-1.79305[/C][/ROW]
[ROW][C]191[/C][C]3.5[/C][C]2.21108[/C][C]1.28892[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]3.76892[/C][C]4.23108[/C][/ROW]
[ROW][C]193[/C][C]10[/C][C]10.214[/C][C]-0.214014[/C][/ROW]
[ROW][C]194[/C][C]5.5[/C][C]3.56663[/C][C]1.93337[/C][/ROW]
[ROW][C]195[/C][C]6[/C][C]5.96258[/C][C]0.0374179[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]5.74323[/C][C]0.756772[/C][/ROW]
[ROW][C]197[/C][C]6.5[/C][C]4.03927[/C][C]2.46073[/C][/ROW]
[ROW][C]198[/C][C]8.5[/C][C]9.83615[/C][C]-1.33615[/C][/ROW]
[ROW][C]199[/C][C]4[/C][C]0.839168[/C][C]3.16083[/C][/ROW]
[ROW][C]200[/C][C]9.5[/C][C]7.48102[/C][C]2.01898[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]7.08632[/C][C]0.913682[/C][/ROW]
[ROW][C]202[/C][C]8.5[/C][C]11.391[/C][C]-2.89103[/C][/ROW]
[ROW][C]203[/C][C]5.5[/C][C]5.4889[/C][C]0.0111026[/C][/ROW]
[ROW][C]204[/C][C]7[/C][C]3.37709[/C][C]3.62291[/C][/ROW]
[ROW][C]205[/C][C]9[/C][C]7.013[/C][C]1.987[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]5.958[/C][C]2.042[/C][/ROW]
[ROW][C]207[/C][C]10[/C][C]8.01784[/C][C]1.98216[/C][/ROW]
[ROW][C]208[/C][C]8[/C][C]8.12426[/C][C]-0.124265[/C][/ROW]
[ROW][C]209[/C][C]6[/C][C]5.59741[/C][C]0.402593[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]8.59154[/C][C]-0.591543[/C][/ROW]
[ROW][C]211[/C][C]5[/C][C]1.40179[/C][C]3.59821[/C][/ROW]
[ROW][C]212[/C][C]9[/C][C]11.5627[/C][C]-2.56271[/C][/ROW]
[ROW][C]213[/C][C]4.5[/C][C]1.57818[/C][C]2.92182[/C][/ROW]
[ROW][C]214[/C][C]8.5[/C][C]7.65632[/C][C]0.843685[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]5.77096[/C][C]1.22904[/C][/ROW]
[ROW][C]216[/C][C]9.5[/C][C]8.04086[/C][C]1.45914[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]5.91621[/C][C]2.58379[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]5.88429[/C][C]1.61571[/C][/ROW]
[ROW][C]219[/C][C]7.5[/C][C]10.0882[/C][C]-2.58824[/C][/ROW]
[ROW][C]220[/C][C]5[/C][C]6.43181[/C][C]-1.43181[/C][/ROW]
[ROW][C]221[/C][C]7[/C][C]7.49251[/C][C]-0.49251[/C][/ROW]
[ROW][C]222[/C][C]8[/C][C]9.02239[/C][C]-1.02239[/C][/ROW]
[ROW][C]223[/C][C]5.5[/C][C]3.26879[/C][C]2.23121[/C][/ROW]
[ROW][C]224[/C][C]8.5[/C][C]7.14642[/C][C]1.35358[/C][/ROW]
[ROW][C]225[/C][C]7.5[/C][C]4.93124[/C][C]2.56876[/C][/ROW]
[ROW][C]226[/C][C]9.5[/C][C]8.22013[/C][C]1.27987[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]6.7717[/C][C]0.228299[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]7.44914[/C][C]0.55086[/C][/ROW]
[ROW][C]229[/C][C]8.5[/C][C]11.5338[/C][C]-3.03383[/C][/ROW]
[ROW][C]230[/C][C]3.5[/C][C]2.52344[/C][C]0.976561[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]5.14565[/C][C]1.35435[/C][/ROW]
[ROW][C]232[/C][C]6.5[/C][C]3.81701[/C][C]2.68299[/C][/ROW]
[ROW][C]233[/C][C]10.5[/C][C]7.97389[/C][C]2.52611[/C][/ROW]
[ROW][C]234[/C][C]8.5[/C][C]6.82683[/C][C]1.67317[/C][/ROW]
[ROW][C]235[/C][C]8[/C][C]4.10593[/C][C]3.89407[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]7.40902[/C][C]2.59098[/C][/ROW]
[ROW][C]237[/C][C]10[/C][C]7.7695[/C][C]2.2305[/C][/ROW]
[ROW][C]238[/C][C]9.5[/C][C]6.26647[/C][C]3.23353[/C][/ROW]
[ROW][C]239[/C][C]9[/C][C]7.39798[/C][C]1.60202[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]8.14684[/C][C]1.85316[/C][/ROW]
[ROW][C]241[/C][C]7.5[/C][C]8.77359[/C][C]-1.27359[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]5.5002[/C][C]-1.0002[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]9.66748[/C][C]-5.16748[/C][/ROW]
[ROW][C]244[/C][C]0.5[/C][C]-0.715752[/C][C]1.21575[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]9.63956[/C][C]-3.13956[/C][/ROW]
[ROW][C]246[/C][C]4.5[/C][C]5.89788[/C][C]-1.39788[/C][/ROW]
[ROW][C]247[/C][C]5.5[/C][C]5.92343[/C][C]-0.423432[/C][/ROW]
[ROW][C]248[/C][C]5[/C][C]6.46249[/C][C]-1.46249[/C][/ROW]
[ROW][C]249[/C][C]6[/C][C]9.244[/C][C]-3.244[/C][/ROW]
[ROW][C]250[/C][C]4[/C][C]1.36358[/C][C]2.63642[/C][/ROW]
[ROW][C]251[/C][C]8[/C][C]4.17121[/C][C]3.82879[/C][/ROW]
[ROW][C]252[/C][C]10.5[/C][C]7.39775[/C][C]3.10225[/C][/ROW]
[ROW][C]253[/C][C]8.5[/C][C]7.60114[/C][C]0.898857[/C][/ROW]
[ROW][C]254[/C][C]6.5[/C][C]6.26095[/C][C]0.239049[/C][/ROW]
[ROW][C]255[/C][C]8[/C][C]7.20575[/C][C]0.794247[/C][/ROW]
[ROW][C]256[/C][C]8.5[/C][C]8.70626[/C][C]-0.206259[/C][/ROW]
[ROW][C]257[/C][C]5.5[/C][C]6.10555[/C][C]-0.605549[/C][/ROW]
[ROW][C]258[/C][C]7[/C][C]8.17034[/C][C]-1.17034[/C][/ROW]
[ROW][C]259[/C][C]5[/C][C]7.02746[/C][C]-2.02746[/C][/ROW]
[ROW][C]260[/C][C]3.5[/C][C]5.84408[/C][C]-2.34408[/C][/ROW]
[ROW][C]261[/C][C]5[/C][C]3.44513[/C][C]1.55487[/C][/ROW]
[ROW][C]262[/C][C]9[/C][C]7.07223[/C][C]1.92777[/C][/ROW]
[ROW][C]263[/C][C]8.5[/C][C]9.66585[/C][C]-1.16585[/C][/ROW]
[ROW][C]264[/C][C]5[/C][C]3.2219[/C][C]1.7781[/C][/ROW]
[ROW][C]265[/C][C]9.5[/C][C]11.3303[/C][C]-1.83026[/C][/ROW]
[ROW][C]266[/C][C]3[/C][C]8.98172[/C][C]-5.98172[/C][/ROW]
[ROW][C]267[/C][C]1.5[/C][C]0.686002[/C][C]0.813998[/C][/ROW]
[ROW][C]268[/C][C]6[/C][C]10.7296[/C][C]-4.7296[/C][/ROW]
[ROW][C]269[/C][C]0.5[/C][C]-0.954551[/C][C]1.45455[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]4.7845[/C][C]1.7155[/C][/ROW]
[ROW][C]271[/C][C]7.5[/C][C]8.9597[/C][C]-1.4597[/C][/ROW]
[ROW][C]272[/C][C]4.5[/C][C]1.86358[/C][C]2.63642[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]6.34368[/C][C]1.65632[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]8.20675[/C][C]0.79325[/C][/ROW]
[ROW][C]275[/C][C]7.5[/C][C]5.83669[/C][C]1.66331[/C][/ROW]
[ROW][C]276[/C][C]8.5[/C][C]6.69405[/C][C]1.80595[/C][/ROW]
[ROW][C]277[/C][C]7[/C][C]3.20595[/C][C]3.79405[/C][/ROW]
[ROW][C]278[/C][C]9.5[/C][C]8.05931[/C][C]1.44069[/C][/ROW]
[ROW][C]279[/C][C]6.5[/C][C]2.28281[/C][C]4.21719[/C][/ROW]
[ROW][C]280[/C][C]9.5[/C][C]8.85587[/C][C]0.644125[/C][/ROW]
[ROW][C]281[/C][C]6[/C][C]5.07847[/C][C]0.921526[/C][/ROW]
[ROW][C]282[/C][C]8[/C][C]6.91789[/C][C]1.08211[/C][/ROW]
[ROW][C]283[/C][C]9.5[/C][C]7.59217[/C][C]1.90783[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.34669[/C][C]1.65331[/C][/ROW]
[ROW][C]285[/C][C]8[/C][C]6.241[/C][C]1.759[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]9.60493[/C][C]-0.604929[/C][/ROW]
[ROW][C]287[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266351&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266351&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.221222.27878
22.54.93865-2.43865
364.980891.01911
46.55.325711.17429
515.54167-4.54167
615.03695-4.03695
75.56.53567-1.03567
88.55.54832.9517
96.55.697960.80204
104.55.33764-0.837639
1126.47299-4.47299
1255.67322-0.673222
130.56.74955-6.24955
1455.22204-0.222041
1555.84284-0.842843
162.54.73695-2.23695
1755.35572-0.355717
185.56.17778-0.67778
193.55.53441-2.03441
2035.47848-2.47848
2145.24568-1.24568
220.55.03594-4.53594
236.55.549550.950453
244.55.38427-0.88427
257.54.938032.56197
265.55.58803-0.0880259
2746.25486-2.25486
287.55.798541.70146
2975.219851.78015
3044.72658-0.726582
315.55.350750.149253
322.55.69132-3.19132
335.56.03464-0.534637
340.55.14911-4.64911
353.55.61522-2.11522
362.56.42337-3.92337
374.55.94429-1.44429
384.56.16301-1.66301
394.55.08718-0.58718
4065.812760.187236
412.55.07035-2.57035
4256.58774-1.58774
4304.72078-4.72078
4456.42338-1.42338
456.54.88541.6146
4655.51997-0.519972
4765.098930.90107
484.55.69494-1.19494
495.55.92127-0.421266
5015.10355-4.10355
517.54.472173.02783
5265.102290.89771
5355.54504-0.545044
5415.68677-4.68677
5556.04336-1.04336
566.55.639190.860812
5776.368720.631278
584.56.45189-1.95189
5905.27645-5.27645
608.55.454643.04536
613.54.6757-1.1757
627.55.584021.91598
633.55.52699-2.02699
6464.848211.15179
651.54.96775-3.46775
6695.860413.13959
673.54.50419-1.00419
683.55.10542-1.60542
6946.1159-2.1159
706.55.632150.867855
717.55.330032.16997
7265.031270.968735
7355.73938-0.739383
745.55.037370.462632
753.55.49779-1.99779
767.55.010092.48991
7715.28261-4.28261
