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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 computationMon, 15 Dec 2014 16:46:45 +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/15/t1418662330r5aql7gjfuqpv6p.htm/, Retrieved Thu, 16 May 2024 23:22:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268752, Retrieved Thu, 16 May 2024 23:22:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact51

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [RFC vs. Ruwe Ex] [2014-12-15 16:46:45] [3bdd9332f2b4587684e97c4d9c2e2a73] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
149	96	68	86	7,5
152	75	55	62	2,5
139	70	39	70	6,0
148	88	32	71	6,5
158	114	62	108	1,0
128	69	33	64	1,0
224	176	52	119	5,5
159	114	62	97	8,5
105	121	77	129	6,5
159	110	76	153	4,5
167	158	41	78	2,0
165	116	48	80	5,0
159	181	63	99	0,5
119	77	30	68	5,0
176	141	78	147	5,0
54	35	19	40	2,5
91	80	31	57	5,0
163	152	66	120	5,5
124	97	35	71	3,5
137	99	42	84	3,0
121	84	45	68	4,0
153	68	21	55	0,5
148	101	25	137	6,5
221	107	44	79	4,5
188	88	69	116	7,5
149	112	54	101	5,5
244	171	74	111	4,0
148	137	80	189	7,5
92	77	42	66	7,0
150	66	61	81	4,0
153	93	41	63	5,5
94	105	46	69	2,5
156	131	39	71	5,5
146	89	63	70	0,5
132	102	34	64	3,5
161	161	51	143	2,5
105	120	42	85	4,5
97	127	31	86	4,5
151	77	39	55	4,5
131	108	20	69	6,0
166	85	49	120	2,5
157	168	53	96	5,0
111	48	31	60	0,0
145	152	39	95	5,0
162	75	54	100	6,5
163	107	49	68	5,0
59	62	34	57	6,0
187	121	46	105	4,5
109	124	55	85	5,5
90	72	42	103	1,0
105	40	50	57	7,5
83	58	13	51	6,0
116	97	37	69	5,0
42	88	25	41	1,0
148	126	30	49	5,0
155	104	28	50	6,5
125	148	45	93	7,0
116	146	35	58	4,5
128	80	28	54	0,0
138	97	41	74	8,5
49	25	6	15	3,5
96	99	45	69	7,5
164	118	73	107	3,5
162	58	17	65	6,0
99	63	40	58	1,5
202	139	64	107	9,0
186	50	37	70	3,5
66	60	25	53	3,5
183	152	65	136	4,0
214	142	100	126	6,5
188	94	28	95	7,5
104	66	35	69	6,0
177	127	56	136	5,0
126	67	29	58	5,5
76	90	43	59	3,5
99	75	59	118	7,5
157	96	52	110	1,0
139	128	50	82	6,5
78	41	3	50	NA
162	146	59	102	6,5
108	69	27	65	6,5
159	186	61	90	7,0
74	81	28	64	3,5
110	85	51	83	1,5
96	54	35	70	4,0
116	46	29	50	7,5
87	106	48	77	4,5
97	34	25	37	0,0
127	60	44	81	3,5
106	95	64	101	5,5
80	57	32	79	5,0
74	62	20	71	4,5
91	36	28	60	2,5
133	56	34	55	7,5
74	54	31	44	7,0
114	64	26	40	0,0
140	76	58	56	4,5
95	98	23	43	3,0
98	88	21	45	1,5
121	35	21	32	3,5
126	102	33	56	2,5
98	61	16	40	5,5
95	80	20	34	8,0
110	49	37	89	1,0
70	78	35	50	5,0
102	90	33	56	4,5
86	45	27	46	3,0
130	55	41	76	3,0
96	96	40	64	8,0
102	43	35	74	2,5
100	52	28	57	7,0
94	60	32	45	0,0
52	54	22	30	1,0
98	51	44	62	3,5
118	51	27	51	5,5
99	38	17	36	5,5
48	41	12	34	0,5
50	146	45	61	7,5
150	182	37	70	9
154	192	37	69	9,5
109	263	108	145	8,5
68	35	10	23	7
194	439	68	120	8
158	214	72	147	10
159	341	143	215	7
67	58	9	24	8,5
147	292	55	84	9
39	85	17	30	9,5
100	200	37	77	4
111	158	27	46	6
138	199	37	61	8
101	297	58	178	5,5
131	227	66	160	9,5
101	108	21	57	7,5
114	86	19	42	7
165	302	78	163	7,5
114	148	35	75	8
111	178	48	94	7
75	120	27	45	7
82	207	43	78	6
121	157	30	47	10
32	128	25	29	2,5
150	296	69	97	9
117	323	72	116	8
71	79	23	32	6
165	70	13	50	8,5
154	146	61	118	6
126	246	43	66	9
138	145	22	48	8
149	196	51	86	8
145	199	67	89	9
120	127	36	76	5,5
138	91	21	39	5
109	153	44	75	7
132	299	45	57	5,5
172	228	34	72	9
169	190	36	60	2
114	180	72	109	8,5
156	212	39	76	9
172	269	43	65	8,5
68	130	25	40	9
89	179	56	58	7,5
167	243	80	123	10
113	190	40	71	9
115	299	73	102	7,5
78	121	34	80	6
118	137	72	97	10,5
87	305	42	46	8,5
173	157	61	93	8
2	96	23	19	10
162	183	74	140	10,5
49	52	16	78	6,5
122	238	66	98	9,5
96	40	9	40	8,5
100	226	41	80	7,5
82	190	57	76	5
100	214	48	79	8
115	145	51	87	10
141	119	53	95	7
165	222	29	49	7,5
165	222	29	49	7,5
110	159	55	80	9,5
118	165	54	86	6
158	249	43	69	10
146	125	51	79	7
49	122	20	52	3
90	186	79	120	6
121	148	39	69	7
155	274	61	94	10
104	172	55	72	7
147	84	30	43	3,5
110	168	55	87	8
108	102	22	52	10
113	106	37	71	5,5
115	2	2	61	6
61	139	38	51	6,5
60	95	27	50	6,5
109	130	56	67	8,5
68	72	25	30	4
111	141	39	70	9,5
77	113	33	52	8
73	206	43	75	8,5
151	268	57	87	5,5
89	175	43	69	7
78	77	23	72	9
110	125	44	79	8
220	255	54	121	10
65	111	28	43	8
141	132	36	58	6
117	211	39	57	8
122	92	16	50	5
63	76	23	69	9
44	171	40	64	4,5
52	83	24	38	8,5
62	119	29	53	7
131	266	78	90	9,5
101	186	57	96	8,5
42	50	37	49	7,5
152	117	27	56	7,5
107	219	61	102	5
77	246	27	40	7
154	279	69	100	8
103	148	34	67	5,5
96	137	44	78	8,5
154	130	21	62	7,5
175	181	34	55	9,5
57	98	39	59	7
112	226	51	96	8
143	234	34	86	8,5
49	138	31	38	3,5
110	85	13	43	6,5
131	66	12	23	6,5
167	236	51	77	10,5
56	106	24	48	8,5
137	135	19	26	8
86	122	30	91	10
121	218	81	94	10
149	199	42	62	9,5
168	112	22	74	9
140	278	85	114	10
88	94	27	52	7,5
168	113	25	64	4,5
94	84	22	31	4,5
51	86	19	38	0,5
48	62	14	27	6,5
145	222	45	105	4,5
66	167	45	64	5,5
85	82	28	62	5
109	207	51	65	6
63	184	41	58	4
102	83	31	76	8
162	183	74	140	10,5
128	85	24	48	8,5
86	89	19	68	6,5
114	225	51	80	8
164	237	73	71	8,5
119	102	24	76	5,5
126	221	61	63	7
132	128	23	46	5
142	91	14	53	3,5
83	198	54	74	5
94	204	51	70	9
81	158	62	78	8,5
166	138	36	56	5
110	226	59	100	9,5
64	44	24	51	3
93	196	26	52	1,5
104	83	54	102	6
105	79	39	78	0,5
49	52	16	78	6,5
88	105	36	55	7,5
95	116	31	98	4,5
102	83	31	76	8
99	196	42	73	9
63	153	39	47	7,5
76	157	25	45	8,5
109	75	31	83	7
117	106	38	60	9,5
57	58	31	48	6,5
120	75	17	50	9,5
73	74	22	56	6
91	185	55	77	8
108	265	62	91	9,5
105	131	51	76	8
117	139	30	68	8
119	196	49	74	9
31	78	16	29	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 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 & 8 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268752&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]8 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=268752&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268752&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 time8 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.40822 -0.00276785L[t] + 0.0180543B[t] -0.00671728C[t] -0.000649436H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.40822 -0.00276785L[t] +  0.0180543B[t] -0.00671728C[t] -0.000649436H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268752&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.40822 -0.00276785L[t] +  0.0180543B[t] -0.00671728C[t] -0.000649436H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268752&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268752&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] = + 4.40822 -0.00276785L[t] + 0.0180543B[t] -0.00671728C[t] -0.000649436H[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.408220.4578259.6293.77973e-191.88987e-19
L-0.002767850.00399945-0.69210.4894720.244736
B0.01805430.002427857.4361.2591e-126.29552e-13
C-0.006717280.0130691-0.5140.6076680.303834
H-0.0006494360.00783926-0.082840.9340350.467017

\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) & 4.40822 & 0.457825 & 9.629 & 3.77973e-19 & 1.88987e-19 \tabularnewline
L & -0.00276785 & 0.00399945 & -0.6921 & 0.489472 & 0.244736 \tabularnewline
B & 0.0180543 & 0.00242785 & 7.436 & 1.2591e-12 & 6.29552e-13 \tabularnewline
C & -0.00671728 & 0.0130691 & -0.514 & 0.607668 & 0.303834 \tabularnewline
H & -0.000649436 & 0.00783926 & -0.08284 & 0.934035 & 0.467017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268752&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]4.40822[/C][C]0.457825[/C][C]9.629[/C][C]3.77973e-19[/C][C]1.88987e-19[/C][/ROW]
[ROW][C]L[/C][C]-0.00276785[/C][C]0.00399945[/C][C]-0.6921[/C][C]0.489472[/C][C]0.244736[/C][/ROW]
[ROW][C]B[/C][C]0.0180543[/C][C]0.00242785[/C][C]7.436[/C][C]1.2591e-12[/C][C]6.29552e-13[/C][/ROW]
[ROW][C]C[/C][C]-0.00671728[/C][C]0.0130691[/C][C]-0.514[/C][C]0.607668[/C][C]0.303834[/C][/ROW]
[ROW][C]H[/C][C]-0.000649436[/C][C]0.00783926[/C][C]-0.08284[/C][C]0.934035[/C][C]0.467017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268752&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268752&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)4.408220.4578259.6293.77973e-191.88987e-19
L-0.002767850.00399945-0.69210.4894720.244736
B0.01805430.002427857.4361.2591e-126.29552e-13
C-0.006717280.0130691-0.5140.6076680.303834
H-0.0006494360.00783926-0.082840.9340350.467017






Multiple Linear Regression - Regression Statistics
Multiple R0.451796
R-squared0.204119
Adjusted R-squared0.19279
F-TEST (value)18.017
F-TEST (DF numerator)4
F-TEST (DF denominator)281
p-value3.47944e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29711
Sum Squared Residuals1482.75

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.451796 \tabularnewline
R-squared & 0.204119 \tabularnewline
Adjusted R-squared & 0.19279 \tabularnewline
F-TEST (value) & 18.017 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 3.47944e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.29711 \tabularnewline
Sum Squared Residuals & 1482.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268752&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.451796[/C][/ROW]