786.55.946330.553669
79NANA0.367079
806.55.129741.37026
816.56.360440.139563
8278.93379-1.93379
833.57.24217-3.74217
841.52.33569-0.835695
8541.192482.80752
867.58.70875-1.20875
874.59.06487-4.56487
8801.29144-1.29144
893.53.334020.165984
905.55.445420.0545751
9155.63671-0.636713
924.56.57835-2.07835
932.5-0.2102152.71022
947.55.443992.05601
95712.0508-5.05084
9600.475207-0.475207
974.57.23348-2.73348
9837.05602-4.05602
991.52.54742-1.04742
1003.56.64493-3.14493
1012.52.105310.394693
1025.52.935672.56433
103811.678-3.67797
10411.35712-0.357122
10555.99401-0.994008
1064.56.27291-1.77291
10734.71668-1.71668
10830.5665432.43346
109810.1173-2.1173
1102.50.3450972.1549
111711.9902-4.99022
11204.07447-4.07447
11312.22453-1.22453
1143.52.789370.710628
1155.54.684310.815685
1165.59.91132-4.41132
1170.5-0.434850.93485
1187.55.485492.01451
11996.655912.34409
1209.59.035690.464308
1218.56.270612.22939
122710.2607-3.26068
12385.248752.75125
1241012.0203-2.02032
12573.695013.30499
1268.58.350730.149275
12795.202063.79794
1289.512.9413-3.44131
12944.74428-0.744276
13065.332870.667127
131811.4665-3.46653
1325.53.5861.914
1339.57.898611.60139
1347.55.991641.50836
13578.26558-1.26558
1367.55.978141.52186
13787.928280.0717225
13876.157710.842287
13978.57718-1.57718
14062.678553.32145
1411013.9464-3.94641
1422.52.312880.187115
143910.355-1.35496
14487.464710.535289
14562.594473.40553
1468.58.62822-0.128224
14765.170970.829029
14897.466421.53358
14987.135710.864294
15086.095381.90462
15199.57616-0.576156
1525.56.0058-0.505801
15354.524580.475416
154710.6068-3.60682
1555.54.273381.22662
156914.0929-5.0929
15720.2878011.7122
1588.56.992531.50747
15998.96110.0389016
1608.55.874612.62539
16198.485340.51466
1627.55.216182.28382
163108.210871.78913
164910.4326-1.43264
1657.57.59321-0.0932147
16661.510874.48913
16710.511.3663-0.866257
1688.56.796931.70307
16983.972364.02764
170106.171213.82879
17110.59.045451.45455
1726.54.861151.63885
1739.55.777093.72291
1748.58.88215-0.382151
1757.59.68125-2.18125
17654.621010.378994
17784.308153.69185
178108.747871.25213
17977.23539-0.235385
1807.57.73539-0.235385
1817.54.554582.94542
1829.510.1424-0.642367
18364.134981.86502
184108.869091.13091
185710.3044-3.3044
18633.90705-0.907048
18765.439860.56014
18875.456491.54351
189109.812480.187515
19078.79305-1.79305
1913.52.211081.28892
19283.768924.23108
1931010.214-0.214014
1945.53.566631.93337
19565.962580.0374179
1966.55.743230.756772
1976.54.039272.46073
1988.59.83615-1.33615
19940.8391683.16083
2009.57.481022.01898
20187.086320.913682
2028.511.391-2.89103
2035.55.48890.0111026
20473.377093.62291
20597.0131.987
20685.9582.042
207108.017841.98216
20888.12426-0.124265
20965.597410.402593
21088.59154-0.591543
21151.401793.59821
212911.5627-2.56271
2134.51.578182.92182
2148.57.656320.843685
21575.770961.22904
2169.58.040861.45914
2178.55.916212.58379
2187.55.884291.61571
2197.510.0882-2.58824
22056.43181-1.43181
22177.49251-0.49251
22289.02239-1.02239
2235.53.268792.23121
2248.57.146421.35358
2257.54.931242.56876
2269.58.220131.27987
22776.77170.228299
22887.449140.55086
2298.511.5338-3.03383
2303.52.523440.976561
2316.55.145651.35435
2326.53.817012.68299
23310.57.973892.52611
2348.56.826831.67317
23584.105933.89407
236107.409022.59098
237107.76952.2305
2389.56.266473.23353
23997.397981.60202
240108.146841.85316
2417.58.77359-1.27359
2424.55.5002-1.0002
2434.59.66748-5.16748
2440.5-0.7157521.21575
2456.59.63956-3.13956
2464.55.89788-1.39788
2475.55.92343-0.423432
24856.46249-1.46249
24969.244-3.244
25041.363582.63642
25184.171213.82879
25210.57.397753.10225
2538.57.601140.898857
2546.56.260950.239049
25587.205750.794247
2568.58.70626-0.206259
2575.56.10555-0.605549
25878.17034-1.17034
25957.02746-2.02746
2603.55.84408-2.34408
26153.445131.55487
26297.072231.92777
2638.59.66585-1.16585
26453.22191.7781
2659.511.3303-1.83026
26638.98172-5.98172
2671.50.6860020.813998
268610.7296-4.7296
2690.5-0.9545511.45455
2706.54.78451.7155
2717.58.9597-1.4597
2724.51.863582.63642
27386.343681.65632
27498.206750.79325
2757.55.836691.66331
2768.56.694051.80595
27773.205953.79405
2789.58.059311.44069
2796.52.282814.21719
2809.58.855870.644125
28165.078470.921526
28286.917891.08211
2839.57.592171.90783
28486.346691.65331
28586.2411.759
28699.60493-0.604929
2875NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9767620.0464750.0232375
90.9529890.09402180.0470109
100.9320360.1359280.0679642
110.9427510.1144970.0572485
120.9074970.1850050.0925026
130.9290760.1418470.0709235
140.90010.19980.0999
150.8569570.2860850.143043
160.8098140.3803720.190186
170.7817280.4365450.218272
180.7344630.5310740.265537
190.6704090.6591810.329591
200.622170.755660.37783
210.5512630.8974740.448737
220.6248380.7503250.375162
230.5937170.8125660.406283
240.5290840.9418320.470916
250.4864350.972870.513565
260.4290880.8581750.570912
270.3765550.7531110.623445
280.3194360.6388710.680564
290.3630980.7261960.636902
300.3277640.6555270.672236
310.304450.60890.69555
320.2757330.5514670.724267
330.2758170.5516350.724183
340.3833790.7667590.616621
350.3367010.6734020.663299
360.3708990.7417980.629101
370.3288430.6576850.671157
380.2907980.5815960.709202
390.2512510.5025020.748749
400.2509940.5019880.749006
410.2972990.5945990.702701
420.2687340.5374670.731266
430.3929560.7859120.607044
440.3553210.7106420.644679
450.3362050.6724090.663795
460.3045320.6090630.695468
470.2951620.5903250.704838
480.2594190.5188390.740581
490.2307260.4614510.769274
500.321720.643440.67828
510.3663310.7326610.633669
520.361610.723220.63839
530.3258130.6516260.674187
540.3634110.7268210.636589
550.3420380.6840760.657962
560.3526510.7053030.647349
570.3635650.7271290.636435
580.3323910.6647810.667609
590.4554970.9109940.544503
600.547060.9058790.45294
610.5077040.9845910.492296
620.5366290.9267420.463371
630.5250470.9499060.474953
640.5058120.9883770.494188
650.541350.9173010.45865
660.6097420.7805160.390258
670.5848430.8303150.415157
680.5521170.8957650.447883
690.5411560.9176870.458844
700.5064790.9870420.493521
710.5147450.9705110.485255
720.4935630.9871270.506437
730.4613360.9226710.538664
740.4316180.8632360.568382
750.4047990.8095970.595201
760.4078580.8157150.592142
770.5265580.9468830.473442
780.5105450.9789090.489455
790.4874240.9748470.512576
800.4784640.9569290.521536
810.4674250.9348490.532575
820.4426590.8853180.557341
830.502750.99450.49725
840.471140.9422810.52886
850.5039290.9921410.496071
860.473170.9463410.52683
870.5821540.8356920.417846
880.5656340.8687320.434366
890.5342780.9314450.465722
900.5016490.9967020.498351
910.468730.9374590.53127
920.4665590.9331180.533441
930.4926080.9852160.507392
940.5091140.9817720.490886
950.6392550.721490.360745
960.6161390.7677210.383861
970.6113320.7773350.388668
980.6582230.6835540.341777
990.6405820.7188360.359418
1000.6649980.6700040.335002
1010.6471730.7056550.352827
1020.7012060.5975870.298794
1030.781730.4365390.21827
1040.7610620.4778760.238938
1050.7429030.5141930.257097
1060.7397930.5204140.260207
1070.753450.49310.24655
1080.7774730.4450550.222527
1090.7964110.4071770.203589
1100.8005590.3988830.199441
1110.9000840.1998320.0999161
1120.9312490.1375030.0687514
1130.9346760.1306480.065324
1140.9291590.1416830.0708414
1150.9232690.1534620.0767308
1160.9557310.08853830.0442691
1170.9570240.08595170.0429759
1180.9633120.0733760.036688
1190.9695510.06089760.0304488
1200.9640170.07196560.0359828
1210.9675820.06483610.0324181
1220.963380.073240.03662
1230.9676280.06474320.0323716
1240.9711520.05769650.0288483
1250.9809450.03810960.0190548
1260.9782270.04354680.0217734
1270.9889440.02211110.0110556
1280.9905010.0189990.00949949
1290.9883860.02322830.0116142
1300.9865920.0268160.013408
1310.9871860.02562790.012814
1320.9871380.02572480.0128624
1330.9864280.02714370.0135718
1340.9850870.02982630.0149132
1350.9832330.03353380.0167669
1360.9819160.03616820.0180841
1370.9783870.04322620.0216131
1380.9752270.04954530.0247726
1390.9711920.05761540.0288077
1400.9798130.04037440.0201872
1410.9849220.03015660.0150783
1420.9817790.03644140.0182207
1430.9780620.04387580.0219379
1440.9740570.05188610.0259431
1450.9779570.04408620.0220431
1460.9768640.04627110.0231355
1470.974250.05150030.0257502
1480.9719110.05617790.0280889
1490.9670890.0658220.032911
1500.9644840.07103290.0355164
1510.9601760.07964720.0398236
1520.9549090.09018220.0450911
1530.9474140.1051720.0525859
1540.9518520.09629620.0481481
1550.9467810.1064370.0532187
1560.9807530.03849490.0192474
1570.9786980.04260440.0213022
1580.9765490.0469020.023451
1590.9715340.05693120.0284656
1600.976310.04738010.0236901
1610.9716750.05664920.0283246
1620.9698150.06036910.0301845
1630.9685310.06293810.0314691
1640.9638310.07233750.0361688
1650.9573930.08521350.0426067
1660.9688590.06228120.0311406
1670.9632780.07344330.0367217
1680.9583030.08339350.0416967
1690.9808530.03829460.0191473
1700.9827980.03440350.0172018
1710.9802720.03945570.0197279
1720.9778310.04433860.0221693
1730.9832130.03357410.0167871
1740.9791350.04173040.0208652
1750.9797230.04055380.0202769
1760.9752770.04944540.0247227
1770.9797160.04056870.0202843
1780.9763640.04727210.023636
1790.9709060.05818770.0290938
1800.9644290.07114130.0355707
1810.9657710.06845750.0342288
1820.9619810.07603730.0380187
1830.9610340.07793290.0389664
1840.9547680.0904640.045232
1850.9612170.07756580.0387829
1860.9616560.07668720.0383436
1870.9539210.09215830.0460792
1880.9489060.1021890.0510944
1890.9392920.1214160.0607082
1900.9499670.1000660.0500328
1910.9412150.1175690.0587847
1920.9614010.07719820.0385991
1930.9569830.08603320.0430166
1940.9509260.09814850.0490742
1950.940680.1186390.0593197
1960.9298130.1403740.0701871
1970.9228520.1542970.0771484
1980.9188750.1622490.0811245
1990.9250510.1498990.0749493
2000.9196030.1607930.0803967
2010.9116140.1767720.0883858
2020.9220340.1559310.0779656
2030.9070190.1859620.0929808
2040.9226640.1546720.077336
2050.9122840.1754330.0877165
2060.9016210.1967580.0983792
2070.8983480.2033050.101652
2080.8857830.2284330.114217
2090.8678960.2642070.132104
2100.852570.2948590.14743
2110.8804350.2391290.119565
2120.875930.2481410.12407
2130.8910080.2179840.108992
2140.8755650.2488710.124435
2150.8557860.2884290.144214
2160.8363950.327210.163605
2170.8309740.3380520.169026
2180.8079640.3840720.192036
2190.8308780.3382440.169122
2200.8081250.3837490.191875
2210.7875490.4249030.212451
2220.7662110.4675780.233789
2230.7505860.4988270.249414
2240.7199390.5601210.280061
2250.7100760.5798490.289924
2260.6794660.6410680.320534
2270.6398820.7202360.360118
2280.6038020.7923960.396198
2290.6096920.7806160.390308
2300.572270.855460.42773
2310.535270.929460.46473
2320.5361810.9276390.463819
2330.5630170.8739660.436983
2340.5547820.8904350.445218
2350.632920.7341610.36708
2360.6019630.7960750.398037
2370.600650.7986990.39935
2380.6290630.7418740.370937
2390.5877650.824470.412235
2400.5675110.8649770.432489
2410.5450380.9099250.454962
2420.5071220.9857560.492878
2430.6768830.6462350.323117
2440.6459150.708170.354085
2450.6826830.6346340.317317
2460.6513390.6973220.348661
2470.6119310.7761370.388069
2480.5839510.8320980.416049
2490.6205120.7589760.379488
2500.6005540.7988910.399446
2510.5922980.8154050.407702
2520.6160660.7678680.383934
2530.5687070.8625850.431293
2540.51160.9767990.4884
2550.4548560.9097120.545144
2560.3976260.7952520.602374
2570.3609940.7219870.639006
2580.3178620.6357250.682138
2590.3116620.6233230.688338
2600.345870.6917390.65413
2610.295840.5916810.70416
2620.2463090.4926180.753691
2630.2876550.5753090.712345
2640.2508690.5017380.749131
2650.2671750.534350.732825
2660.8347150.3305710.165285
2670.8021310.3957370.197869
2680.9995860.0008284830.000414241
2690.9999941.26469e-056.32346e-06
2700.9999833.45214e-051.72607e-05
2710.9999794.28834e-052.14417e-05
2720.9999735.45368e-052.72684e-05
2730.9999230.0001534147.67071e-05
2740.999660.0006791510.000339575
2750.9992250.001549240.000774619
2760.996760.006479420.00323971
2770.9875260.02494870.0124743
2780.9663530.06729380.0336469
2790.9973710.005257880.00262894

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.976762 & 0.046475 & 0.0232375 \tabularnewline
9 & 0.952989 & 0.0940218 & 0.0470109 \tabularnewline
10 & 0.932036 & 0.135928 & 0.0679642 \tabularnewline
11 & 0.942751 & 0.114497 & 0.0572485 \tabularnewline
12 & 0.907497 & 0.185005 & 0.0925026 \tabularnewline
13 & 0.929076 & 0.141847 & 0.0709235 \tabularnewline
14 & 0.9001 & 0.1998 & 0.0999 \tabularnewline
15 & 0.856957 & 0.286085 & 0.143043 \tabularnewline
16 & 0.809814 & 0.380372 & 0.190186 \tabularnewline
17 & 0.781728 & 0.436545 & 0.218272 \tabularnewline
18 & 0.734463 & 0.531074 & 0.265537 \tabularnewline
19 & 0.670409 & 0.659181 & 0.329591 \tabularnewline
20 & 0.62217 & 0.75566 & 0.37783 \tabularnewline
21 & 0.551263 & 0.897474 & 0.448737 \tabularnewline
22 & 0.624838 & 0.750325 & 0.375162 \tabularnewline
23 & 0.593717 & 0.812566 & 0.406283 \tabularnewline
24 & 0.529084 & 0.941832 & 0.470916 \tabularnewline
25 & 0.486435 & 0.97287 & 0.513565 \tabularnewline
26 & 0.429088 & 0.858175 & 0.570912 \tabularnewline
27 & 0.376555 & 0.753111 & 0.623445 \tabularnewline
28 & 0.319436 & 0.638871 & 0.680564 \tabularnewline
29 & 0.363098 & 0.726196 & 0.636902 \tabularnewline
30 & 0.327764 & 0.655527 & 0.672236 \tabularnewline
31 & 0.30445 & 0.6089 & 0.69555 \tabularnewline
32 & 0.275733 & 0.551467 & 0.724267 \tabularnewline
33 & 0.275817 & 0.551635 & 0.724183 \tabularnewline
34 & 0.383379 & 0.766759 & 0.616621 \tabularnewline
35 & 0.336701 & 0.673402 & 0.663299 \tabularnewline
36 & 0.370899 & 0.741798 & 0.629101 \tabularnewline
37 & 0.328843 & 0.657685 & 0.671157 \tabularnewline
38 & 0.290798 & 0.581596 & 0.709202 \tabularnewline
39 & 0.251251 & 0.502502 & 0.748749 \tabularnewline
40 & 0.250994 & 0.501988 & 0.749006 \tabularnewline
41 & 0.297299 & 0.594599 & 0.702701 \tabularnewline
42 & 0.268734 & 0.537467 & 0.731266 \tabularnewline
43 & 0.392956 & 0.785912 & 0.607044 \tabularnewline
44 & 0.355321 & 0.710642 & 0.644679 \tabularnewline
45 & 0.336205 & 0.672409 & 0.663795 \tabularnewline
46 & 0.304532 & 0.609063 & 0.695468 \tabularnewline
47 & 0.295162 & 0.590325 & 0.704838 \tabularnewline
48 & 0.259419 & 0.518839 & 0.740581 \tabularnewline
49 & 0.230726 & 0.461451 & 0.769274 \tabularnewline
50 & 0.32172 & 0.64344 & 0.67828 \tabularnewline
51 & 0.366331 & 0.732661 & 0.633669 \tabularnewline
52 & 0.36161 & 0.72322 & 0.63839 \tabularnewline
53 & 0.325813 & 0.651626 & 0.674187 \tabularnewline
54 & 0.363411 & 0.726821 & 0.636589 \tabularnewline
55 & 0.342038 & 0.684076 & 0.657962 \tabularnewline
56 & 0.352651 & 0.705303 & 0.647349 \tabularnewline
57 & 0.363565 & 0.727129 & 0.636435 \tabularnewline
58 & 0.332391 & 0.664781 & 0.667609 \tabularnewline
59 & 0.455497 & 0.910994 & 0.544503 \tabularnewline
60 & 0.54706 & 0.905879 & 0.45294 \tabularnewline
61 & 0.507704 & 0.984591 & 0.492296 \tabularnewline
62 & 0.536629 & 0.926742 & 0.463371 \tabularnewline
63 & 0.525047 & 0.949906 & 0.474953 \tabularnewline
64 & 0.505812 & 0.988377 & 0.494188 \tabularnewline
65 & 0.54135 & 0.917301 & 0.45865 \tabularnewline
66 & 0.609742 & 0.780516 & 0.390258 \tabularnewline
67 & 0.584843 & 0.830315 & 0.415157 \tabularnewline
68 & 0.552117 & 0.895765 & 0.447883 \tabularnewline
69 & 0.541156 & 0.917687 & 0.458844 \tabularnewline
70 & 0.506479 & 0.987042 & 0.493521 \tabularnewline
71 & 0.514745 & 0.970511 & 0.485255 \tabularnewline
72 & 0.493563 & 0.987127 & 0.506437 \tabularnewline
73 & 0.461336 & 0.922671 & 0.538664 \tabularnewline
74 & 0.431618 & 0.863236 & 0.568382 \tabularnewline
75 & 0.404799 & 0.809597 & 0.595201 \tabularnewline
76 & 0.407858 & 0.815715 & 0.592142 \tabularnewline