[ROW][C]R-squared[/C][C]0.204119[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.19279[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.017[/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]3.47944e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.29711[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1482.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268752&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268752&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 R0.451796
R-squared0.204119
Adjusted R-squared0.19279
F-TEST (value)18.017
F-TEST (DF numerator)4
F-TEST (DF denominator)281
p-value3.47944e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29711
Sum Squared Residuals1482.75






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.216392.28361
22.54.93186-2.43186
364.979851.02015
46.55.326291.17371
515.54247-4.54247
615.03644-4.03644
75.56.53919-1.03919
88.55.546852.95315
96.55.701150.798848
104.55.34422-0.844222
1126.4725-4.4725
1255.67143-0.671433
130.56.74847-6.24847
1455.22334-0.223342
1555.84731-0.847313
162.54.73705-2.23705
1755.35543-0.355431
185.56.18003-0.680034
193.55.53505-2.03505
2035.47972-2.47972
2145.24343-1.24343
220.55.03564-4.53564
236.55.565150.934848
244.55.38146-0.881463
257.54.937812.56219
265.55.58956-0.0895597
2746.25098-2.25098
287.55.811881.68812
2975.218771.78123
3044.72226-0.722263
315.55.347460.15254
322.55.68993-3.18993
335.56.03346-0.533458
340.55.14229-4.64229
353.55.61445-2.11445
362.56.43388-3.93388
374.55.94678-1.44678
384.56.16854-1.66854
394.55.08276-0.582757
4065.816330.183666
412.55.07629-2.57629
4256.58842-1.58842
4304.72039-4.72039
4456.42746-1.42746
456.54.886221.61378
4655.51556-0.515556
4765.098870.901127
484.55.69801-1.19801
495.55.9206-0.420599
5015.11-4.11
517.54.466883.03312
5265.105190.894813
5355.54506-0.54506
5415.68618-4.68618
5556.04007-1.04007
566.55.636290.863711
5776.371590.628407
584.56.4503-1.9503
5905.27512-5.27512
608.55.454053.04595
613.54.6739-1.1739
627.55.582791.91721
633.55.52484-2.02484
6464.850571.14943
651.54.96526-3.46526
6695.859263.14074
673.54.50211-1.00211
683.55.10644-1.60644
6946.121-2.121
706.55.626050.873953
717.55.335182.16482
7265.032030.967974
7355.74671-0.746709
745.55.036640.463365
753.55.49559-1.99559
767.55.015322.48468
7715.28614-4.28614
786.55.945320.554685
79NANA0.366813
806.55.131451.36855
816.56.358020.141979
8278.93614-1.93614
833.57.24188-3.74188
841.52.33687-0.836868
8541.190372.80963
867.58.70873-1.20873
874.59.06162-4.56162
8801.29179-1.29179
893.53.334480.165518
905.55.449620.0503761
9155.64231-0.642305
924.56.57925-2.07925
932.5-0.2129752.71297
947.55.441522.05848
95712.0475-5.04753
9600.466872-0.466872
974.57.23217-2.73217
9837.05546-4.05546
991.52.54336-1.04336
1003.56.64297-3.14297
1012.52.104820.395176
1025.52.933192.56681
103811.6821-3.68207
10411.35512-0.355124
10555.99274-0.992742
1064.56.27138-1.77138
10734.71662-1.71662
10830.5654582.43454
109810.1191-2.11907
1102.50.3451522.15485
111711.9871-4.98712
11204.07196-4.07196
11312.22191-1.22191
1143.52.787890.71211
1155.54.682690.817312
1165.59.9129-4.4129
1170.5-0.4361440.936144
1187.55.484922.01508
11996.655042.34496
1209.59.035160.464838
1218.56.269792.23021
122710.2624-3.26238
12385.25542.7446
1241012.0244-2.02444
12573.693883.30612
1268.58.349190.150811
12795.201213.79879
1289.512.9437-3.44374
12944.74232-0.742321
13065.33090.6691
131811.4856-3.48558
1325.53.59671.9033
1339.57.900451.59955
1347.55.990441.50956
13578.27411-1.27411
1367.55.98091.5191
13787.931170.0688295
13876.156550.84345
13978.57899-1.57899
14062.675793.32421
1411013.9438-3.94383
1422.52.310620.189382
143910.3569-1.35693
14487.462710.537292
14562.595523.40448
1468.58.6315-0.131505
14765.169110.830885
14897.465171.53483
14987.136010.863987
15086.091821.90818
15199.57779-0.577789
1525.56.0028-0.502802
15354.524560.475442
154710.6018-3.60179
1555.54.273381.22662
156914.09-5.08997
15720.2880191.71198
1588.56.992611.50739
15998.957690.0423087
1608.55.873152.62685
16198.479760.520241
1627.55.215912.28409
163108.210961.78904
164910.4315-1.43154
1657.57.59655-0.0965496
16661.508414.49159
16710.511.362-0.861969
1688.56.793751.70625
16983.969064.03094
170106.175763.82424
17110.59.053281.44672
1726.54.860471.63953
1739.55.778243.72176
1748.58.88434-0.384336
1757.59.67932-2.17932
17654.621310.378687
17784.30873.6913
178108.74871.2513
17977.23295-0.232948
1807.57.73295-0.232948
1817.54.552982.94702
1829.510.142-0.641982
18364.132761.86724
184108.867011.13299
185710.3071-3.3071
18633.90861-0.908609
18765.438550.561445
18875.455271.54473
189109.809490.190514
19078.78846-1.78846
1913.52.210921.28908
19283.769274.23073
1931010.2146-0.214554
1945.53.572971.92703
19565.960540.0394553
1966.55.743460.756536
1976.54.03392.4661
1988.59.8325-1.3325
19940.8392043.1608
2009.57.479782.02022
20187.087790.912205
2028.511.3894-2.88943
2035.55.487720.0122773
20473.381253.61875
20597.013671.98633
20685.961822.03818
207108.016321.98368
20888.12163-0.121625
20965.594840.405161
21088.59158-0.591584
21151.406663.59334
212911.5635-2.56346
2134.51.57692.9231
2148.57.655850.844152
21575.765671.23433
2169.58.041531.45847
2178.55.914322.58568
2187.55.882121.61788
2197.510.0899-2.58995
22056.4291-1.4291
22177.49068-0.490676
22289.02326-1.02326
2235.53.269722.23028
2248.57.14771.3523
2257.54.927562.57244
2269.58.219481.28052
22776.773560.226443
22887.452880.547123
2298.511.5312-3.03117
2303.52.523120.976884
2316.55.141671.35833
2326.53.814212.68579
23310.57.974582.52542
2348.56.821841.67816
23584.112193.88781
236107.403992.59601
237107.766222.23378
2389.56.269463.23054
23997.39481.6052
240108.146611.85339
2417.58.77386-1.27386
2424.55.49669-0.996685
2434.59.66742-5.16742
2440.5-0.7168521.21685
2456.59.64446-3.14446
2464.55.89676-1.39676
2475.55.92505-0.425051
24856.45896-1.45896
24969.24275-3.24275
25041.366812.63319
25184.175763.82424
25210.57.396163.10384
2538.57.605220.894778
2546.56.260360.239642
25587.196680.803318
2568.58.70981-0.209807
2575.56.09879-0.598795
25878.16944-1.16944
25957.02966-2.02966
2603.55.84244-2.34244
26153.443071.55693
26297.069471.93053
2638.59.66205-1.16205
26453.222761.77724
2659.511.3311-1.83113
26638.98103-5.98103
2671.50.6898890.810111
268610.7313-4.73125
2690.5-0.9467181.44672
2706.54.78281.7172
2717.58.96769-1.46769
2724.51.866812.63319
27386.34331.6567
27498.203650.796351
2757.55.835231.66477
2768.56.698451.80155
27773.203913.79609
2789.58.058191.44181
2796.52.283484.21652
2809.58.858030.641969
28165.076930.923073
28286.91811.0819
2839.57.590761.90924
28486.348241.65176
28586.240281.75972
28699.60434-0.604337
2875NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.21639 & 2.28361 \tabularnewline
2 & 2.5 & 4.93186 & -2.43186 \tabularnewline
3 & 6 & 4.97985 & 1.02015 \tabularnewline
4 & 6.5 & 5.32629 & 1.17371 \tabularnewline
5 & 1 & 5.54247 & -4.54247 \tabularnewline
6 & 1 & 5.03644 & -4.03644 \tabularnewline
7 & 5.5 & 6.53919 & -1.03919 \tabularnewline
8 & 8.5 & 5.54685 & 2.95315 \tabularnewline
9 & 6.5 & 5.70115 & 0.798848 \tabularnewline
10 & 4.5 & 5.34422 & -0.844222 \tabularnewline
11 & 2 & 6.4725 & -4.4725 \tabularnewline
12 & 5 & 5.67143 & -0.671433 \tabularnewline
13 & 0.5 & 6.74847 & -6.24847 \tabularnewline
14 & 5 & 5.22334 & -0.223342 \tabularnewline
15 & 5 & 5.84731 & -0.847313 \tabularnewline
16 & 2.5 & 4.73705 & -2.23705 \tabularnewline
17 & 5 & 5.35543 & -0.355431 \tabularnewline
18 & 5.5 & 6.18003 & -0.680034 \tabularnewline
19 & 3.5 & 5.53505 & -2.03505 \tabularnewline
20 & 3 & 5.47972 & -2.47972 \tabularnewline
21 & 4 & 5.24343 & -1.24343 \tabularnewline
22 & 0.5 & 5.03564 & -4.53564 \tabularnewline
23 & 6.5 & 5.56515 & 0.934848 \tabularnewline
24 & 4.5 & 5.38146 & -0.881463 \tabularnewline
25 & 7.5 & 4.93781 & 2.56219 \tabularnewline
26 & 5.5 & 5.58956 & -0.0895597 \tabularnewline
27 & 4 & 6.25098 & -2.25098 \tabularnewline
28 & 7.5 & 5.81188 & 1.68812 \tabularnewline
29 & 7 & 5.21877 & 1.78123 \tabularnewline
30 & 4 & 4.72226 & -0.722263 \tabularnewline
31 & 5.5 & 5.34746 & 0.15254 \tabularnewline
32 & 2.5 & 5.68993 & -3.18993 \tabularnewline
33 & 5.5 & 6.03346 & -0.533458 \tabularnewline
34 & 0.5 & 5.14229 & -4.64229 \tabularnewline
35 & 3.5 & 5.61445 & -2.11445 \tabularnewline
36 & 2.5 & 6.43388 & -3.93388 \tabularnewline
37 & 4.5 & 5.94678 & -1.44678 \tabularnewline
38 & 4.5 & 6.16854 & -1.66854 \tabularnewline
39 & 4.5 & 5.08276 & -0.582757 \tabularnewline
40 & 6 & 5.81633 & 0.183666 \tabularnewline
41 & 2.5 & 5.07629 & -2.57629 \tabularnewline
42 & 5 & 6.58842 & -1.58842 \tabularnewline
43 & 0 & 4.72039 & -4.72039 \tabularnewline
44 & 5 & 6.42746 & -1.42746 \tabularnewline
45 & 6.5 & 4.88622 & 1.61378 \tabularnewline
46 & 5 & 5.51556 & -0.515556 \tabularnewline
47 & 6 & 5.09887 & 0.901127 \tabularnewline
48 & 4.5 & 5.69801 & -1.19801 \tabularnewline
49 & 5.5 & 5.9206 & -0.420599 \tabularnewline
50 & 1 & 5.11 & -4.11 \tabularnewline
51 & 7.5 & 4.46688 & 3.03312 \tabularnewline
52 & 6 & 5.10519 & 0.894813 \tabularnewline
53 & 5 & 5.54506 & -0.54506 \tabularnewline
54 & 1 & 5.68618 & -4.68618 \tabularnewline
55 & 5 & 6.04007 & -1.04007 \tabularnewline
56 & 6.5 & 5.63629 & 0.863711 \tabularnewline