77 & 0.526558 & 0.946883 & 0.473442 \tabularnewline
78 & 0.510545 & 0.978909 & 0.489455 \tabularnewline
79 & 0.487424 & 0.974847 & 0.512576 \tabularnewline
80 & 0.478464 & 0.956929 & 0.521536 \tabularnewline
81 & 0.467425 & 0.934849 & 0.532575 \tabularnewline
82 & 0.442659 & 0.885318 & 0.557341 \tabularnewline
83 & 0.50275 & 0.9945 & 0.49725 \tabularnewline
84 & 0.47114 & 0.942281 & 0.52886 \tabularnewline
85 & 0.503929 & 0.992141 & 0.496071 \tabularnewline
86 & 0.47317 & 0.946341 & 0.52683 \tabularnewline
87 & 0.582154 & 0.835692 & 0.417846 \tabularnewline
88 & 0.565634 & 0.868732 & 0.434366 \tabularnewline
89 & 0.534278 & 0.931445 & 0.465722 \tabularnewline
90 & 0.501649 & 0.996702 & 0.498351 \tabularnewline
91 & 0.46873 & 0.937459 & 0.53127 \tabularnewline
92 & 0.466559 & 0.933118 & 0.533441 \tabularnewline
93 & 0.492608 & 0.985216 & 0.507392 \tabularnewline
94 & 0.509114 & 0.981772 & 0.490886 \tabularnewline
95 & 0.639255 & 0.72149 & 0.360745 \tabularnewline
96 & 0.616139 & 0.767721 & 0.383861 \tabularnewline
97 & 0.611332 & 0.777335 & 0.388668 \tabularnewline
98 & 0.658223 & 0.683554 & 0.341777 \tabularnewline
99 & 0.640582 & 0.718836 & 0.359418 \tabularnewline
100 & 0.664998 & 0.670004 & 0.335002 \tabularnewline
101 & 0.647173 & 0.705655 & 0.352827 \tabularnewline
102 & 0.701206 & 0.597587 & 0.298794 \tabularnewline
103 & 0.78173 & 0.436539 & 0.21827 \tabularnewline
104 & 0.761062 & 0.477876 & 0.238938 \tabularnewline
105 & 0.742903 & 0.514193 & 0.257097 \tabularnewline
106 & 0.739793 & 0.520414 & 0.260207 \tabularnewline
107 & 0.75345 & 0.4931 & 0.24655 \tabularnewline
108 & 0.777473 & 0.445055 & 0.222527 \tabularnewline
109 & 0.796411 & 0.407177 & 0.203589 \tabularnewline
110 & 0.800559 & 0.398883 & 0.199441 \tabularnewline
111 & 0.900084 & 0.199832 & 0.0999161 \tabularnewline
112 & 0.931249 & 0.137503 & 0.0687514 \tabularnewline
113 & 0.934676 & 0.130648 & 0.065324 \tabularnewline
114 & 0.929159 & 0.141683 & 0.0708414 \tabularnewline
115 & 0.923269 & 0.153462 & 0.0767308 \tabularnewline
116 & 0.955731 & 0.0885383 & 0.0442691 \tabularnewline
117 & 0.957024 & 0.0859517 & 0.0429759 \tabularnewline
118 & 0.963312 & 0.073376 & 0.036688 \tabularnewline
119 & 0.969551 & 0.0608976 & 0.0304488 \tabularnewline
120 & 0.964017 & 0.0719656 & 0.0359828 \tabularnewline
121 & 0.967582 & 0.0648361 & 0.0324181 \tabularnewline
122 & 0.96338 & 0.07324 & 0.03662 \tabularnewline
123 & 0.967628 & 0.0647432 & 0.0323716 \tabularnewline
124 & 0.971152 & 0.0576965 & 0.0288483 \tabularnewline
125 & 0.980945 & 0.0381096 & 0.0190548 \tabularnewline
126 & 0.978227 & 0.0435468 & 0.0217734 \tabularnewline
127 & 0.988944 & 0.0221111 & 0.0110556 \tabularnewline
128 & 0.990501 & 0.018999 & 0.00949949 \tabularnewline
129 & 0.988386 & 0.0232283 & 0.0116142 \tabularnewline
130 & 0.986592 & 0.026816 & 0.013408 \tabularnewline
131 & 0.987186 & 0.0256279 & 0.012814 \tabularnewline
132 & 0.987138 & 0.0257248 & 0.0128624 \tabularnewline
133 & 0.986428 & 0.0271437 & 0.0135718 \tabularnewline
134 & 0.985087 & 0.0298263 & 0.0149132 \tabularnewline
135 & 0.983233 & 0.0335338 & 0.0167669 \tabularnewline
136 & 0.981916 & 0.0361682 & 0.0180841 \tabularnewline
137 & 0.978387 & 0.0432262 & 0.0216131 \tabularnewline
138 & 0.975227 & 0.0495453 & 0.0247726 \tabularnewline
139 & 0.971192 & 0.0576154 & 0.0288077 \tabularnewline
140 & 0.979813 & 0.0403744 & 0.0201872 \tabularnewline
141 & 0.984922 & 0.0301566 & 0.0150783 \tabularnewline
142 & 0.981779 & 0.0364414 & 0.0182207 \tabularnewline
143 & 0.978062 & 0.0438758 & 0.0219379 \tabularnewline
144 & 0.974057 & 0.0518861 & 0.0259431 \tabularnewline
145 & 0.977957 & 0.0440862 & 0.0220431 \tabularnewline
146 & 0.976864 & 0.0462711 & 0.0231355 \tabularnewline
147 & 0.97425 & 0.0515003 & 0.0257502 \tabularnewline
148 & 0.971911 & 0.0561779 & 0.0280889 \tabularnewline
149 & 0.967089 & 0.065822 & 0.032911 \tabularnewline
150 & 0.964484 & 0.0710329 & 0.0355164 \tabularnewline
151 & 0.960176 & 0.0796472 & 0.0398236 \tabularnewline
152 & 0.954909 & 0.0901822 & 0.0450911 \tabularnewline
153 & 0.947414 & 0.105172 & 0.0525859 \tabularnewline
154 & 0.951852 & 0.0962962 & 0.0481481 \tabularnewline
155 & 0.946781 & 0.106437 & 0.0532187 \tabularnewline
156 & 0.980753 & 0.0384949 & 0.0192474 \tabularnewline
157 & 0.978698 & 0.0426044 & 0.0213022 \tabularnewline
158 & 0.976549 & 0.046902 & 0.023451 \tabularnewline
159 & 0.971534 & 0.0569312 & 0.0284656 \tabularnewline
160 & 0.97631 & 0.0473801 & 0.0236901 \tabularnewline
161 & 0.971675 & 0.0566492 & 0.0283246 \tabularnewline
162 & 0.969815 & 0.0603691 & 0.0301845 \tabularnewline
163 & 0.968531 & 0.0629381 & 0.0314691 \tabularnewline
164 & 0.963831 & 0.0723375 & 0.0361688 \tabularnewline
165 & 0.957393 & 0.0852135 & 0.0426067 \tabularnewline
166 & 0.968859 & 0.0622812 & 0.0311406 \tabularnewline
167 & 0.963278 & 0.0734433 & 0.0367217 \tabularnewline
168 & 0.958303 & 0.0833935 & 0.0416967 \tabularnewline
169 & 0.980853 & 0.0382946 & 0.0191473 \tabularnewline
170 & 0.982798 & 0.0344035 & 0.0172018 \tabularnewline
171 & 0.980272 & 0.0394557 & 0.0197279 \tabularnewline
172 & 0.977831 & 0.0443386 & 0.0221693 \tabularnewline
173 & 0.983213 & 0.0335741 & 0.0167871 \tabularnewline
174 & 0.979135 & 0.0417304 & 0.0208652 \tabularnewline
175 & 0.979723 & 0.0405538 & 0.0202769 \tabularnewline
176 & 0.975277 & 0.0494454 & 0.0247227 \tabularnewline
177 & 0.979716 & 0.0405687 & 0.0202843 \tabularnewline
178 & 0.976364 & 0.0472721 & 0.023636 \tabularnewline
179 & 0.970906 & 0.0581877 & 0.0290938 \tabularnewline
180 & 0.964429 & 0.0711413 & 0.0355707 \tabularnewline
181 & 0.965771 & 0.0684575 & 0.0342288 \tabularnewline
182 & 0.961981 & 0.0760373 & 0.0380187 \tabularnewline
183 & 0.961034 & 0.0779329 & 0.0389664 \tabularnewline
184 & 0.954768 & 0.090464 & 0.045232 \tabularnewline
185 & 0.961217 & 0.0775658 & 0.0387829 \tabularnewline
186 & 0.961656 & 0.0766872 & 0.0383436 \tabularnewline
187 & 0.953921 & 0.0921583 & 0.0460792 \tabularnewline
188 & 0.948906 & 0.102189 & 0.0510944 \tabularnewline
189 & 0.939292 & 0.121416 & 0.0607082 \tabularnewline
190 & 0.949967 & 0.100066 & 0.0500328 \tabularnewline
191 & 0.941215 & 0.117569 & 0.0587847 \tabularnewline
192 & 0.961401 & 0.0771982 & 0.0385991 \tabularnewline
193 & 0.956983 & 0.0860332 & 0.0430166 \tabularnewline
194 & 0.950926 & 0.0981485 & 0.0490742 \tabularnewline
195 & 0.94068 & 0.118639 & 0.0593197 \tabularnewline
196 & 0.929813 & 0.140374 & 0.0701871 \tabularnewline
197 & 0.922852 & 0.154297 & 0.0771484 \tabularnewline
198 & 0.918875 & 0.162249 & 0.0811245 \tabularnewline
199 & 0.925051 & 0.149899 & 0.0749493 \tabularnewline
200 & 0.919603 & 0.160793 & 0.0803967 \tabularnewline
201 & 0.911614 & 0.176772 & 0.0883858 \tabularnewline
202 & 0.922034 & 0.155931 & 0.0779656 \tabularnewline
203 & 0.907019 & 0.185962 & 0.0929808 \tabularnewline
204 & 0.922664 & 0.154672 & 0.077336 \tabularnewline
205 & 0.912284 & 0.175433 & 0.0877165 \tabularnewline
206 & 0.901621 & 0.196758 & 0.0983792 \tabularnewline
207 & 0.898348 & 0.203305 & 0.101652 \tabularnewline
208 & 0.885783 & 0.228433 & 0.114217 \tabularnewline
209 & 0.867896 & 0.264207 & 0.132104 \tabularnewline
210 & 0.85257 & 0.294859 & 0.14743 \tabularnewline
211 & 0.880435 & 0.239129 & 0.119565 \tabularnewline
212 & 0.87593 & 0.248141 & 0.12407 \tabularnewline
213 & 0.891008 & 0.217984 & 0.108992 \tabularnewline
214 & 0.875565 & 0.248871 & 0.124435 \tabularnewline
215 & 0.855786 & 0.288429 & 0.144214 \tabularnewline
216 & 0.836395 & 0.32721 & 0.163605 \tabularnewline
217 & 0.830974 & 0.338052 & 0.169026 \tabularnewline
218 & 0.807964 & 0.384072 & 0.192036 \tabularnewline
219 & 0.830878 & 0.338244 & 0.169122 \tabularnewline
220 & 0.808125 & 0.383749 & 0.191875 \tabularnewline
221 & 0.787549 & 0.424903 & 0.212451 \tabularnewline
222 & 0.766211 & 0.467578 & 0.233789 \tabularnewline
223 & 0.750586 & 0.498827 & 0.249414 \tabularnewline
224 & 0.719939 & 0.560121 & 0.280061 \tabularnewline
225 & 0.710076 & 0.579849 & 0.289924 \tabularnewline
226 & 0.679466 & 0.641068 & 0.320534 \tabularnewline
227 & 0.639882 & 0.720236 & 0.360118 \tabularnewline
228 & 0.603802 & 0.792396 & 0.396198 \tabularnewline
229 & 0.609692 & 0.780616 & 0.390308 \tabularnewline
230 & 0.57227 & 0.85546 & 0.42773 \tabularnewline
231 & 0.53527 & 0.92946 & 0.46473 \tabularnewline
232 & 0.536181 & 0.927639 & 0.463819 \tabularnewline
233 & 0.563017 & 0.873966 & 0.436983 \tabularnewline
234 & 0.554782 & 0.890435 & 0.445218 \tabularnewline
235 & 0.63292 & 0.734161 & 0.36708 \tabularnewline
236 & 0.601963 & 0.796075 & 0.398037 \tabularnewline
237 & 0.60065 & 0.798699 & 0.39935 \tabularnewline
238 & 0.629063 & 0.741874 & 0.370937 \tabularnewline
239 & 0.587765 & 0.82447 & 0.412235 \tabularnewline
240 & 0.567511 & 0.864977 & 0.432489 \tabularnewline
241 & 0.545038 & 0.909925 & 0.454962 \tabularnewline
242 & 0.507122 & 0.985756 & 0.492878 \tabularnewline
243 & 0.676883 & 0.646235 & 0.323117 \tabularnewline
244 & 0.645915 & 0.70817 & 0.354085 \tabularnewline
245 & 0.682683 & 0.634634 & 0.317317 \tabularnewline
246 & 0.651339 & 0.697322 & 0.348661 \tabularnewline
247 & 0.611931 & 0.776137 & 0.388069 \tabularnewline
248 & 0.583951 & 0.832098 & 0.416049 \tabularnewline
249 & 0.620512 & 0.758976 & 0.379488 \tabularnewline
250 & 0.600554 & 0.798891 & 0.399446 \tabularnewline
251 & 0.592298 & 0.815405 & 0.407702 \tabularnewline
252 & 0.616066 & 0.767868 & 0.383934 \tabularnewline
253 & 0.568707 & 0.862585 & 0.431293 \tabularnewline
254 & 0.5116 & 0.976799 & 0.4884 \tabularnewline
255 & 0.454856 & 0.909712 & 0.545144 \tabularnewline
256 & 0.397626 & 0.795252 & 0.602374 \tabularnewline
257 & 0.360994 & 0.721987 & 0.639006 \tabularnewline
258 & 0.317862 & 0.635725 & 0.682138 \tabularnewline
259 & 0.311662 & 0.623323 & 0.688338 \tabularnewline
260 & 0.34587 & 0.691739 & 0.65413 \tabularnewline
261 & 0.29584 & 0.591681 & 0.70416 \tabularnewline
262 & 0.246309 & 0.492618 & 0.753691 \tabularnewline
263 & 0.287655 & 0.575309 & 0.712345 \tabularnewline
264 & 0.250869 & 0.501738 & 0.749131 \tabularnewline
265 & 0.267175 & 0.53435 & 0.732825 \tabularnewline
266 & 0.834715 & 0.330571 & 0.165285 \tabularnewline
267 & 0.802131 & 0.395737 & 0.197869 \tabularnewline
268 & 0.999586 & 0.000828483 & 0.000414241 \tabularnewline
269 & 0.999994 & 1.26469e-05 & 6.32346e-06 \tabularnewline
270 & 0.999983 & 3.45214e-05 & 1.72607e-05 \tabularnewline
271 & 0.999979 & 4.28834e-05 & 2.14417e-05 \tabularnewline
272 & 0.999973 & 5.45368e-05 & 2.72684e-05 \tabularnewline
273 & 0.999923 & 0.000153414 & 7.67071e-05 \tabularnewline
274 & 0.99966 & 0.000679151 & 0.000339575 \tabularnewline
275 & 0.999225 & 0.00154924 & 0.000774619 \tabularnewline
276 & 0.99676 & 0.00647942 & 0.00323971 \tabularnewline
277 & 0.987526 & 0.0249487 & 0.0124743 \tabularnewline
278 & 0.966353 & 0.0672938 & 0.0336469 \tabularnewline
279 & 0.997371 & 0.00525788 & 0.00262894 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266351&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]8[/C][C]0.976762[/C][C]0.046475[/C][C]0.0232375[/C][/ROW]
[ROW][C]9[/C][C]0.952989[/C][C]0.0940218[/C][C]0.0470109[/C][/ROW]
[ROW][C]10[/C][C]0.932036[/C][C]0.135928[/C][C]0.0679642[/C][/ROW]
[ROW][C]11[/C][C]0.942751[/C][C]0.114497[/C][C]0.0572485[/C][/ROW]
[ROW][C]12[/C][C]0.907497[/C][C]0.185005[/C][C]0.0925026[/C][/ROW]
[ROW][C]13[/C][C]0.929076[/C][C]0.141847[/C][C]0.0709235[/C][/ROW]
[ROW][C]14[/C][C]0.9001[/C][C]0.1998[/C][C]0.0999[/C][/ROW]
[ROW][C]15[/C][C]0.856957[/C][C]0.286085[/C][C]0.143043[/C][/ROW]
[ROW][C]16[/C][C]0.809814[/C][C]0.380372[/C][C]0.190186[/C][/ROW]
[ROW][C]17[/C][C]0.781728[/C][C]0.436545[/C][C]0.218272[/C][/ROW]
[ROW][C]18[/C][C]0.734463[/C][C]0.531074[/C][C]0.265537[/C][/ROW]
[ROW][C]19[/C][C]0.670409[/C][C]0.659181[/C][C]0.329591[/C][/ROW]
[ROW][C]20[/C][C]0.62217[/C][C]0.75566[/C][C]0.37783[/C][/ROW]
[ROW][C]21[/C][C]0.551263[/C][C]0.897474[/C][C]0.448737[/C][/ROW]
[ROW][C]22[/C][C]0.624838[/C][C]0.750325[/C][C]0.375162[/C][/ROW]
[ROW][C]23[/C][C]0.593717[/C][C]0.812566[/C][C]0.406283[/C][/ROW]
[ROW][C]24[/C][C]0.529084[/C][C]0.941832[/C][C]0.470916[/C][/ROW]
[ROW][C]25[/C][C]0.486435[/C][C]0.97287[/C][C]0.513565[/C][/ROW]
[ROW][C]26[/C][C]0.429088[/C][C]0.858175[/C][C]0.570912[/C][/ROW]
[ROW][C]27[/C][C]0.376555[/C][C]0.753111[/C][C]0.623445[/C][/ROW]
[ROW][C]28[/C][C]0.319436[/C][C]0.638871[/C][C]0.680564[/C][/ROW]
[ROW][C]29[/C][C]0.363098[/C][C]0.726196[/C][C]0.636902[/C][/ROW]
[ROW][C]30[/C][C]0.327764[/C][C]0.655527[/C][C]0.672236[/C][/ROW]
[ROW][C]31[/C][C]0.30445[/C][C]0.6089[/C][C]0.69555[/C][/ROW]
[ROW][C]32[/C][C]0.275733[/C][C]0.551467[/C][C]0.724267[/C][/ROW]
[ROW][C]33[/C][C]0.275817[/C][C]0.551635[/C][C]0.724183[/C][/ROW]
[ROW][C]34[/C][C]0.383379[/C][C]0.766759[/C][C]0.616621[/C][/ROW]
[ROW][C]35[/C][C]0.336701[/C][C]0.673402[/C][C]0.663299[/C][/ROW]
[ROW][C]36[/C][C]0.370899[/C][C]0.741798[/C][C]0.629101[/C][/ROW]
[ROW][C]37[/C][C]0.328843[/C][C]0.657685[/C][C]0.671157[/C][/ROW]
[ROW][C]38[/C][C]0.290798[/C][C]0.581596[/C][C]0.709202[/C][/ROW]
[ROW][C]39[/C][C]0.251251[/C][C]0.502502[/C][C]0.748749[/C][/ROW]
[ROW][C]40[/C][C]0.250994[/C][C]0.501988[/C][C]0.749006[/C][/ROW]
[ROW][C]41[/C][C]0.297299[/C][C]0.594599[/C][C]0.702701[/C][/ROW]
[ROW][C]42[/C][C]0.268734[/C][C]0.537467[/C][C]0.731266[/C][/ROW]
[ROW][C]43[/C][C]0.392956[/C][C]0.785912[/C][C]0.607044[/C][/ROW]
[ROW][C]44[/C][C]0.355321[/C][C]0.710642[/C][C]0.644679[/C][/ROW]
[ROW][C]45[/C][C]0.336205[/C][C]0.672409[/C][C]0.663795[/C][/ROW]
[ROW][C]46[/C][C]0.304532[/C][C]0.609063[/C][C]0.695468[/C][/ROW]
[ROW][C]47[/C][C]0.295162[/C][C]0.590325[/C][C]0.704838[/C][/ROW]
[ROW][C]48[/C][C]0.259419[/C][C]0.518839[/C][C]0.740581[/C][/ROW]
[ROW][C]49[/C][C]0.230726[/C][C]0.461451[/C][C]0.769274[/C][/ROW]
[ROW][C]50[/C][C]0.32172[/C][C]0.64344[/C][C]0.67828[/C][/ROW]
[ROW][C]51[/C][C]0.366331[/C][C]0.732661[/C][C]0.633669[/C][/ROW]
[ROW][C]52[/C][C]0.36161[/C][C]0.72322[/C][C]0.63839[/C][/ROW]
[ROW][C]53[/C][C]0.325813[/C][C]0.651626[/C][C]0.674187[/C][/ROW]
[ROW][C]54[/C][C]0.363411[/C][C]0.726821[/C][C]0.636589[/C][/ROW]
[ROW][C]55[/C][C]0.342038[/C][C]0.684076[/C][C]0.657962[/C][/ROW]
[ROW][C]56[/C][C]0.352651[/C][C]0.705303[/C][C]0.647349[/C][/ROW]
[ROW][C]57[/C][C]0.363565[/C][C]0.727129[/C][C]0.636435[/C][/ROW]
[ROW][C]58[/C][C]0.332391[/C][C]0.664781[/C][C]0.667609[/C][/ROW]
[ROW][C]59[/C][C]0.455497[/C][C]0.910994[/C][C]0.544503[/C][/ROW]
[ROW][C]60[/C][C]0.54706[/C][C]0.905879[/C][C]0.45294[/C][/ROW]
[ROW][C]61[/C][C]0.507704[/C][C]0.984591[/C][C]0.492296[/C][/ROW]
[ROW][C]62[/C][C]0.536629[/C][C]0.926742[/C][C]0.463371[/C][/ROW]
[ROW][C]63[/C][C]0.525047[/C][C]0.949906[/C][C]0.474953[/C][/ROW]
[ROW][C]64[/C][C]0.505812[/C][C]0.988377[/C][C]0.494188[/C][/ROW]
[ROW][C]65[/C][C]0.54135[/C][C]0.917301[/C][C]0.45865[/C][/ROW]
[ROW][C]66[/C][C]0.609742[/C][C]0.780516[/C][C]0.390258[/C][/ROW]
[ROW][C]67[/C][C]0.584843[/C][C]0.830315[/C][C]0.415157[/C][/ROW]
[ROW][C]68[/C][C]0.552117[/C][C]0.895765[/C][C]0.447883[/C][/ROW]
[ROW][C]69[/C][C]0.541156[/C][C]0.917687[/C][C]0.458844[/C][/ROW]
[ROW][C]70[/C][C]0.506479[/C][C]0.987042[/C][C]0.493521[/C][/ROW]
[ROW][C]71[/C][C]0.514745[/C][C]0.970511[/C][C]0.485255[/C][/ROW]
[ROW][C]72[/C][C]0.493563[/C][C]0.987127[/C][C]0.506437[/C][/ROW]
[ROW][C]73[/C][C]0.461336[/C][C]0.922671[/C][C]0.538664[/C][/ROW]
[ROW][C]74[/C][C]0.431618[/C][C]0.863236[/C][C]0.568382[/C][/ROW]
[ROW][C]75[/C][C]0.404799[/C][C]0.809597[/C][C]0.595201[/C][/ROW]
[ROW][C]76[/C][C]0.407858[/C][C]0.815715[/C][C]0.592142[/C][/ROW]
[ROW][C]77[/C][C]0.526558[/C][C]0.946883[/C][C]0.473442[/C][/ROW]