57 & 7 & 6.37159 & 0.628407 \tabularnewline
58 & 4.5 & 6.4503 & -1.9503 \tabularnewline
59 & 0 & 5.27512 & -5.27512 \tabularnewline
60 & 8.5 & 5.45405 & 3.04595 \tabularnewline
61 & 3.5 & 4.6739 & -1.1739 \tabularnewline
62 & 7.5 & 5.58279 & 1.91721 \tabularnewline
63 & 3.5 & 5.52484 & -2.02484 \tabularnewline
64 & 6 & 4.85057 & 1.14943 \tabularnewline
65 & 1.5 & 4.96526 & -3.46526 \tabularnewline
66 & 9 & 5.85926 & 3.14074 \tabularnewline
67 & 3.5 & 4.50211 & -1.00211 \tabularnewline
68 & 3.5 & 5.10644 & -1.60644 \tabularnewline
69 & 4 & 6.121 & -2.121 \tabularnewline
70 & 6.5 & 5.62605 & 0.873953 \tabularnewline
71 & 7.5 & 5.33518 & 2.16482 \tabularnewline
72 & 6 & 5.03203 & 0.967974 \tabularnewline
73 & 5 & 5.74671 & -0.746709 \tabularnewline
74 & 5.5 & 5.03664 & 0.463365 \tabularnewline
75 & 3.5 & 5.49559 & -1.99559 \tabularnewline
76 & 7.5 & 5.01532 & 2.48468 \tabularnewline
77 & 1 & 5.28614 & -4.28614 \tabularnewline
78 & 6.5 & 5.94532 & 0.554685 \tabularnewline
79 & NA & NA & 0.366813 \tabularnewline
80 & 6.5 & 5.13145 & 1.36855 \tabularnewline
81 & 6.5 & 6.35802 & 0.141979 \tabularnewline
82 & 7 & 8.93614 & -1.93614 \tabularnewline
83 & 3.5 & 7.24188 & -3.74188 \tabularnewline
84 & 1.5 & 2.33687 & -0.836868 \tabularnewline
85 & 4 & 1.19037 & 2.80963 \tabularnewline
86 & 7.5 & 8.70873 & -1.20873 \tabularnewline
87 & 4.5 & 9.06162 & -4.56162 \tabularnewline
88 & 0 & 1.29179 & -1.29179 \tabularnewline
89 & 3.5 & 3.33448 & 0.165518 \tabularnewline
90 & 5.5 & 5.44962 & 0.0503761 \tabularnewline
91 & 5 & 5.64231 & -0.642305 \tabularnewline
92 & 4.5 & 6.57925 & -2.07925 \tabularnewline
93 & 2.5 & -0.212975 & 2.71297 \tabularnewline
94 & 7.5 & 5.44152 & 2.05848 \tabularnewline
95 & 7 & 12.0475 & -5.04753 \tabularnewline
96 & 0 & 0.466872 & -0.466872 \tabularnewline
97 & 4.5 & 7.23217 & -2.73217 \tabularnewline
98 & 3 & 7.05546 & -4.05546 \tabularnewline
99 & 1.5 & 2.54336 & -1.04336 \tabularnewline
100 & 3.5 & 6.64297 & -3.14297 \tabularnewline
101 & 2.5 & 2.10482 & 0.395176 \tabularnewline
102 & 5.5 & 2.93319 & 2.56681 \tabularnewline
103 & 8 & 11.6821 & -3.68207 \tabularnewline
104 & 1 & 1.35512 & -0.355124 \tabularnewline
105 & 5 & 5.99274 & -0.992742 \tabularnewline
106 & 4.5 & 6.27138 & -1.77138 \tabularnewline
107 & 3 & 4.71662 & -1.71662 \tabularnewline
108 & 3 & 0.565458 & 2.43454 \tabularnewline
109 & 8 & 10.1191 & -2.11907 \tabularnewline
110 & 2.5 & 0.345152 & 2.15485 \tabularnewline
111 & 7 & 11.9871 & -4.98712 \tabularnewline
112 & 0 & 4.07196 & -4.07196 \tabularnewline
113 & 1 & 2.22191 & -1.22191 \tabularnewline
114 & 3.5 & 2.78789 & 0.71211 \tabularnewline
115 & 5.5 & 4.68269 & 0.817312 \tabularnewline
116 & 5.5 & 9.9129 & -4.4129 \tabularnewline
117 & 0.5 & -0.436144 & 0.936144 \tabularnewline
118 & 7.5 & 5.48492 & 2.01508 \tabularnewline
119 & 9 & 6.65504 & 2.34496 \tabularnewline
120 & 9.5 & 9.03516 & 0.464838 \tabularnewline
121 & 8.5 & 6.26979 & 2.23021 \tabularnewline
122 & 7 & 10.2624 & -3.26238 \tabularnewline
123 & 8 & 5.2554 & 2.7446 \tabularnewline
124 & 10 & 12.0244 & -2.02444 \tabularnewline
125 & 7 & 3.69388 & 3.30612 \tabularnewline
126 & 8.5 & 8.34919 & 0.150811 \tabularnewline
127 & 9 & 5.20121 & 3.79879 \tabularnewline
128 & 9.5 & 12.9437 & -3.44374 \tabularnewline
129 & 4 & 4.74232 & -0.742321 \tabularnewline
130 & 6 & 5.3309 & 0.6691 \tabularnewline
131 & 8 & 11.4856 & -3.48558 \tabularnewline
132 & 5.5 & 3.5967 & 1.9033 \tabularnewline
133 & 9.5 & 7.90045 & 1.59955 \tabularnewline
134 & 7.5 & 5.99044 & 1.50956 \tabularnewline
135 & 7 & 8.27411 & -1.27411 \tabularnewline
136 & 7.5 & 5.9809 & 1.5191 \tabularnewline
137 & 8 & 7.93117 & 0.0688295 \tabularnewline
138 & 7 & 6.15655 & 0.84345 \tabularnewline
139 & 7 & 8.57899 & -1.57899 \tabularnewline
140 & 6 & 2.67579 & 3.32421 \tabularnewline
141 & 10 & 13.9438 & -3.94383 \tabularnewline
142 & 2.5 & 2.31062 & 0.189382 \tabularnewline
143 & 9 & 10.3569 & -1.35693 \tabularnewline
144 & 8 & 7.46271 & 0.537292 \tabularnewline
145 & 6 & 2.59552 & 3.40448 \tabularnewline
146 & 8.5 & 8.6315 & -0.131505 \tabularnewline
147 & 6 & 5.16911 & 0.830885 \tabularnewline
148 & 9 & 7.46517 & 1.53483 \tabularnewline
149 & 8 & 7.13601 & 0.863987 \tabularnewline
150 & 8 & 6.09182 & 1.90818 \tabularnewline
151 & 9 & 9.57779 & -0.577789 \tabularnewline
152 & 5.5 & 6.0028 & -0.502802 \tabularnewline
153 & 5 & 4.52456 & 0.475442 \tabularnewline
154 & 7 & 10.6018 & -3.60179 \tabularnewline
155 & 5.5 & 4.27338 & 1.22662 \tabularnewline
156 & 9 & 14.09 & -5.08997 \tabularnewline
157 & 2 & 0.288019 & 1.71198 \tabularnewline
158 & 8.5 & 6.99261 & 1.50739 \tabularnewline
159 & 9 & 8.95769 & 0.0423087 \tabularnewline
160 & 8.5 & 5.87315 & 2.62685 \tabularnewline
161 & 9 & 8.47976 & 0.520241 \tabularnewline
162 & 7.5 & 5.21591 & 2.28409 \tabularnewline
163 & 10 & 8.21096 & 1.78904 \tabularnewline
164 & 9 & 10.4315 & -1.43154 \tabularnewline
165 & 7.5 & 7.59655 & -0.0965496 \tabularnewline
166 & 6 & 1.50841 & 4.49159 \tabularnewline
167 & 10.5 & 11.362 & -0.861969 \tabularnewline
168 & 8.5 & 6.79375 & 1.70625 \tabularnewline
169 & 8 & 3.96906 & 4.03094 \tabularnewline
170 & 10 & 6.17576 & 3.82424 \tabularnewline
171 & 10.5 & 9.05328 & 1.44672 \tabularnewline
172 & 6.5 & 4.86047 & 1.63953 \tabularnewline
173 & 9.5 & 5.77824 & 3.72176 \tabularnewline
174 & 8.5 & 8.88434 & -0.384336 \tabularnewline
175 & 7.5 & 9.67932 & -2.17932 \tabularnewline
176 & 5 & 4.62131 & 0.378687 \tabularnewline
177 & 8 & 4.3087 & 3.6913 \tabularnewline
178 & 10 & 8.7487 & 1.2513 \tabularnewline
179 & 7 & 7.23295 & -0.232948 \tabularnewline
180 & 7.5 & 7.73295 & -0.232948 \tabularnewline
181 & 7.5 & 4.55298 & 2.94702 \tabularnewline
182 & 9.5 & 10.142 & -0.641982 \tabularnewline
183 & 6 & 4.13276 & 1.86724 \tabularnewline
184 & 10 & 8.86701 & 1.13299 \tabularnewline
185 & 7 & 10.3071 & -3.3071 \tabularnewline
186 & 3 & 3.90861 & -0.908609 \tabularnewline
187 & 6 & 5.43855 & 0.561445 \tabularnewline
188 & 7 & 5.45527 & 1.54473 \tabularnewline
189 & 10 & 9.80949 & 0.190514 \tabularnewline
190 & 7 & 8.78846 & -1.78846 \tabularnewline
191 & 3.5 & 2.21092 & 1.28908 \tabularnewline
192 & 8 & 3.76927 & 4.23073 \tabularnewline
193 & 10 & 10.2146 & -0.214554 \tabularnewline
194 & 5.5 & 3.57297 & 1.92703 \tabularnewline
195 & 6 & 5.96054 & 0.0394553 \tabularnewline
196 & 6.5 & 5.74346 & 0.756536 \tabularnewline
197 & 6.5 & 4.0339 & 2.4661 \tabularnewline
198 & 8.5 & 9.8325 & -1.3325 \tabularnewline
199 & 4 & 0.839204 & 3.1608 \tabularnewline
200 & 9.5 & 7.47978 & 2.02022 \tabularnewline
201 & 8 & 7.08779 & 0.912205 \tabularnewline
202 & 8.5 & 11.3894 & -2.88943 \tabularnewline
203 & 5.5 & 5.48772 & 0.0122773 \tabularnewline
204 & 7 & 3.38125 & 3.61875 \tabularnewline
205 & 9 & 7.01367 & 1.98633 \tabularnewline
206 & 8 & 5.96182 & 2.03818 \tabularnewline
207 & 10 & 8.01632 & 1.98368 \tabularnewline
208 & 8 & 8.12163 & -0.121625 \tabularnewline
209 & 6 & 5.59484 & 0.405161 \tabularnewline
210 & 8 & 8.59158 & -0.591584 \tabularnewline
211 & 5 & 1.40666 & 3.59334 \tabularnewline
212 & 9 & 11.5635 & -2.56346 \tabularnewline
213 & 4.5 & 1.5769 & 2.9231 \tabularnewline
214 & 8.5 & 7.65585 & 0.844152 \tabularnewline
215 & 7 & 5.76567 & 1.23433 \tabularnewline
216 & 9.5 & 8.04153 & 1.45847 \tabularnewline
217 & 8.5 & 5.91432 & 2.58568 \tabularnewline
218 & 7.5 & 5.88212 & 1.61788 \tabularnewline
219 & 7.5 & 10.0899 & -2.58995 \tabularnewline
220 & 5 & 6.4291 & -1.4291 \tabularnewline
221 & 7 & 7.49068 & -0.490676 \tabularnewline
222 & 8 & 9.02326 & -1.02326 \tabularnewline
223 & 5.5 & 3.26972 & 2.23028 \tabularnewline
224 & 8.5 & 7.1477 & 1.3523 \tabularnewline
225 & 7.5 & 4.92756 & 2.57244 \tabularnewline
226 & 9.5 & 8.21948 & 1.28052 \tabularnewline
227 & 7 & 6.77356 & 0.226443 \tabularnewline
228 & 8 & 7.45288 & 0.547123 \tabularnewline
229 & 8.5 & 11.5312 & -3.03117 \tabularnewline
230 & 3.5 & 2.52312 & 0.976884 \tabularnewline
231 & 6.5 & 5.14167 & 1.35833 \tabularnewline
232 & 6.5 & 3.81421 & 2.68579 \tabularnewline
233 & 10.5 & 7.97458 & 2.52542 \tabularnewline
234 & 8.5 & 6.82184 & 1.67816 \tabularnewline
235 & 8 & 4.11219 & 3.88781 \tabularnewline
236 & 10 & 7.40399 & 2.59601 \tabularnewline
237 & 10 & 7.76622 & 2.23378 \tabularnewline
238 & 9.5 & 6.26946 & 3.23054 \tabularnewline
239 & 9 & 7.3948 & 1.6052 \tabularnewline
240 & 10 & 8.14661 & 1.85339 \tabularnewline
241 & 7.5 & 8.77386 & -1.27386 \tabularnewline
242 & 4.5 & 5.49669 & -0.996685 \tabularnewline
243 & 4.5 & 9.66742 & -5.16742 \tabularnewline
244 & 0.5 & -0.716852 & 1.21685 \tabularnewline
245 & 6.5 & 9.64446 & -3.14446 \tabularnewline
246 & 4.5 & 5.89676 & -1.39676 \tabularnewline
247 & 5.5 & 5.92505 & -0.425051 \tabularnewline
248 & 5 & 6.45896 & -1.45896 \tabularnewline
249 & 6 & 9.24275 & -3.24275 \tabularnewline
250 & 4 & 1.36681 & 2.63319 \tabularnewline
251 & 8 & 4.17576 & 3.82424 \tabularnewline
252 & 10.5 & 7.39616 & 3.10384 \tabularnewline
253 & 8.5 & 7.60522 & 0.894778 \tabularnewline
254 & 6.5 & 6.26036 & 0.239642 \tabularnewline
255 & 8 & 7.19668 & 0.803318 \tabularnewline
256 & 8.5 & 8.70981 & -0.209807 \tabularnewline