[ROW][C]78[/C][C]0.510545[/C][C]0.978909[/C][C]0.489455[/C][/ROW]
[ROW][C]79[/C][C]0.487424[/C][C]0.974847[/C][C]0.512576[/C][/ROW]
[ROW][C]80[/C][C]0.478464[/C][C]0.956929[/C][C]0.521536[/C][/ROW]
[ROW][C]81[/C][C]0.467425[/C][C]0.934849[/C][C]0.532575[/C][/ROW]
[ROW][C]82[/C][C]0.442659[/C][C]0.885318[/C][C]0.557341[/C][/ROW]
[ROW][C]83[/C][C]0.50275[/C][C]0.9945[/C][C]0.49725[/C][/ROW]
[ROW][C]84[/C][C]0.47114[/C][C]0.942281[/C][C]0.52886[/C][/ROW]
[ROW][C]85[/C][C]0.503929[/C][C]0.992141[/C][C]0.496071[/C][/ROW]
[ROW][C]86[/C][C]0.47317[/C][C]0.946341[/C][C]0.52683[/C][/ROW]
[ROW][C]87[/C][C]0.582154[/C][C]0.835692[/C][C]0.417846[/C][/ROW]
[ROW][C]88[/C][C]0.565634[/C][C]0.868732[/C][C]0.434366[/C][/ROW]
[ROW][C]89[/C][C]0.534278[/C][C]0.931445[/C][C]0.465722[/C][/ROW]
[ROW][C]90[/C][C]0.501649[/C][C]0.996702[/C][C]0.498351[/C][/ROW]
[ROW][C]91[/C][C]0.46873[/C][C]0.937459[/C][C]0.53127[/C][/ROW]
[ROW][C]92[/C][C]0.466559[/C][C]0.933118[/C][C]0.533441[/C][/ROW]
[ROW][C]93[/C][C]0.492608[/C][C]0.985216[/C][C]0.507392[/C][/ROW]
[ROW][C]94[/C][C]0.509114[/C][C]0.981772[/C][C]0.490886[/C][/ROW]
[ROW][C]95[/C][C]0.639255[/C][C]0.72149[/C][C]0.360745[/C][/ROW]
[ROW][C]96[/C][C]0.616139[/C][C]0.767721[/C][C]0.383861[/C][/ROW]
[ROW][C]97[/C][C]0.611332[/C][C]0.777335[/C][C]0.388668[/C][/ROW]
[ROW][C]98[/C][C]0.658223[/C][C]0.683554[/C][C]0.341777[/C][/ROW]
[ROW][C]99[/C][C]0.640582[/C][C]0.718836[/C][C]0.359418[/C][/ROW]
[ROW][C]100[/C][C]0.664998[/C][C]0.670004[/C][C]0.335002[/C][/ROW]
[ROW][C]101[/C][C]0.647173[/C][C]0.705655[/C][C]0.352827[/C][/ROW]
[ROW][C]102[/C][C]0.701206[/C][C]0.597587[/C][C]0.298794[/C][/ROW]
[ROW][C]103[/C][C]0.78173[/C][C]0.436539[/C][C]0.21827[/C][/ROW]
[ROW][C]104[/C][C]0.761062[/C][C]0.477876[/C][C]0.238938[/C][/ROW]
[ROW][C]105[/C][C]0.742903[/C][C]0.514193[/C][C]0.257097[/C][/ROW]
[ROW][C]106[/C][C]0.739793[/C][C]0.520414[/C][C]0.260207[/C][/ROW]
[ROW][C]107[/C][C]0.75345[/C][C]0.4931[/C][C]0.24655[/C][/ROW]
[ROW][C]108[/C][C]0.777473[/C][C]0.445055[/C][C]0.222527[/C][/ROW]
[ROW][C]109[/C][C]0.796411[/C][C]0.407177[/C][C]0.203589[/C][/ROW]
[ROW][C]110[/C][C]0.800559[/C][C]0.398883[/C][C]0.199441[/C][/ROW]
[ROW][C]111[/C][C]0.900084[/C][C]0.199832[/C][C]0.0999161[/C][/ROW]
[ROW][C]112[/C][C]0.931249[/C][C]0.137503[/C][C]0.0687514[/C][/ROW]
[ROW][C]113[/C][C]0.934676[/C][C]0.130648[/C][C]0.065324[/C][/ROW]
[ROW][C]114[/C][C]0.929159[/C][C]0.141683[/C][C]0.0708414[/C][/ROW]
[ROW][C]115[/C][C]0.923269[/C][C]0.153462[/C][C]0.0767308[/C][/ROW]
[ROW][C]116[/C][C]0.955731[/C][C]0.0885383[/C][C]0.0442691[/C][/ROW]
[ROW][C]117[/C][C]0.957024[/C][C]0.0859517[/C][C]0.0429759[/C][/ROW]
[ROW][C]118[/C][C]0.963312[/C][C]0.073376[/C][C]0.036688[/C][/ROW]
[ROW][C]119[/C][C]0.969551[/C][C]0.0608976[/C][C]0.0304488[/C][/ROW]
[ROW][C]120[/C][C]0.964017[/C][C]0.0719656[/C][C]0.0359828[/C][/ROW]
[ROW][C]121[/C][C]0.967582[/C][C]0.0648361[/C][C]0.0324181[/C][/ROW]
[ROW][C]122[/C][C]0.96338[/C][C]0.07324[/C][C]0.03662[/C][/ROW]
[ROW][C]123[/C][C]0.967628[/C][C]0.0647432[/C][C]0.0323716[/C][/ROW]
[ROW][C]124[/C][C]0.971152[/C][C]0.0576965[/C][C]0.0288483[/C][/ROW]
[ROW][C]125[/C][C]0.980945[/C][C]0.0381096[/C][C]0.0190548[/C][/ROW]
[ROW][C]126[/C][C]0.978227[/C][C]0.0435468[/C][C]0.0217734[/C][/ROW]
[ROW][C]127[/C][C]0.988944[/C][C]0.0221111[/C][C]0.0110556[/C][/ROW]
[ROW][C]128[/C][C]0.990501[/C][C]0.018999[/C][C]0.00949949[/C][/ROW]
[ROW][C]129[/C][C]0.988386[/C][C]0.0232283[/C][C]0.0116142[/C][/ROW]
[ROW][C]130[/C][C]0.986592[/C][C]0.026816[/C][C]0.013408[/C][/ROW]
[ROW][C]131[/C][C]0.987186[/C][C]0.0256279[/C][C]0.012814[/C][/ROW]
[ROW][C]132[/C][C]0.987138[/C][C]0.0257248[/C][C]0.0128624[/C][/ROW]
[ROW][C]133[/C][C]0.986428[/C][C]0.0271437[/C][C]0.0135718[/C][/ROW]
[ROW][C]134[/C][C]0.985087[/C][C]0.0298263[/C][C]0.0149132[/C][/ROW]
[ROW][C]135[/C][C]0.983233[/C][C]0.0335338[/C][C]0.0167669[/C][/ROW]
[ROW][C]136[/C][C]0.981916[/C][C]0.0361682[/C][C]0.0180841[/C][/ROW]
[ROW][C]137[/C][C]0.978387[/C][C]0.0432262[/C][C]0.0216131[/C][/ROW]
[ROW][C]138[/C][C]0.975227[/C][C]0.0495453[/C][C]0.0247726[/C][/ROW]
[ROW][C]139[/C][C]0.971192[/C][C]0.0576154[/C][C]0.0288077[/C][/ROW]
[ROW][C]140[/C][C]0.979813[/C][C]0.0403744[/C][C]0.0201872[/C][/ROW]
[ROW][C]141[/C][C]0.984922[/C][C]0.0301566[/C][C]0.0150783[/C][/ROW]
[ROW][C]142[/C][C]0.981779[/C][C]0.0364414[/C][C]0.0182207[/C][/ROW]
[ROW][C]143[/C][C]0.978062[/C][C]0.0438758[/C][C]0.0219379[/C][/ROW]
[ROW][C]144[/C][C]0.974057[/C][C]0.0518861[/C][C]0.0259431[/C][/ROW]
[ROW][C]145[/C][C]0.977957[/C][C]0.0440862[/C][C]0.0220431[/C][/ROW]
[ROW][C]146[/C][C]0.976864[/C][C]0.0462711[/C][C]0.0231355[/C][/ROW]
[ROW][C]147[/C][C]0.97425[/C][C]0.0515003[/C][C]0.0257502[/C][/ROW]
[ROW][C]148[/C][C]0.971911[/C][C]0.0561779[/C][C]0.0280889[/C][/ROW]
[ROW][C]149[/C][C]0.967089[/C][C]0.065822[/C][C]0.032911[/C][/ROW]
[ROW][C]150[/C][C]0.964484[/C][C]0.0710329[/C][C]0.0355164[/C][/ROW]
[ROW][C]151[/C][C]0.960176[/C][C]0.0796472[/C][C]0.0398236[/C][/ROW]
[ROW][C]152[/C][C]0.954909[/C][C]0.0901822[/C][C]0.0450911[/C][/ROW]
[ROW][C]153[/C][C]0.947414[/C][C]0.105172[/C][C]0.0525859[/C][/ROW]
[ROW][C]154[/C][C]0.951852[/C][C]0.0962962[/C][C]0.0481481[/C][/ROW]
[ROW][C]155[/C][C]0.946781[/C][C]0.106437[/C][C]0.0532187[/C][/ROW]
[ROW][C]156[/C][C]0.980753[/C][C]0.0384949[/C][C]0.0192474[/C][/ROW]
[ROW][C]157[/C][C]0.978698[/C][C]0.0426044[/C][C]0.0213022[/C][/ROW]
[ROW][C]158[/C][C]0.976549[/C][C]0.046902[/C][C]0.023451[/C][/ROW]
[ROW][C]159[/C][C]0.971534[/C][C]0.0569312[/C][C]0.0284656[/C][/ROW]
[ROW][C]160[/C][C]0.97631[/C][C]0.0473801[/C][C]0.0236901[/C][/ROW]
[ROW][C]161[/C][C]0.971675[/C][C]0.0566492[/C][C]0.0283246[/C][/ROW]
[ROW][C]162[/C][C]0.969815[/C][C]0.0603691[/C][C]0.0301845[/C][/ROW]
[ROW][C]163[/C][C]0.968531[/C][C]0.0629381[/C][C]0.0314691[/C][/ROW]
[ROW][C]164[/C][C]0.963831[/C][C]0.0723375[/C][C]0.0361688[/C][/ROW]
[ROW][C]165[/C][C]0.957393[/C][C]0.0852135[/C][C]0.0426067[/C][/ROW]
[ROW][C]166[/C][C]0.968859[/C][C]0.0622812[/C][C]0.0311406[/C][/ROW]
[ROW][C]167[/C][C]0.963278[/C][C]0.0734433[/C][C]0.0367217[/C][/ROW]
[ROW][C]168[/C][C]0.958303[/C][C]0.0833935[/C][C]0.0416967[/C][/ROW]
[ROW][C]169[/C][C]0.980853[/C][C]0.0382946[/C][C]0.0191473[/C][/ROW]
[ROW][C]170[/C][C]0.982798[/C][C]0.0344035[/C][C]0.0172018[/C][/ROW]
[ROW][C]171[/C][C]0.980272[/C][C]0.0394557[/C][C]0.0197279[/C][/ROW]
[ROW][C]172[/C][C]0.977831[/C][C]0.0443386[/C][C]0.0221693[/C][/ROW]
[ROW][C]173[/C][C]0.983213[/C][C]0.0335741[/C][C]0.0167871[/C][/ROW]
[ROW][C]174[/C][C]0.979135[/C][C]0.0417304[/C][C]0.0208652[/C][/ROW]
[ROW][C]175[/C][C]0.979723[/C][C]0.0405538[/C][C]0.0202769[/C][/ROW]
[ROW][C]176[/C][C]0.975277[/C][C]0.0494454[/C][C]0.0247227[/C][/ROW]
[ROW][C]177[/C][C]0.979716[/C][C]0.0405687[/C][C]0.0202843[/C][/ROW]
[ROW][C]178[/C][C]0.976364[/C][C]0.0472721[/C][C]0.023636[/C][/ROW]
[ROW][C]179[/C][C]0.970906[/C][C]0.0581877[/C][C]0.0290938[/C][/ROW]
[ROW][C]180[/C][C]0.964429[/C][C]0.0711413[/C][C]0.0355707[/C][/ROW]
[ROW][C]181[/C][C]0.965771[/C][C]0.0684575[/C][C]0.0342288[/C][/ROW]
[ROW][C]182[/C][C]0.961981[/C][C]0.0760373[/C][C]0.0380187[/C][/ROW]
[ROW][C]183[/C][C]0.961034[/C][C]0.0779329[/C][C]0.0389664[/C][/ROW]
[ROW][C]184[/C][C]0.954768[/C][C]0.090464[/C][C]0.045232[/C][/ROW]
[ROW][C]185[/C][C]0.961217[/C][C]0.0775658[/C][C]0.0387829[/C][/ROW]
[ROW][C]186[/C][C]0.961656[/C][C]0.0766872[/C][C]0.0383436[/C][/ROW]
[ROW][C]187[/C][C]0.953921[/C][C]0.0921583[/C][C]0.0460792[/C][/ROW]
[ROW][C]188[/C][C]0.948906[/C][C]0.102189[/C][C]0.0510944[/C][/ROW]
[ROW][C]189[/C][C]0.939292[/C][C]0.121416[/C][C]0.0607082[/C][/ROW]
[ROW][C]190[/C][C]0.949967[/C][C]0.100066[/C][C]0.0500328[/C][/ROW]
[ROW][C]191[/C][C]0.941215[/C][C]0.117569[/C][C]0.0587847[/C][/ROW]
[ROW][C]192[/C][C]0.961401[/C][C]0.0771982[/C][C]0.0385991[/C][/ROW]