257 & 5.5 & 6.09879 & -0.598795 \tabularnewline
258 & 7 & 8.16944 & -1.16944 \tabularnewline
259 & 5 & 7.02966 & -2.02966 \tabularnewline
260 & 3.5 & 5.84244 & -2.34244 \tabularnewline
261 & 5 & 3.44307 & 1.55693 \tabularnewline
262 & 9 & 7.06947 & 1.93053 \tabularnewline
263 & 8.5 & 9.66205 & -1.16205 \tabularnewline
264 & 5 & 3.22276 & 1.77724 \tabularnewline
265 & 9.5 & 11.3311 & -1.83113 \tabularnewline
266 & 3 & 8.98103 & -5.98103 \tabularnewline
267 & 1.5 & 0.689889 & 0.810111 \tabularnewline
268 & 6 & 10.7313 & -4.73125 \tabularnewline
269 & 0.5 & -0.946718 & 1.44672 \tabularnewline
270 & 6.5 & 4.7828 & 1.7172 \tabularnewline
271 & 7.5 & 8.96769 & -1.46769 \tabularnewline
272 & 4.5 & 1.86681 & 2.63319 \tabularnewline
273 & 8 & 6.3433 & 1.6567 \tabularnewline
274 & 9 & 8.20365 & 0.796351 \tabularnewline
275 & 7.5 & 5.83523 & 1.66477 \tabularnewline
276 & 8.5 & 6.69845 & 1.80155 \tabularnewline
277 & 7 & 3.20391 & 3.79609 \tabularnewline
278 & 9.5 & 8.05819 & 1.44181 \tabularnewline
279 & 6.5 & 2.28348 & 4.21652 \tabularnewline
280 & 9.5 & 8.85803 & 0.641969 \tabularnewline
281 & 6 & 5.07693 & 0.923073 \tabularnewline
282 & 8 & 6.9181 & 1.0819 \tabularnewline
283 & 9.5 & 7.59076 & 1.90924 \tabularnewline
284 & 8 & 6.34824 & 1.65176 \tabularnewline
285 & 8 & 6.24028 & 1.75972 \tabularnewline
286 & 9 & 9.60434 & -0.604337 \tabularnewline
287 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268752&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]5.21639[/C][C]2.28361[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]4.93186[/C][C]-2.43186[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]4.97985[/C][C]1.02015[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]5.32629[/C][C]1.17371[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.54247[/C][C]-4.54247[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]5.03644[/C][C]-4.03644[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]6.53919[/C][C]-1.03919[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]5.54685[/C][C]2.95315[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]5.70115[/C][C]0.798848[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]5.34422[/C][C]-0.844222[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]6.4725[/C][C]-4.4725[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]5.67143[/C][C]-0.671433[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]6.74847[/C][C]-6.24847[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]5.22334[/C][C]-0.223342[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]5.84731[/C][C]-0.847313[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]4.73705[/C][C]-2.23705[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]5.35543[/C][C]-0.355431[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]6.18003[/C][C]-0.680034[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]5.53505[/C][C]-2.03505[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]5.47972[/C][C]-2.47972[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]5.24343[/C][C]-1.24343[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]5.03564[/C][C]-4.53564[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]5.56515[/C][C]0.934848[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]5.38146[/C][C]-0.881463[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]4.93781[/C][C]2.56219[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]5.58956[/C][C]-0.0895597[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]6.25098[/C][C]-2.25098[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]5.81188[/C][C]1.68812[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]5.21877[/C][C]1.78123[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]4.72226[/C][C]-0.722263[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]5.34746[/C][C]0.15254[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]5.68993[/C][C]-3.18993[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]6.03346[/C][C]-0.533458[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]5.14229[/C][C]-4.64229[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]5.61445[/C][C]-2.11445[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]6.43388[/C][C]-3.93388[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.94678[/C][C]-1.44678[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]6.16854[/C][C]-1.66854[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]5.08276[/C][C]-0.582757[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.81633[/C][C]0.183666[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]5.07629[/C][C]-2.57629[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.58842[/C][C]-1.58842[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]4.72039[/C][C]-4.72039[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.42746[/C][C]-1.42746[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]4.88622[/C][C]1.61378[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]5.51556[/C][C]-0.515556[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]5.09887[/C][C]0.901127[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]5.69801[/C][C]-1.19801[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]5.9206[/C][C]-0.420599[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]5.11[/C][C]-4.11[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]4.46688[/C][C]3.03312[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]5.10519[/C][C]0.894813[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.54506[/C][C]-0.54506[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]5.68618[/C][C]-4.68618[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]6.04007[/C][C]-1.04007[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]5.63629[/C][C]0.863711[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]6.37159[/C][C]0.628407[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]6.4503[/C][C]-1.9503[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]5.27512[/C][C]-5.27512[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]5.45405[/C][C]3.04595[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.6739[/C][C]-1.1739[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]5.58279[/C][C]1.91721[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]5.52484[/C][C]-2.02484[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]4.85057[/C][C]1.14943[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]4.96526[/C][C]-3.46526[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]5.85926[/C][C]3.14074[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]4.50211[/C][C]-1.00211[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]5.10644[/C][C]-1.60644[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]6.121[/C][C]-2.121[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]5.62605[/C][C]0.873953[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]5.33518[/C][C]2.16482[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]5.03203[/C][C]0.967974[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]5.74671[/C][C]-0.746709[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]5.03664[/C][C]0.463365[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]5.49559[/C][C]-1.99559[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]5.01532[/C][C]2.48468[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]5.28614[/C][C]-4.28614[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.94532[/C][C]0.554685[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]0.366813[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]5.13145[/C][C]1.36855[/C][/ROW]
[ROW][C]81[/C][C]6.5[/C][C]6.35802[/C][C]0.141979[/C][/ROW]
[ROW][C]82[/C][C]7[/C][C]8.93614[/C][C]-1.93614[/C][/ROW]
[ROW][C]83[/C][C]3.5[/C][C]7.24188[/C][C]-3.74188[/C][/ROW]
[ROW][C]84[/C][C]1.5[/C][C]2.33687[/C][C]-0.836868[/C][/ROW]
[ROW][C]85[/C][C]4[/C][C]1.19037[/C][C]2.80963[/C][/ROW]
[ROW][C]86[/C][C]7.5[/C][C]8.70873[/C][C]-1.20873[/C][/ROW]
[ROW][C]87[/C][C]4.5[/C][C]9.06162[/C][C]-4.56162[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]1.29179[/C][C]-1.29179[/C][/ROW]
[ROW][C]89[/C][C]3.5[/C][C]3.33448[/C][C]0.165518[/C][/ROW]
[ROW][C]90[/C][C]5.5[/C][C]5.44962[/C][C]0.0503761[/C][/ROW]
[ROW][C]91[/C][C]5[/C][C]5.64231[/C][C]-0.642305[/C][/ROW]
[ROW][C]92[/C][C]4.5[/C][C]6.57925[/C][C]-2.07925[/C][/ROW]
[ROW][C]93[/C][C]2.5[/C][C]-0.212975[/C][C]2.71297[/C][/ROW]
[ROW][C]94[/C][C]7.5[/C][C]5.44152[/C][C]2.05848[/C][/ROW]
[ROW][C]95[/C][C]7[/C][C]12.0475[/C][C]-5.04753[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.466872[/C][C]-0.466872[/C][/ROW]
[ROW][C]97[/C][C]4.5[/C][C]7.23217[/C][C]-2.73217[/C][/ROW]
[ROW][C]98[/C][C]3[/C][C]7.05546[/C][C]-4.05546[/C][/ROW]
[ROW][C]99[/C][C]1.5[/C][C]2.54336[/C][C]-1.04336[/C][/ROW]
[ROW][C]100[/C][C]3.5[/C][C]6.64297[/C][C]-3.14297[/C][/ROW]
[ROW][C]101[/C][C]2.5[/C][C]2.10482[/C][C]0.395176[/C][/ROW]
[ROW][C]102[/C][C]5.5[/C][C]2.93319[/C][C]2.56681[/C][/ROW]
[ROW][C]103[/C][C]8[/C][C]11.6821[/C][C]-3.68207[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]1.35512[/C][C]-0.355124[/C][/ROW]