[ROW][C]193[/C][C]0.956983[/C][C]0.0860332[/C][C]0.0430166[/C][/ROW]
[ROW][C]194[/C][C]0.950926[/C][C]0.0981485[/C][C]0.0490742[/C][/ROW]
[ROW][C]195[/C][C]0.94068[/C][C]0.118639[/C][C]0.0593197[/C][/ROW]
[ROW][C]196[/C][C]0.929813[/C][C]0.140374[/C][C]0.0701871[/C][/ROW]
[ROW][C]197[/C][C]0.922852[/C][C]0.154297[/C][C]0.0771484[/C][/ROW]
[ROW][C]198[/C][C]0.918875[/C][C]0.162249[/C][C]0.0811245[/C][/ROW]
[ROW][C]199[/C][C]0.925051[/C][C]0.149899[/C][C]0.0749493[/C][/ROW]
[ROW][C]200[/C][C]0.919603[/C][C]0.160793[/C][C]0.0803967[/C][/ROW]
[ROW][C]201[/C][C]0.911614[/C][C]0.176772[/C][C]0.0883858[/C][/ROW]
[ROW][C]202[/C][C]0.922034[/C][C]0.155931[/C][C]0.0779656[/C][/ROW]
[ROW][C]203[/C][C]0.907019[/C][C]0.185962[/C][C]0.0929808[/C][/ROW]
[ROW][C]204[/C][C]0.922664[/C][C]0.154672[/C][C]0.077336[/C][/ROW]
[ROW][C]205[/C][C]0.912284[/C][C]0.175433[/C][C]0.0877165[/C][/ROW]
[ROW][C]206[/C][C]0.901621[/C][C]0.196758[/C][C]0.0983792[/C][/ROW]
[ROW][C]207[/C][C]0.898348[/C][C]0.203305[/C][C]0.101652[/C][/ROW]
[ROW][C]208[/C][C]0.885783[/C][C]0.228433[/C][C]0.114217[/C][/ROW]
[ROW][C]209[/C][C]0.867896[/C][C]0.264207[/C][C]0.132104[/C][/ROW]
[ROW][C]210[/C][C]0.85257[/C][C]0.294859[/C][C]0.14743[/C][/ROW]
[ROW][C]211[/C][C]0.880435[/C][C]0.239129[/C][C]0.119565[/C][/ROW]
[ROW][C]212[/C][C]0.87593[/C][C]0.248141[/C][C]0.12407[/C][/ROW]
[ROW][C]213[/C][C]0.891008[/C][C]0.217984[/C][C]0.108992[/C][/ROW]
[ROW][C]214[/C][C]0.875565[/C][C]0.248871[/C][C]0.124435[/C][/ROW]
[ROW][C]215[/C][C]0.855786[/C][C]0.288429[/C][C]0.144214[/C][/ROW]
[ROW][C]216[/C][C]0.836395[/C][C]0.32721[/C][C]0.163605[/C][/ROW]
[ROW][C]217[/C][C]0.830974[/C][C]0.338052[/C][C]0.169026[/C][/ROW]
[ROW][C]218[/C][C]0.807964[/C][C]0.384072[/C][C]0.192036[/C][/ROW]
[ROW][C]219[/C][C]0.830878[/C][C]0.338244[/C][C]0.169122[/C][/ROW]
[ROW][C]220[/C][C]0.808125[/C][C]0.383749[/C][C]0.191875[/C][/ROW]
[ROW][C]221[/C][C]0.787549[/C][C]0.424903[/C][C]0.212451[/C][/ROW]
[ROW][C]222[/C][C]0.766211[/C][C]0.467578[/C][C]0.233789[/C][/ROW]
[ROW][C]223[/C][C]0.750586[/C][C]0.498827[/C][C]0.249414[/C][/ROW]
[ROW][C]224[/C][C]0.719939[/C][C]0.560121[/C][C]0.280061[/C][/ROW]
[ROW][C]225[/C][C]0.710076[/C][C]0.579849[/C][C]0.289924[/C][/ROW]
[ROW][C]226[/C][C]0.679466[/C][C]0.641068[/C][C]0.320534[/C][/ROW]
[ROW][C]227[/C][C]0.639882[/C][C]0.720236[/C][C]0.360118[/C][/ROW]
[ROW][C]228[/C][C]0.603802[/C][C]0.792396[/C][C]0.396198[/C][/ROW]
[ROW][C]229[/C][C]0.609692[/C][C]0.780616[/C][C]0.390308[/C][/ROW]
[ROW][C]230[/C][C]0.57227[/C][C]0.85546[/C][C]0.42773[/C][/ROW]
[ROW][C]231[/C][C]0.53527[/C][C]0.92946[/C][C]0.46473[/C][/ROW]
[ROW][C]232[/C][C]0.536181[/C][C]0.927639[/C][C]0.463819[/C][/ROW]
[ROW][C]233[/C][C]0.563017[/C][C]0.873966[/C][C]0.436983[/C][/ROW]
[ROW][C]234[/C][C]0.554782[/C][C]0.890435[/C][C]0.445218[/C][/ROW]
[ROW][C]235[/C][C]0.63292[/C][C]0.734161[/C][C]0.36708[/C][/ROW]
[ROW][C]236[/C][C]0.601963[/C][C]0.796075[/C][C]0.398037[/C][/ROW]
[ROW][C]237[/C][C]0.60065[/C][C]0.798699[/C][C]0.39935[/C][/ROW]
[ROW][C]238[/C][C]0.629063[/C][C]0.741874[/C][C]0.370937[/C][/ROW]
[ROW][C]239[/C][C]0.587765[/C][C]0.82447[/C][C]0.412235[/C][/ROW]
[ROW][C]240[/C][C]0.567511[/C][C]0.864977[/C][C]0.432489[/C][/ROW]
[ROW][C]241[/C][C]0.545038[/C][C]0.909925[/C][C]0.454962[/C][/ROW]
[ROW][C]242[/C][C]0.507122[/C][C]0.985756[/C][C]0.492878[/C][/ROW]
[ROW][C]243[/C][C]0.676883[/C][C]0.646235[/C][C]0.323117[/C][/ROW]
[ROW][C]244[/C][C]0.645915[/C][C]0.70817[/C][C]0.354085[/C][/ROW]
[ROW][C]245[/C][C]0.682683[/C][C]0.634634[/C][C]0.317317[/C][/ROW]
[ROW][C]246[/C][C]0.651339[/C][C]0.697322[/C][C]0.348661[/C][/ROW]
[ROW][C]247[/C][C]0.611931[/C][C]0.776137[/C][C]0.388069[/C][/ROW]
[ROW][C]248[/C][C]0.583951[/C][C]0.832098[/C][C]0.416049[/C][/ROW]
[ROW][C]249[/C][C]0.620512[/C][C]0.758976[/C][C]0.379488[/C][/ROW]
[ROW][C]250[/C][C]0.600554[/C][C]0.798891[/C][C]0.399446[/C][/ROW]
[ROW][C]251[/C][C]0.592298[/C][C]0.815405[/C][C]0.407702[/C][/ROW]
[ROW][C]252[/C][C]0.616066[/C][C]0.767868[/C][C]0.383934[/C][/ROW]
[ROW][C]253[/C][C]0.568707[/C][C]0.862585[/C][C]0.431293[/C][/ROW]
[ROW][C]254[/C][C]0.5116[/C][C]0.976799[/C][C]0.4884[/C][/ROW]
[ROW][C]255[/C][C]0.454856[/C][C]0.909712[/C][C]0.545144[/C][/ROW]
[ROW][C]256[/C][C]0.397626[/C][C]0.795252[/C][C]0.602374[/C][/ROW]
[ROW][C]257[/C][C]0.360994[/C][C]0.721987[/C][C]0.639006[/C][/ROW]
[ROW][C]258[/C][C]0.317862[/C][C]0.635725[/C][C]0.682138[/C][/ROW]
[ROW][C]259[/C][C]0.311662[/C][C]0.623323[/C][C]0.688338[/C][/ROW]
[ROW][C]260[/C][C]0.34587[/C][C]0.691739[/C][C]0.65413[/C][/ROW]
[ROW][C]261[/C][C]0.29584[/C][C]0.591681[/C][C]0.70416[/C][/ROW]
[ROW][C]262[/C][C]0.246309[/C][C]0.492618[/C][C]0.753691[/C][/ROW]
[ROW][C]263[/C][C]0.287655[/C][C]0.575309[/C][C]0.712345[/C][/ROW]
[ROW][C]264[/C][C]0.250869[/C][C]0.501738[/C][C]0.749131[/C][/ROW]
[ROW][C]265[/C][C]0.267175[/C][C]0.53435[/C][C]0.732825[/C][/ROW]
[ROW][C]266[/C][C]0.834715[/C][C]0.330571[/C][C]0.165285[/C][/ROW]
[ROW][C]267[/C][C]0.802131[/C][C]0.395737[/C][C]0.197869[/C][/ROW]
[ROW][C]268[/C][C]0.999586[/C][C]0.000828483[/C][C]0.000414241[/C][/ROW]
[ROW][C]269[/C][C]0.999994[/C][C]1.26469e-05[/C][C]6.32346e-06[/C][/ROW]
[ROW][C]270[/C][C]0.999983[/C][C]3.45214e-05[/C][C]1.72607e-05[/C][/ROW]
[ROW][C]271[/C][C]0.999979[/C][C]4.28834e-05[/C][C]2.14417e-05[/C][/ROW]
[ROW][C]272[/C][C]0.999973[/C][C]5.45368e-05[/C][C]2.72684e-05[/C][/ROW]
[ROW][C]273[/C][C]0.999923[/C][C]0.000153414[/C][C]7.67071e-05[/C][/ROW]
[ROW][C]274[/C][C]0.99966[/C][C]0.000679151[/C][C]0.000339575[/C][/ROW]
[ROW][C]275[/C][C]0.999225[/C][C]0.00154924[/C][C]0.000774619[/C][/ROW]
[ROW][C]276[/C][C]0.99676[/C][C]0.00647942[/C][C]0.00323971[/C][/ROW]
[ROW][C]277[/C][C]0.987526[/C][C]0.0249487[/C][C]0.0124743[/C][/ROW]
[ROW][C]278[/C][C]0.966353[/C][C]0.0672938[/C][C]0.0336469[/C][/ROW]
[ROW][C]279[/C][C]0.997371[/C][C]0.00525788[/C][C]0.00262894[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266351&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266351&T=5

As an alternative you can also use a QR Code:  
QR Code


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9767620.0464750.0232375
90.9529890.09402180.0470109
100.9320360.1359280.0679642
110.9427510.1144970.0572485
120.9074970.1850050.0925026
130.9290760.1418470.0709235
140.90010.19980.0999
150.8569570.2860850.143043
160.8098140.3803720.190186
170.7817280.4365450.218272
180.7344630.5310740.265537
190.6704090.6591810.329591
200.622170.755660.37783
210.5512630.8974740.448737
220.6248380.7503250.375162
230.5937170.8125660.406283
240.5290840.9418320.470916
250.4864350.972870.513565
260.4290880.8581750.570912
270.3765550.7531110.623445
280.3194360.6388710.680564
290.3630980.7261960.636902
300.3277640.6555270.672236
310.304450.60890.69555
320.2757330.5514670.724267
330.2758170.5516350.724183
340.3833790.7667590.616621
350.3367010.6734020.663299
360.3708990.7417980.629101
370.3288430.6576850.671157
380.2907980.5815960.709202
390.2512510.5025020.748749
400.2509940.5019880.749006
410.2972990.5945990.702701
420.2687340.5374670.731266
430.3929560.7859120.607044
440.3553210.7106420.644679
450.3362050.6724090.663795
460.3045320.6090630.695468
470.2951620.5903250.704838
480.2594190.5188390.740581
490.2307260.4614510.769274
500.321720.643440.67828
510.3663310.7326610.633669
520.361610.723220.63839
530.3258130.6516260.674187
540.3634110.7268210.636589
550.3420380.6840760.657962
560.3526510.7053030.647349
570.3635650.7271290.636435
580.3323910.6647810.667609
590.4554970.9109940.544503
600.547060.9058790.45294
610.5077040.9845910.492296
620.5366290.9267420.463371
630.5250470.9499060.474953
640.5058120.9883770.494188
650.541350.9173010.45865
660.6097420.7805160.390258
670.5848430.8303150.415157
680.5521170.8957650.447883
690.5411560.9176870.458844