[ROW][C]105[/C][C]5[/C][C]5.99274[/C][C]-0.992742[/C][/ROW]
[ROW][C]106[/C][C]4.5[/C][C]6.27138[/C][C]-1.77138[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]4.71662[/C][C]-1.71662[/C][/ROW]
[ROW][C]108[/C][C]3[/C][C]0.565458[/C][C]2.43454[/C][/ROW]
[ROW][C]109[/C][C]8[/C][C]10.1191[/C][C]-2.11907[/C][/ROW]
[ROW][C]110[/C][C]2.5[/C][C]0.345152[/C][C]2.15485[/C][/ROW]
[ROW][C]111[/C][C]7[/C][C]11.9871[/C][C]-4.98712[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]4.07196[/C][C]-4.07196[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]2.22191[/C][C]-1.22191[/C][/ROW]
[ROW][C]114[/C][C]3.5[/C][C]2.78789[/C][C]0.71211[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]4.68269[/C][C]0.817312[/C][/ROW]
[ROW][C]116[/C][C]5.5[/C][C]9.9129[/C][C]-4.4129[/C][/ROW]
[ROW][C]117[/C][C]0.5[/C][C]-0.436144[/C][C]0.936144[/C][/ROW]
[ROW][C]118[/C][C]7.5[/C][C]5.48492[/C][C]2.01508[/C][/ROW]
[ROW][C]119[/C][C]9[/C][C]6.65504[/C][C]2.34496[/C][/ROW]
[ROW][C]120[/C][C]9.5[/C][C]9.03516[/C][C]0.464838[/C][/ROW]
[ROW][C]121[/C][C]8.5[/C][C]6.26979[/C][C]2.23021[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]10.2624[/C][C]-3.26238[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]5.2554[/C][C]2.7446[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]12.0244[/C][C]-2.02444[/C][/ROW]
[ROW][C]125[/C][C]7[/C][C]3.69388[/C][C]3.30612[/C][/ROW]
[ROW][C]126[/C][C]8.5[/C][C]8.34919[/C][C]0.150811[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]5.20121[/C][C]3.79879[/C][/ROW]
[ROW][C]128[/C][C]9.5[/C][C]12.9437[/C][C]-3.44374[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]4.74232[/C][C]-0.742321[/C][/ROW]
[ROW][C]130[/C][C]6[/C][C]5.3309[/C][C]0.6691[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]11.4856[/C][C]-3.48558[/C][/ROW]
[ROW][C]132[/C][C]5.5[/C][C]3.5967[/C][C]1.9033[/C][/ROW]
[ROW][C]133[/C][C]9.5[/C][C]7.90045[/C][C]1.59955[/C][/ROW]
[ROW][C]134[/C][C]7.5[/C][C]5.99044[/C][C]1.50956[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]8.27411[/C][C]-1.27411[/C][/ROW]
[ROW][C]136[/C][C]7.5[/C][C]5.9809[/C][C]1.5191[/C][/ROW]
[ROW][C]137[/C][C]8[/C][C]7.93117[/C][C]0.0688295[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]6.15655[/C][C]0.84345[/C][/ROW]
[ROW][C]139[/C][C]7[/C][C]8.57899[/C][C]-1.57899[/C][/ROW]
[ROW][C]140[/C][C]6[/C][C]2.67579[/C][C]3.32421[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.9438[/C][C]-3.94383[/C][/ROW]
[ROW][C]142[/C][C]2.5[/C][C]2.31062[/C][C]0.189382[/C][/ROW]
[ROW][C]143[/C][C]9[/C][C]10.3569[/C][C]-1.35693[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]7.46271[/C][C]0.537292[/C][/ROW]
[ROW][C]145[/C][C]6[/C][C]2.59552[/C][C]3.40448[/C][/ROW]
[ROW][C]146[/C][C]8.5[/C][C]8.6315[/C][C]-0.131505[/C][/ROW]
[ROW][C]147[/C][C]6[/C][C]5.16911[/C][C]0.830885[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]7.46517[/C][C]1.53483[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]7.13601[/C][C]0.863987[/C][/ROW]
[ROW][C]150[/C][C]8[/C][C]6.09182[/C][C]1.90818[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]9.57779[/C][C]-0.577789[/C][/ROW]
[ROW][C]152[/C][C]5.5[/C][C]6.0028[/C][C]-0.502802[/C][/ROW]
[ROW][C]153[/C][C]5[/C][C]4.52456[/C][C]0.475442[/C][/ROW]
[ROW][C]154[/C][C]7[/C][C]10.6018[/C][C]-3.60179[/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]14.09[/C][C]-5.08997[/C][/ROW]
[ROW][C]157[/C][C]2[/C][C]0.288019[/C][C]1.71198[/C][/ROW]
[ROW][C]158[/C][C]8.5[/C][C]6.99261[/C][C]1.50739[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.95769[/C][C]0.0423087[/C][/ROW]
[ROW][C]160[/C][C]8.5[/C][C]5.87315[/C][C]2.62685[/C][/ROW]
[ROW][C]161[/C][C]9[/C][C]8.47976[/C][C]0.520241[/C][/ROW]
[ROW][C]162[/C][C]7.5[/C][C]5.21591[/C][C]2.28409[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]8.21096[/C][C]1.78904[/C][/ROW]
[ROW][C]164[/C][C]9[/C][C]10.4315[/C][C]-1.43154[/C][/ROW]
[ROW][C]165[/C][C]7.5[/C][C]7.59655[/C][C]-0.0965496[/C][/ROW]
[ROW][C]166[/C][C]6[/C][C]1.50841[/C][C]4.49159[/C][/ROW]
[ROW][C]167[/C][C]10.5[/C][C]11.362[/C][C]-0.861969[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]6.79375[/C][C]1.70625[/C][/ROW]
[ROW][C]169[/C][C]8[/C][C]3.96906[/C][C]4.03094[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]6.17576[/C][C]3.82424[/C][/ROW]
[ROW][C]171[/C][C]10.5[/C][C]9.05328[/C][C]1.44672[/C][/ROW]
[ROW][C]172[/C][C]6.5[/C][C]4.86047[/C][C]1.63953[/C][/ROW]
[ROW][C]173[/C][C]9.5[/C][C]5.77824[/C][C]3.72176[/C][/ROW]
[ROW][C]174[/C][C]8.5[/C][C]8.88434[/C][C]-0.384336[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]9.67932[/C][C]-2.17932[/C][/ROW]
[ROW][C]176[/C][C]5[/C][C]4.62131[/C][C]0.378687[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]4.3087[/C][C]3.6913[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.7487[/C][C]1.2513[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]7.23295[/C][C]-0.232948[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]7.73295[/C][C]-0.232948[/C][/ROW]
[ROW][C]181[/C][C]7.5[/C][C]4.55298[/C][C]2.94702[/C][/ROW]
[ROW][C]182[/C][C]9.5[/C][C]10.142[/C][C]-0.641982[/C][/ROW]
[ROW][C]183[/C][C]6[/C][C]4.13276[/C][C]1.86724[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]8.86701[/C][C]1.13299[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]10.3071[/C][C]-3.3071[/C][/ROW]
[ROW][C]186[/C][C]3[/C][C]3.90861[/C][C]-0.908609[/C][/ROW]
[ROW][C]187[/C][C]6[/C][C]5.43855[/C][C]0.561445[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]5.45527[/C][C]1.54473[/C][/ROW]
[ROW][C]189[/C][C]10[/C][C]9.80949[/C][C]0.190514[/C][/ROW]
[ROW][C]190[/C][C]7[/C][C]8.78846[/C][C]-1.78846[/C][/ROW]
[ROW][C]191[/C][C]3.5[/C][C]2.21092[/C][C]1.28908[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]3.76927[/C][C]4.23073[/C][/ROW]
[ROW][C]193[/C][C]10[/C][C]10.2146[/C][C]-0.214554[/C][/ROW]
[ROW][C]194[/C][C]5.5[/C][C]3.57297[/C][C]1.92703[/C][/ROW]
[ROW][C]195[/C][C]6[/C][C]5.96054[/C][C]0.0394553[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]5.74346[/C][C]0.756536[/C][/ROW]
[ROW][C]197[/C][C]6.5[/C][C]4.0339[/C][C]2.4661[/C][/ROW]
[ROW][C]198[/C][C]8.5[/C][C]9.8325[/C][C]-1.3325[/C][/ROW]
[ROW][C]199[/C][C]4[/C][C]0.839204[/C][C]3.1608[/C][/ROW]
[ROW][C]200[/C][C]9.5[/C][C]7.47978[/C][C]2.02022[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]7.08779[/C][C]0.912205[/C][/ROW]
[ROW][C]202[/C][C]8.5[/C][C]11.3894[/C][C]-2.88943[/C][/ROW]
[ROW][C]203[/C][C]5.5[/C][C]5.48772[/C][C]0.0122773[/C][/ROW]
[ROW][C]204[/C][C]7[/C][C]3.38125[/C][C]3.61875[/C][/ROW]
[ROW][C]205[/C][C]9[/C][C]7.01367[/C][C]1.98633[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]5.96182[/C][C]2.03818[/C][/ROW]
[ROW][C]207[/C][C]10[/C][C]8.01632[/C][C]1.98368[/C][/ROW]
[ROW][C]208[/C][C]8[/C][C]8.12163[/C][C]-0.121625[/C][/ROW]
[ROW][C]209[/C][C]6[/C][C]5.59484[/C][C]0.405161[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]8.59158[/C][C]-0.591584[/C][/ROW]
[ROW][C]211[/C][C]5[/C][C]1.40666[/C][C]3.59334[/C][/ROW]
[ROW][C]212[/C][C]9[/C][C]11.5635[/C][C]-2.56346[/C][/ROW]
[ROW][C]213[/C][C]4.5[/C][C]1.5769[/C][C]2.9231[/C][/ROW]
[ROW][C]214[/C][C]8.5[/C][C]7.65585[/C][C]0.844152[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]5.76567[/C][C]1.23433[/C][/ROW]
[ROW][C]216[/C][C]9.5[/C][C]8.04153[/C][C]1.45847[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]5.91432[/C][C]2.58568[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]5.88212[/C][C]1.61788[/C][/ROW]
[ROW][C]219[/C][C]7.5[/C][C]10.0899[/C][C]-2.58995[/C][/ROW]
[ROW][C]220[/C][C]5[/C][C]6.4291[/C][C]-1.4291[/C][/ROW]
[ROW][C]221[/C][C]7[/C][C]7.49068[/C][C]-0.490676[/C][/ROW]
[ROW][C]222[/C][C]8[/C][C]9.02326[/C][C]-1.02326[/C][/ROW]
[ROW][C]223[/C][C]5.5[/C][C]3.26972[/C][C]2.23028[/C][/ROW]
[ROW][C]224[/C][C]8.5[/C][C]7.1477[/C][C]1.3523[/C][/ROW]
[ROW][C]225[/C][C]7.5[/C][C]4.92756[/C][C]2.57244[/C][/ROW]
[ROW][C]226[/C][C]9.5[/C][C]8.21948[/C][C]1.28052[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]6.77356[/C][C]0.226443[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]7.45288[/C][C]0.547123[/C][/ROW]
[ROW][C]229[/C][C]8.5[/C][C]11.5312[/C][C]-3.03117[/C][/ROW]
[ROW][C]230[/C][C]3.5[/C][C]2.52312[/C][C]0.976884[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]5.14167[/C][C]1.35833[/C][/ROW]
[ROW][C]232[/C][C]6.5[/C][C]3.81421[/C][C]2.68579[/C][/ROW]
[ROW][C]233[/C][C]10.5[/C][C]7.97458[/C][C]2.52542[/C][/ROW]
[ROW][C]234[/C][C]8.5[/C][C]6.82184[/C][C]1.67816[/C][/ROW]
[ROW][C]235[/C][C]8[/C][C]4.11219[/C][C]3.88781[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]7.40399[/C][C]2.59601[/C][/ROW]
[ROW][C]237[/C][C]10[/C][C]7.76622[/C][C]2.23378[/C][/ROW]
[ROW][C]238[/C][C]9.5[/C][C]6.26946[/C][C]3.23054[/C][/ROW]
[ROW][C]239[/C][C]9[/C][C]7.3948[/C][C]1.6052[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]8.14661[/C][C]1.85339[/C][/ROW]
[ROW][C]241[/C][C]7.5[/C][C]8.77386[/C][C]-1.27386[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]5.49669[/C][C]-0.996685[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]9.66742[/C][C]-5.16742[/C][/ROW]
[ROW][C]244[/C][C]0.5[/C][C]-0.716852[/C][C]1.21685[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]9.64446[/C][C]-3.14446[/C][/ROW]
[ROW][C]246[/C][C]4.5[/C][C]5.89676[/C][C]-1.39676[/C][/ROW]
[ROW][C]247[/C][C]5.5[/C][C]5.92505[/C][C]-0.425051[/C][/ROW]
[ROW][C]248[/C][C]5[/C][C]6.45896[/C][C]-1.45896[/C][/ROW]
[ROW][C]249[/C][C]6[/C][C]9.24275[/C][C]-3.24275[/C][/ROW]
[ROW][C]250[/C][C]4[/C][C]1.36681[/C][C]2.63319[/C][/ROW]
[ROW][C]251[/C][C]8[/C][C]4.17576[/C][C]3.82424[/C][/ROW]
[ROW][C]252[/C][C]10.5[/C][C]7.39616[/C][C]3.10384[/C][/ROW]
[ROW][C]253[/C][C]8.5[/C][C]7.60522[/C][C]0.894778[/C][/ROW]
[ROW][C]254[/C][C]6.5[/C][C]6.26036[/C][C]0.239642[/C][/ROW]
[ROW][C]255[/C][C]8[/C][C]7.19668[/C][C]0.803318[/C][/ROW]
[ROW][C]256[/C][C]8.5[/C][C]8.70981[/C][C]-0.209807[/C][/ROW]
[ROW][C]257[/C][C]5.5[/C][C]6.09879[/C][C]-0.598795[/C][/ROW]
[ROW][C]258[/C][C]7[/C][C]8.16944[/C][C]-1.16944[/C][/ROW]
[ROW][C]259[/C][C]5[/C][C]7.02966[/C][C]-2.02966[/C][/ROW]
[ROW][C]260[/C][C]3.5[/C][C]5.84244[/C][C]-2.34244[/C][/ROW]
[ROW][C]261[/C][C]5[/C][C]3.44307[/C][C]1.55693[/C][/ROW]
[ROW][C]262[/C][C]9[/C][C]7.06947[/C][C]1.93053[/C][/ROW]
[ROW][C]263[/C][C]8.5[/C][C]9.66205[/C][C]-1.16205[/C][/ROW]
[ROW][C]264[/C][C]5[/C][C]3.22276[/C][C]1.77724[/C][/ROW]
[ROW][C]265[/C][C]9.5[/C][C]11.3311[/C][C]-1.83113[/C][/ROW]
[ROW][C]266[/C][C]3[/C][C]8.98103[/C][C]-5.98103[/C][/ROW]
[ROW][C]267[/C][C]1.5[/C][C]0.689889[/C][C]0.810111[/C][/ROW]
[ROW][C]268[/C][C]6[/C][C]10.7313[/C][C]-4.73125[/C][/ROW]
[ROW][C]269[/C][C]0.5[/C][C]-0.946718[/C][C]1.44672[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]4.7828[/C][C]1.7172[/C][/ROW]
[ROW][C]271[/C][C]7.5[/C][C]8.96769[/C][C]-1.46769[/C][/ROW]
[ROW][C]272[/C][C]4.5[/C][C]1.86681[/C][C]2.63319[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]6.3433[/C][C]1.6567[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]8.20365[/C][C]0.796351[/C][/ROW]
[ROW][C]275[/C][C]7.5[/C][C]5.83523[/C][C]1.66477[/C][/ROW]
[ROW][C]276[/C][C]8.5[/C][C]6.69845[/C][C]1.80155[/C][/ROW]
[ROW][C]277[/C][C]7[/C][C]3.20391[/C][C]3.79609[/C][/ROW]
[ROW][C]278[/C][C]9.5[/C][C]8.05819[/C][C]1.44181[/C][/ROW]
[ROW][C]279[/C][C]6.5[/C][C]2.28348[/C][C]4.21652[/C][/ROW]
[ROW][C]280[/C][C]9.5[/C][C]8.85803[/C][C]0.641969[/C][/ROW]
[ROW][C]281[/C][C]6[/C][C]5.07693[/C][C]0.923073[/C][/ROW]
[ROW][C]282[/C][C]8[/C][C]6.9181[/C][C]1.0819[/C][/ROW]
[ROW][C]283[/C][C]9.5[/C][C]7.59076[/C][C]1.90924[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.34824[/C][C]1.65176[/C][/ROW]
[ROW][C]285[/C][C]8[/C][C]6.24028[/C][C]1.75972[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]9.60434[/C][C]-0.604337[/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=268752&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268752&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
17.55.216392.28361
22.54.93186-2.43186
364.979851.02015
46.55.326291.17371
515.54247-4.54247
615.03644-4.03644
75.56.53919-1.03919
88.55.546852.95315
96.55.701150.798848
104.55.34422-0.844222
1126.4725-4.4725
1255.67143-0.671433
130.56.74847-6.24847
1455.22334-0.223342
1555.84731-0.847313
162.54.73705-2.23705
1755.35543-0.355431
185.56.18003-0.680034
193.55.53505-2.03505
2035.47972-2.47972
2145.24343-1.24343
220.55.03564-4.53564
236.55.565150.934848
244.55.38146-0.881463
257.54.937812.56219
265.55.58956-0.0895597
2746.25098-2.25098
287.55.811881.68812
2975.218771.78123
3044.72226-0.722263
315.55.347460.15254
322.55.68993-3.18993
335.56.03346-0.533458
340.55.14229-4.64229
353.55.61445-2.11445
362.56.43388-3.93388
374.55.94678-1.44678
384.56.16854-1.66854
394.55.08276-0.582757
4065.816330.183666
412.55.07629-2.57629
4256.58842-1.58842
4304.72039-4.72039
4456.42746-1.42746
456.54.886221.61378
4655.51556-0.515556
4765.098870.901127
484.55.69801-1.19801
495.55.9206-0.420599
5015.11-4.11
517.54.466883.03312
5265.105190.894813
5355.54506-0.54506
5415.68618-4.68618
5556.04007-1.04007
566.55.636290.863711
5776.371590.628407
584.56.4503-1.9503
5905.27512-5.27512
608.55.454053.04595
613.54.6739-1.1739
627.55.582791.91721
633.55.52484-2.02484
6464.850571.14943
651.54.96526-3.46526
6695.859263.14074
673.54.50211-1.00211
683.55.10644-1.60644
6946.121-2.121
706.55.626050.873953
717.55.335182.16482
7265.032030.967974
7355.74671-0.746709
745.55.036640.463365
753.55.49559-1.99559
767.55.015322.48468
7715.28614-4.28614
786.55.945320.554685
79NANA0.366813
806.55.131451.36855
816.56.358020.141979
8278.93614-1.93614
833.57.24188-3.74188
841.52.33687-0.836868
8541.190372.80963
867.58.70873-1.20873
874.59.06162-4.56162
8801.29179-1.29179
893.53.334480.165518
905.55.449620.0503761
9155.64231-0.642305
924.56.57925-2.07925
932.5-0.2129752.71297
947.55.441522.05848
95712.0475-5.04753
9600.466872-0.466872
974.57.23217-2.73217
9837.05546-4.05546
991.52.54336-1.04336
1003.56.64297-3.14297
1012.52.104820.395176
1025.52.933192.56681
103811.6821-3.68207
10411.35512-0.355124
10555.99274-0.992742
1064.56.27138-1.77138
10734.71662-1.71662
10830.5654582.43454
109810.1191-2.11907
1102.50.3451522.15485
111711.9871-4.98712
11204.07196-4.07196
11312.22191-1.22191
1143.52.787890.71211
1155.54.682690.817312
1165.59.9129-4.4129
1170.5-0.4361440.936144
1187.55.484922.01508
11996.655042.34496
1209.59.035160.464838
1218.56.269792.23021
122710.2624-3.26238
12385.25542.7446
1241012.0244-2.02444
12573.693883.30612
1268.58.349190.150811
12795.201213.79879
1289.512.9437-3.44374
12944.74232-0.742321
13065.33090.6691
131811.4856-3.48558
1325.53.59671.9033
1339.57.900451.59955
1347.55.990441.50956
13578.27411-1.27411
1367.55.98091.5191
13787.931170.0688295
13876.156550.84345
13978.57899-1.57899
14062.675793.32421
1411013.9438-3.94383
1422.52.310620.189382
143910.3569-1.35693
14487.462710.537292
14562.595523.40448
1468.58.6315-0.131505
14765.169110.830885
14897.465171.53483
14987.136010.863987
15086.091821.90818
15199.57779-0.577789
1525.56.0028-0.502802
15354.524560.475442
154710.6018-3.60179
1555.54.273381.22662
156914.09-5.08997
15720.2880191.71198
1588.56.992611.50739
15998.957690.0423087
1608.55.873152.62685
16198.479760.520241
1627.55.215912.28409
163108.210961.78904
164910.4315-1.43154
1657.57.59655-0.0965496
16661.508414.49159
16710.511.362-0.861969
1688.56.793751.70625
16983.969064.03094
170106.175763.82424
17110.59.053281.44672
1726.54.860471.63953
1739.55.778243.72176
1748.58.88434-0.384336
1757.59.67932-2.17932
17654.621310.378687
17784.30873.6913
178108.74871.2513
17977.23295-0.232948
1807.57.73295-0.232948
1817.54.552982.94702
1829.510.142-0.641982
18364.132761.86724
184108.867011.13299
185710.3071-3.3071
18633.90861-0.908609
18765.438550.561445
18875.455271.54473
189109.809490.190514
19078.78846-1.78846
1913.52.210921.28908
19283.769274.23073
1931010.2146-0.214554
1945.53.572971.92703
19565.960540.0394553
1966.55.743460.756536
1976.54.03392.4661
1988.59.8325-1.3325
19940.8392043.1608
2009.57.479782.02022
20187.087790.912205
2028.511.3894-2.88943
2035.55.487720.0122773
20473.381253.61875
20597.013671.98633
20685.961822.03818
207108.016321.98368
20888.12163-0.121625
20965.594840.405161
21088.59158-0.591584
21151.406663.59334
212911.5635-2.56346
2134.51.57692.9231
2148.57.655850.844152
21575.765671.23433
2169.58.041531.45847
2178.55.914322.58568
2187.55.882121.61788
2197.510.0899-2.58995
22056.4291-1.4291
22177.49068-0.490676
22289.02326-1.02326
2235.53.269722.23028
2248.57.14771.3523
2257.54.927562.57244
2269.58.219481.28052
22776.773560.226443
22887.452880.547123
2298.511.5312-3.03117
2303.52.523120.976884
2316.55.141671.35833
2326.53.814212.68579
23310.57.974582.52542
2348.56.821841.67816
23584.112193.88781
236107.403992.59601
237107.766222.23378
2389.56.269463.23054
23997.39481.6052
240108.146611.85339
2417.58.77386-1.27386
2424.55.49669-0.996685
2434.59.66742-5.16742
2440.5-0.7168521.21685
2456.59.64446-3.14446
2464.55.89676-1.39676
2475.55.92505-0.425051
24856.45896-1.45896
24969.24275-3.24275
25041.366812.63319
25184.175763.82424
25210.57.396163.10384
2538.57.605220.894778
2546.56.260360.239642
25587.196680.803318
2568.58.70981-0.209807
2575.56.09879-0.598795
25878.16944-1.16944
25957.02966-2.02966
2603.55.84244-2.34244
26153.443071.55693
26297.069471.93053
2638.59.66205-1.16205
26453.222761.77724
2659.511.3311-1.83113
26638.98103-5.98103
2671.50.6898890.810111
268610.7313-4.73125
2690.5-0.9467181.44672
2706.54.78281.7172
2717.58.96769-1.46769
2724.51.866812.63319
27386.34331.6567
27498.203650.796351
2757.55.835231.66477
2768.56.698451.80155
27773.203913.79609
2789.58.058191.44181
2796.52.283484.21652
2809.58.858030.641969
28165.076930.923073
28286.91811.0819
2839.57.590761.90924
28486.348241.65176
28586.240281.75972
28699.60434-0.604337
2875NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9767610.04647750.0232387
90.9529860.09402770.0470138
100.9320340.1359320.0679661
110.9427490.1145020.0572512
120.9074930.1850150.0925073
130.9290690.1418620.0709312
140.900090.199820.0999098
150.8569490.2861030.143051
160.8098030.3803940.190197
170.7817160.4365690.218284
180.7344520.5310960.265548
190.6703990.6592020.329601
200.6221640.7556720.377836
210.5512520.8974960.448748
220.6248240.7503530.375176
230.5936810.8126380.406319
240.529040.941920.47096