700.5064790.9870420.493521
710.5147450.9705110.485255
720.4935630.9871270.506437
730.4613360.9226710.538664
740.4316180.8632360.568382
750.4047990.8095970.595201
760.4078580.8157150.592142
770.5265580.9468830.473442
780.5105450.9789090.489455
790.4874240.9748470.512576
800.4784640.9569290.521536
810.4674250.9348490.532575
820.4426590.8853180.557341
830.502750.99450.49725
840.471140.9422810.52886
850.5039290.9921410.496071
860.473170.9463410.52683
870.5821540.8356920.417846
880.5656340.8687320.434366
890.5342780.9314450.465722
900.5016490.9967020.498351
910.468730.9374590.53127
920.4665590.9331180.533441
930.4926080.9852160.507392
940.5091140.9817720.490886
950.6392550.721490.360745
960.6161390.7677210.383861
970.6113320.7773350.388668
980.6582230.6835540.341777
990.6405820.7188360.359418
1000.6649980.6700040.335002
1010.6471730.7056550.352827
1020.7012060.5975870.298794
1030.781730.4365390.21827
1040.7610620.4778760.238938
1050.7429030.5141930.257097
1060.7397930.5204140.260207
1070.753450.49310.24655
1080.7774730.4450550.222527
1090.7964110.4071770.203589
1100.8005590.3988830.199441
1110.9000840.1998320.0999161
1120.9312490.1375030.0687514
1130.9346760.1306480.065324
1140.9291590.1416830.0708414
1150.9232690.1534620.0767308
1160.9557310.08853830.0442691
1170.9570240.08595170.0429759
1180.9633120.0733760.036688
1190.9695510.06089760.0304488
1200.9640170.07196560.0359828
1210.9675820.06483610.0324181
1220.963380.073240.03662
1230.9676280.06474320.0323716
1240.9711520.05769650.0288483
1250.9809450.03810960.0190548
1260.9782270.04354680.0217734
1270.9889440.02211110.0110556
1280.9905010.0189990.00949949
1290.9883860.02322830.0116142
1300.9865920.0268160.013408
1310.9871860.02562790.012814
1320.9871380.02572480.0128624
1330.9864280.02714370.0135718
1340.9850870.02982630.0149132
1350.9832330.03353380.0167669
1360.9819160.03616820.0180841
1370.9783870.04322620.0216131
1380.9752270.04954530.0247726
1390.9711920.05761540.0288077
1400.9798130.04037440.0201872
1410.9849220.03015660.0150783
1420.9817790.03644140.0182207
1430.9780620.04387580.0219379
1440.9740570.05188610.0259431
1450.9779570.04408620.0220431
1460.9768640.04627110.0231355
1470.974250.05150030.0257502
1480.9719110.05617790.0280889
1490.9670890.0658220.032911
1500.9644840.07103290.0355164
1510.9601760.07964720.0398236
1520.9549090.09018220.0450911
1530.9474140.1051720.0525859
1540.9518520.09629620.0481481
1550.9467810.1064370.0532187
1560.9807530.03849490.0192474
1570.9786980.04260440.0213022
1580.9765490.0469020.023451
1590.9715340.05693120.0284656
1600.976310.04738010.0236901
1610.9716750.05664920.0283246
1620.9698150.06036910.0301845
1630.9685310.06293810.0314691
1640.9638310.07233750.0361688
1650.9573930.08521350.0426067
1660.9688590.06228120.0311406
1670.9632780.07344330.0367217
1680.9583030.08339350.0416967
1690.9808530.03829460.0191473
1700.9827980.03440350.0172018
1710.9802720.03945570.0197279
1720.9778310.04433860.0221693
1730.9832130.03357410.0167871
1740.9791350.04173040.0208652
1750.9797230.04055380.0202769
1760.9752770.04944540.0247227
1770.9797160.04056870.0202843
1780.9763640.04727210.023636
1790.9709060.05818770.0290938
1800.9644290.07114130.0355707
1810.9657710.06845750.0342288
1820.9619810.07603730.0380187
1830.9610340.07793290.0389664
1840.9547680.0904640.045232
1850.9612170.07756580.0387829
1860.9616560.07668720.0383436
1870.9539210.09215830.0460792
1880.9489060.1021890.0510944
1890.9392920.1214160.0607082
1900.9499670.1000660.0500328
1910.9412150.1175690.0587847
1920.9614010.07719820.0385991
1930.9569830.08603320.0430166
1940.9509260.09814850.0490742
1950.940680.1186390.0593197
1960.9298130.1403740.0701871
1970.9228520.1542970.0771484
1980.9188750.1622490.0811245
1990.9250510.1498990.0749493
2000.9196030.1607930.0803967
2010.9116140.1767720.0883858
2020.9220340.1559310.0779656
2030.9070190.1859620.0929808
2040.9226640.1546720.077336
2050.9122840.1754330.0877165
2060.9016210.1967580.0983792
2070.8983480.2033050.101652
2080.8857830.2284330.114217
2090.8678960.2642070.132104
2100.852570.2948590.14743
2110.8804350.2391290.119565
2120.875930.2481410.12407
2130.8910080.2179840.108992
2140.8755650.2488710.124435
2150.8557860.2884290.144214
2160.8363950.327210.163605
2170.8309740.3380520.169026
2180.8079640.3840720.192036
2190.8308780.3382440.169122
2200.8081250.3837490.191875
2210.7875490.4249030.212451
2220.7662110.4675780.233789
2230.7505860.4988270.249414
2240.7199390.5601210.280061
2250.7100760.5798490.289924
2260.6794660.6410680.320534
2270.6398820.7202360.360118
2280.6038020.7923960.396198
2290.6096920.7806160.390308
2300.572270.855460.42773
2310.535270.929460.46473
2320.5361810.9276390.463819
2330.5630170.8739660.436983
2340.5547820.8904350.445218
2350.632920.7341610.36708
2360.6019630.7960750.398037
2370.600650.7986990.39935
2380.6290630.7418740.370937
2390.5877650.824470.412235
2400.5675110.8649770.432489
2410.5450380.9099250.454962
2420.5071220.9857560.492878
2430.6768830.6462350.323117
2440.6459150.708170.354085
2450.6826830.6346340.317317
2460.6513390.6973220.348661
2470.6119310.7761370.388069
2480.5839510.8320980.416049
2490.6205120.7589760.379488
2500.6005540.7988910.399446
2510.5922980.8154050.407702
2520.6160660.7678680.383934
2530.5687070.8625850.431293
2540.51160.9767990.4884
2550.4548560.9097120.545144
2560.3976260.7952520.602374
2570.3609940.7219870.639006
2580.3178620.6357250.682138
2590.3116620.6233230.688338
2600.345870.6917390.65413
2610.295840.5916810.70416
2620.2463090.4926180.753691
2630.2876550.5753090.712345
2640.2508690.5017380.749131
2650.2671750.534350.732825
2660.8347150.3305710.165285
2670.8021310.3957370.197869
2680.9995860.0008284830.000414241
2690.9999941.26469e-056.32346e-06
2700.9999833.45214e-051.72607e-05
2710.9999794.28834e-052.14417e-05
2720.9999735.45368e-052.72684e-05
2730.9999230.0001534147.67071e-05
2740.999660.0006791510.000339575
2750.9992250.001549240.000774619
2760.996760.006479420.00323971
2770.9875260.02494870.0124743
2780.9663530.06729380.0336469
2790.9973710.005257880.00262894






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0367647NOK
5% type I error level460.169118NOK
10% type I error level870.319853NOK

\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 & 10 & 0.0367647 & NOK \tabularnewline
5% type I error level & 46 & 0.169118 & NOK \tabularnewline
10% type I error level & 87 & 0.319853 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266351&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]10[/C][C]0.0367647[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]46[/C][C]0.169118[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]87[/C][C]0.319853[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266351&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266351&T=6

As an alternative you can also use a QR Code:  
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 level100.0367647NOK
5% type I error level460.169118NOK
10% type I error level870.319853NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; 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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), 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,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
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, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
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,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
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,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
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,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
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,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
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')
}