250.486390.972780.51361
260.4290440.8580880.570956
270.3764910.7529810.623509
280.3193280.6386560.680672
290.3629850.7259690.637015
300.3276430.6552860.672357
310.304330.608660.69567
320.2756080.5512160.724392
330.2756870.5513740.724313
340.383120.7662410.61688
350.3364450.672890.663555
360.3707580.7415170.629242
370.3287190.6574380.671281
380.2907070.5814150.709293
390.2511530.5023060.748847
400.2508960.5017910.749104
410.2972470.5944940.702753
420.2686890.5373770.731311
430.3928950.7857910.607105
440.3552890.7105780.644711
450.336170.672340.66383
460.3044810.6089630.695519
470.2951120.5902250.704888
480.2593940.5187880.740606
490.2307010.4614010.769299
500.3217960.6435910.678204
510.3664620.7329240.633538
520.3617340.7234680.638266
530.3259340.6518670.674066
540.3635240.7270490.636476
550.3421330.6842650.657867
560.3527510.7055020.647249
570.3636630.7273270.636337
580.3324740.6649480.667526
590.4555610.9111210.544439
600.547130.9057390.45287
610.5077630.9844740.492237
620.5366970.9266050.463303
630.525090.949820.47491
640.5058510.9882980.494149
650.5413390.9173230.458661
660.609740.7805190.39026
670.584820.830360.41518
680.5521040.8957920.447896
690.5412320.9175370.458768
700.5065360.9869270.493464
710.5147690.9704610.485231
720.4935870.9871730.506413
730.4614380.9228770.538562
740.4317190.8634390.568281
750.4048680.8097350.595132
760.4078750.815750.592125
770.5267130.9465740.473287
780.51070.97860.4893
790.4875820.9751640.512418
800.4786140.9572290.521386
810.4675670.9351350.532433
820.4428340.8856670.557166
830.5029290.9941420.497071
840.4713340.9426670.528666
850.5041470.9917060.495853
860.4733870.9467740.526613
870.5822640.8354710.417736
880.5657590.8684830.434241
890.5344080.9311850.465592
900.5018010.9963980.498199
910.4689280.9378560.531072
920.4667850.9335690.533215
930.4928590.9857170.507141
940.5093910.9812180.490609
950.6393990.7212020.360601
960.6161520.7676960.383848
970.6113140.7773710.388686
980.658190.683620.34181
990.6404660.7190690.359534
1000.6648140.6703720.335186
1010.6469820.7060350.353018
1020.7010630.5978740.298937
1030.7817540.4364910.218246
1040.7610690.4778610.238931
1050.7428910.5142180.257109
1060.739740.520520.26026
1070.7533920.4932160.246608
1080.7774290.4451420.222571
1090.7964150.407170.203585
1100.8005630.3988750.199437
1110.8999840.2000320.100016
1120.931120.1377610.0688804
1130.934510.130980.0654901
1140.9289710.1420580.071029
1150.9230610.1538780.076939
1160.9556040.08879130.0443957
1170.956910.08618050.0430903
1180.9632210.07355770.0367789
1190.9694820.06103510.0305176
1200.963940.07211970.0360599
1210.9675180.06496470.0324823
1220.9633140.07337160.0366858
1230.9675510.0648980.032449
1240.9711050.05778990.0288949
1250.9809140.03817110.0190855
1260.9781930.04361440.0218072
1270.9889270.0221450.0110725
1280.9904910.01901760.00950882
1290.9883730.0232530.0116265
1300.9865790.02684230.0134212
1310.987210.0255810.0127905
1320.9871490.02570260.0128513
1330.9864380.02712380.0135619
1340.9850990.02980110.0149005
1350.9832620.0334750.0167375
1360.981950.03609990.0180499
1370.9784280.04314310.0215715
1380.9752770.04944580.0247229
1390.9712510.05749880.0287494
1400.979870.0402590.0201295
1410.9849520.03009520.0150476
1420.9818170.03636570.0181829
1430.9781080.04378340.0218917
1440.9741070.05178590.025893
1450.9780120.04397530.0219876
1460.9769340.04613130.0230656
1470.9743280.05134360.0256718
1480.9719990.05600210.0280011
1490.9671840.06563220.0328161
1500.9645830.07083370.0354169
1510.9602880.0794240.039712
1520.955020.0899610.0449805
1530.9475380.1049230.0524617
1540.9519940.0960130.0480065
1550.9469290.1061420.053071
1560.9808050.03838990.0191949
1570.9787540.04249290.0212465
1580.9766070.04678690.0233934
1590.9716020.05679630.0283982
1600.9763810.04723730.0236187
1610.9717540.05649160.0282458
1620.9698920.06021580.0301079
1630.9686090.06278280.0313914
1640.9639250.07214990.0360749
1650.9575270.0849450.0424725
1660.9689730.06205440.0310272
1670.9634210.07315780.0365789
1680.9584750.0830510.0415255
1690.9810180.03796430.0189821
1700.9829320.03413660.0170683
1710.9804110.03917770.0195889
1720.9779810.04403770.0220188
1730.983340.03331970.0166598
1740.9792870.04142530.0207127
1750.9798620.04027660.0201383
1760.975440.04912040.0245602
1770.9798470.0403060.020153
1780.9765190.04696270.0234814
1790.9710870.05782590.028913
1800.9646390.07072290.0353614
1810.9659830.06803320.0340166
1820.9622180.07556460.0377823
1830.96130.07740090.0387004
1840.9550610.08987850.0449393
1850.9614910.0770170.0385085
1860.9619870.0760260.038013
1870.9543170.09136680.0456834
1880.9493380.1013240.0506621
1890.9397750.120450.0602251
1900.9502490.09950280.0497514
1910.9415340.1169330.0584663
1920.9616590.07668170.0383409
1930.9572690.08546110.0427306
1940.9512410.09751760.0487588
1950.9410460.1179090.0589545
1960.9302330.1395340.0697671
1970.9233270.1533460.0766728
1980.9192390.1615210.0807607
1990.9254010.1491980.0745992
2000.9200160.1599680.0799839
2010.912020.175960.0879798
2020.9224010.1551980.0775992
2030.9074410.1851180.0925592
2040.9228340.1543310.0771657
2050.9124620.1750750.0875377
2060.9017380.1965230.0982616
2070.898550.2028990.10145
2080.8859360.2281280.114064
2090.86810.26380.1319
2100.8528030.2943940.147197
2110.8803180.2393640.119682
2120.8758650.248270.124135
2130.8911160.2177680.108884
2140.8756840.2486320.124316
2150.855960.2880810.14404
2160.8365190.3269610.163481
2170.8312730.3374540.168727
2180.8083050.383390.191695
2190.8314780.3370440.168522
2200.8087690.3824610.191231
2210.7882590.4234810.211741
2220.7669870.4660260.233013
2230.7513450.4973110.248655
2240.7207250.558550.279275
2250.711080.577840.28892
2260.6805620.6388770.319438
2270.6410130.7179740.358987
2280.6047910.7904180.395209
2290.6103210.7793570.389679
2300.5728950.8542090.427105
2310.5360960.9278080.463904
2320.5371020.9257960.462898
2330.5640580.8718840.435942
2340.5564720.8870570.443528
2350.6331140.7337710.366886
2360.602280.7954390.39772
2370.6012480.7975040.398752
2380.6293990.7412020.370601
2390.5880990.8238030.411901
2400.5679540.8640920.432046
2410.5454260.9091480.454574
2420.5072170.9855670.492783
2430.676620.646760.32338
2440.6458550.7082890.354145
2450.6835780.6328440.316422
2460.6521840.6956310.347816
2470.6127820.7744360.387218
2480.5846740.8306520.415326
2490.6210110.7579770.378989
2500.6009390.7981220.399061
2510.5920540.8158930.407946
2520.6161570.7676850.383843
2530.568710.8625810.43129
2540.5115970.9768060.488403
2550.4548280.9096550.545172
2560.3976290.7952590.602371
2570.3606350.7212710.639365
2580.3175370.6350730.682463
2590.3117770.6235540.688223
2600.3460080.6920160.653992
2610.2959580.5919150.704042
2620.2464530.4929060.753547
2630.2876010.5752010.712399
2640.2517990.5035990.748201
2650.2686690.5373380.731331
2660.8338180.3323640.166182
2670.8002690.3994610.199731
2680.9995430.0009139470.000456973
2690.9999921.59453e-057.97264e-06
2700.9999784.37649e-052.18825e-05
2710.9999745.14595e-052.57297e-05
2720.9999657.08526e-053.54263e-05
2730.9999120.0001763178.81585e-05
2740.9996160.000768390.000384195
2750.999250.001500010.000750007
2760.9968370.006325380.00316269
2770.9877810.02443790.012219
2780.9662390.06752190.033761
2790.9975180.004963570.00248178

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.976761 & 0.0464775 & 0.0232387 \tabularnewline
9 & 0.952986 & 0.0940277 & 0.0470138 \tabularnewline
10 & 0.932034 & 0.135932 & 0.0679661 \tabularnewline
11 & 0.942749 & 0.114502 & 0.0572512 \tabularnewline
12 & 0.907493 & 0.185015 & 0.0925073 \tabularnewline
13 & 0.929069 & 0.141862 & 0.0709312 \tabularnewline
14 & 0.90009 & 0.19982 & 0.0999098 \tabularnewline
15 & 0.856949 & 0.286103 & 0.143051 \tabularnewline
16 & 0.809803 & 0.380394 & 0.190197 \tabularnewline
17 & 0.781716 & 0.436569 & 0.218284 \tabularnewline
18 & 0.734452 & 0.531096 & 0.265548 \tabularnewline
19 & 0.670399 & 0.659202 & 0.329601 \tabularnewline
20 & 0.622164 & 0.755672 & 0.377836 \tabularnewline
21 & 0.551252 & 0.897496 & 0.448748 \tabularnewline
22 & 0.624824 & 0.750353 & 0.375176 \tabularnewline
23 & 0.593681 & 0.812638 & 0.406319 \tabularnewline
24 & 0.52904 & 0.94192 & 0.47096 \tabularnewline
25 & 0.48639 & 0.97278 & 0.51361 \tabularnewline
26 & 0.429044 & 0.858088 & 0.570956 \tabularnewline
27 & 0.376491 & 0.752981 & 0.623509 \tabularnewline
28 & 0.319328 & 0.638656 & 0.680672 \tabularnewline
29 & 0.362985 & 0.725969 & 0.637015 \tabularnewline
30 & 0.327643 & 0.655286 & 0.672357 \tabularnewline
31 & 0.30433 & 0.60866 & 0.69567 \tabularnewline
32 & 0.275608 & 0.551216 & 0.724392 \tabularnewline
33 & 0.275687 & 0.551374 & 0.724313 \tabularnewline
34 & 0.38312 & 0.766241 & 0.61688 \tabularnewline
35 & 0.336445 & 0.67289 & 0.663555 \tabularnewline
36 & 0.370758 & 0.741517 & 0.629242 \tabularnewline
37 & 0.328719 & 0.657438 & 0.671281 \tabularnewline
38 & 0.290707 & 0.581415 & 0.709293 \tabularnewline
39 & 0.251153 & 0.502306 & 0.748847 \tabularnewline
40 & 0.250896 & 0.501791 & 0.749104 \tabularnewline
41 & 0.297247 & 0.594494 & 0.702753 \tabularnewline
42 & 0.268689 & 0.537377 & 0.731311 \tabularnewline
43 & 0.392895 & 0.785791 & 0.607105 \tabularnewline
44 & 0.355289 & 0.710578 & 0.644711 \tabularnewline
45 & 0.33617 & 0.67234 & 0.66383 \tabularnewline
46 & 0.304481 & 0.608963 & 0.695519 \tabularnewline
47 & 0.295112 & 0.590225 & 0.704888 \tabularnewline
48 & 0.259394 & 0.518788 & 0.740606 \tabularnewline
49 & 0.230701 & 0.461401 & 0.769299 \tabularnewline
50 & 0.321796 & 0.643591 & 0.678204 \tabularnewline
51 & 0.366462 & 0.732924 & 0.633538 \tabularnewline
52 & 0.361734 & 0.723468 & 0.638266 \tabularnewline
53 & 0.325934 & 0.651867 & 0.674066 \tabularnewline
54 & 0.363524 & 0.727049 & 0.636476 \tabularnewline
55 & 0.342133 & 0.684265 & 0.657867 \tabularnewline
56 & 0.352751 & 0.705502 & 0.647249 \tabularnewline
57 & 0.363663 & 0.727327 & 0.636337 \tabularnewline
58 & 0.332474 & 0.664948 & 0.667526 \tabularnewline
59 & 0.455561 & 0.911121 & 0.544439 \tabularnewline
60 & 0.54713 & 0.905739 & 0.45287 \tabularnewline
61 & 0.507763 & 0.984474 & 0.492237 \tabularnewline
62 & 0.536697 & 0.926605 & 0.463303 \tabularnewline
63 & 0.52509 & 0.94982 & 0.47491 \tabularnewline
64 & 0.505851 & 0.988298 & 0.494149 \tabularnewline
65 & 0.541339 & 0.917323 & 0.458661 \tabularnewline
66 & 0.60974 & 0.780519 & 0.39026 \tabularnewline
67 & 0.58482 & 0.83036 & 0.41518 \tabularnewline
68 & 0.552104 & 0.895792 & 0.447896 \tabularnewline
69 & 0.541232 & 0.917537 & 0.458768 \tabularnewline
70 & 0.506536 & 0.986927 & 0.493464 \tabularnewline
71 & 0.514769 & 0.970461 & 0.485231 \tabularnewline
72 & 0.493587 & 0.987173 & 0.506413 \tabularnewline
73 & 0.461438 & 0.922877 & 0.538562 \tabularnewline
74 & 0.431719 & 0.863439 & 0.568281 \tabularnewline
75 & 0.404868 & 0.809735 & 0.595132 \tabularnewline
76 & 0.407875 & 0.81575 & 0.592125 \tabularnewline
77 & 0.526713 & 0.946574 & 0.473287 \tabularnewline
78 & 0.5107 & 0.9786 & 0.4893 \tabularnewline
79 & 0.487582 & 0.975164 & 0.512418 \tabularnewline
80 & 0.478614 & 0.957229 & 0.521386 \tabularnewline
81 & 0.467567 & 0.935135 & 0.532433 \tabularnewline
82 & 0.442834 & 0.885667 & 0.557166 \tabularnewline
83 & 0.502929 & 0.994142 & 0.497071 \tabularnewline
84 & 0.471334 & 0.942667 & 0.528666 \tabularnewline
85 & 0.504147 & 0.991706 & 0.495853 \tabularnewline
86 & 0.473387 & 0.946774 & 0.526613 \tabularnewline
87 & 0.582264 & 0.835471 & 0.417736 \tabularnewline
88 & 0.565759 & 0.868483 & 0.434241 \tabularnewline
89 & 0.534408 & 0.931185 & 0.465592 \tabularnewline
90 & 0.501801 & 0.996398 & 0.498199 \tabularnewline
91 & 0.468928 & 0.937856 & 0.531072 \tabularnewline
92 & 0.466785 & 0.933569 & 0.533215 \tabularnewline
93 & 0.492859 & 0.985717 & 0.507141 \tabularnewline
94 & 0.509391 & 0.981218 & 0.490609 \tabularnewline
95 & 0.639399 & 0.721202 & 0.360601 \tabularnewline
96 & 0.616152 & 0.767696 & 0.383848 \tabularnewline
97 & 0.611314 & 0.777371 & 0.388686 \tabularnewline
98 & 0.65819 & 0.68362 & 0.34181 \tabularnewline
99 & 0.640466 & 0.719069 & 0.359534 \tabularnewline
100 & 0.664814 & 0.670372 & 0.335186 \tabularnewline
101 & 0.646982 & 0.706035 & 0.353018 \tabularnewline
102 & 0.701063 & 0.597874 & 0.298937 \tabularnewline
103 & 0.781754 & 0.436491 & 0.218246 \tabularnewline
104 & 0.761069 & 0.477861 & 0.238931 \tabularnewline
105 & 0.742891 & 0.514218 & 0.257109 \tabularnewline
106 & 0.73974 & 0.52052 & 0.26026 \tabularnewline
107 & 0.753392 & 0.493216 & 0.246608 \tabularnewline
108 & 0.777429 & 0.445142 & 0.222571 \tabularnewline
109 & 0.796415 & 0.40717 & 0.203585 \tabularnewline
110 & 0.800563 & 0.398875 & 0.199437 \tabularnewline
111 & 0.899984 & 0.200032 & 0.100016 \tabularnewline
112 & 0.93112 & 0.137761 & 0.0688804 \tabularnewline
113 & 0.93451 & 0.13098 & 0.0654901 \tabularnewline
114 & 0.928971 & 0.142058 & 0.071029 \tabularnewline
115 & 0.923061 & 0.153878 & 0.076939 \tabularnewline
116 & 0.955604 & 0.0887913 & 0.0443957 \tabularnewline
117 & 0.95691 & 0.0861805 & 0.0430903 \tabularnewline
118 & 0.963221 & 0.0735577 & 0.0367789 \tabularnewline
119 & 0.969482 & 0.0610351 & 0.0305176 \tabularnewline
120 & 0.96394 & 0.0721197 & 0.0360599 \tabularnewline
121 & 0.967518 & 0.0649647 & 0.0324823 \tabularnewline
122 & 0.963314 & 0.0733716 & 0.0366858 \tabularnewline
123 & 0.967551 & 0.064898 & 0.032449 \tabularnewline
124 & 0.971105 & 0.0577899 & 0.0288949 \tabularnewline
125 & 0.980914 & 0.0381711 & 0.0190855 \tabularnewline
126 & 0.978193 & 0.0436144 & 0.0218072 \tabularnewline
127 & 0.988927 & 0.022145 & 0.0110725 \tabularnewline
128 & 0.990491 & 0.0190176 & 0.00950882 \tabularnewline
129 & 0.988373 & 0.023253 & 0.0116265 \tabularnewline
130 & 0.986579 & 0.0268423 & 0.0134212 \tabularnewline
131 & 0.98721 & 0.025581 & 0.0127905 \tabularnewline
132 & 0.987149 & 0.0257026 & 0.0128513 \tabularnewline
133 & 0.986438 & 0.0271238 & 0.0135619 \tabularnewline
134 & 0.985099 & 0.0298011 & 0.0149005 \tabularnewline
135 & 0.983262 & 0.033475 & 0.0167375 \tabularnewline
136 & 0.98195 & 0.0360999 & 0.0180499 \tabularnewline
137 & 0.978428 & 0.0431431 & 0.0215715 \tabularnewline
138 & 0.975277 & 0.0494458 & 0.0247229 \tabularnewline
139 & 0.971251 & 0.0574988 & 0.0287494 \tabularnewline
140 & 0.97987 & 0.040259 & 0.0201295 \tabularnewline
141 & 0.984952 & 0.0300952 & 0.0150476 \tabularnewline
142 & 0.981817 & 0.0363657 & 0.0181829 \tabularnewline
143 & 0.978108 & 0.0437834 & 0.0218917 \tabularnewline
144 & 0.974107 & 0.0517859 & 0.025893 \tabularnewline
145 & 0.978012 & 0.0439753 & 0.0219876 \tabularnewline
146 & 0.976934 & 0.0461313 & 0.0230656 \tabularnewline
147 & 0.974328 & 0.0513436 & 0.0256718 \tabularnewline
148 & 0.971999 & 0.0560021 & 0.0280011 \tabularnewline
149 & 0.967184 & 0.0656322 & 0.0328161 \tabularnewline
150 & 0.964583 & 0.0708337 & 0.0354169 \tabularnewline
151 & 0.960288 & 0.079424 & 0.039712 \tabularnewline
152 & 0.95502 & 0.089961 & 0.0449805 \tabularnewline
153 & 0.947538 & 0.104923 & 0.0524617 \tabularnewline
154 & 0.951994 & 0.096013 & 0.0480065 \tabularnewline
155 & 0.946929 & 0.106142 & 0.053071 \tabularnewline
156 & 0.980805 & 0.0383899 & 0.0191949 \tabularnewline
157 & 0.978754 & 0.0424929 & 0.0212465 \tabularnewline
158 & 0.976607 & 0.0467869 & 0.0233934 \tabularnewline
159 & 0.971602 & 0.0567963 & 0.0283982 \tabularnewline
160 & 0.976381 & 0.0472373 & 0.0236187 \tabularnewline
161 & 0.971754 & 0.0564916 & 0.0282458 \tabularnewline
162 & 0.969892 & 0.0602158 & 0.0301079 \tabularnewline
163 & 0.968609 & 0.0627828 & 0.0313914 \tabularnewline
164 & 0.963925 & 0.0721499 & 0.0360749 \tabularnewline
165 & 0.957527 & 0.084945 & 0.0424725 \tabularnewline
166 & 0.968973 & 0.0620544 & 0.0310272 \tabularnewline
167 & 0.963421 & 0.0731578 & 0.0365789 \tabularnewline
168 & 0.958475 & 0.083051 & 0.0415255 \tabularnewline
169 & 0.981018 & 0.0379643 & 0.0189821 \tabularnewline
170 & 0.982932 & 0.0341366 & 0.0170683 \tabularnewline
171 & 0.980411 & 0.0391777 & 0.0195889 \tabularnewline
172 & 0.977981 & 0.0440377 & 0.0220188 \tabularnewline
173 & 0.98334 & 0.0333197 & 0.0166598 \tabularnewline
174 & 0.979287 & 0.0414253 & 0.0207127 \tabularnewline
175 & 0.979862 & 0.0402766 & 0.0201383 \tabularnewline
176 & 0.97544 & 0.0491204 & 0.0245602 \tabularnewline
177 & 0.979847 & 0.040306 & 0.020153 \tabularnewline
178 & 0.976519 & 0.0469627 & 0.0234814 \tabularnewline
179 & 0.971087 & 0.0578259 & 0.028913 \tabularnewline
180 & 0.964639 & 0.0707229 & 0.0353614 \tabularnewline
181 & 0.965983 & 0.0680332 & 0.0340166 \tabularnewline
182 & 0.962218 & 0.0755646 & 0.0377823 \tabularnewline
183 & 0.9613 & 0.0774009 & 0.0387004 \tabularnewline
184 & 0.955061 & 0.0898785 & 0.0449393 \tabularnewline
185 & 0.961491 & 0.077017 & 0.0385085 \tabularnewline
186 & 0.961987 & 0.076026 & 0.038013 \tabularnewline
187 & 0.954317 & 0.0913668 & 0.0456834 \tabularnewline
188 & 0.949338 & 0.101324 & 0.0506621 \tabularnewline
189 & 0.939775 & 0.12045 & 0.0602251 \tabularnewline
190 & 0.950249 & 0.0995028 & 0.0497514 \tabularnewline
191 & 0.941534 & 0.116933 & 0.0584663 \tabularnewline
192 & 0.961659 & 0.0766817 & 0.0383409 \tabularnewline
193 & 0.957269 & 0.0854611 & 0.0427306 \tabularnewline
194 & 0.951241 & 0.0975176 & 0.0487588 \tabularnewline
195 & 0.941046 & 0.117909 & 0.0589545 \tabularnewline
196 & 0.930233 & 0.139534 & 0.0697671 \tabularnewline
197 & 0.923327 & 0.153346 & 0.0766728 \tabularnewline
198 & 0.919239 & 0.161521 & 0.0807607 \tabularnewline
199 & 0.925401 & 0.149198 & 0.0745992 \tabularnewline
200 & 0.920016 & 0.159968 & 0.0799839 \tabularnewline
201 & 0.91202 & 0.17596 & 0.0879798 \tabularnewline
202 & 0.922401 & 0.155198 & 0.0775992 \tabularnewline
203 & 0.907441 & 0.185118 & 0.0925592 \tabularnewline
204 & 0.922834 & 0.154331 & 0.0771657 \tabularnewline
205 & 0.912462 & 0.175075 & 0.0875377 \tabularnewline
206 & 0.901738 & 0.196523 & 0.0982616 \tabularnewline
207 & 0.89855 & 0.202899 & 0.10145 \tabularnewline
208 & 0.885936 & 0.228128 & 0.114064 \tabularnewline
209 & 0.8681 & 0.2638 & 0.1319 \tabularnewline
210 & 0.852803 & 0.294394 & 0.147197 \tabularnewline
211 & 0.880318 & 0.239364 & 0.119682 \tabularnewline
212 & 0.875865 & 0.24827 & 0.124135 \tabularnewline
213 & 0.891116 & 0.217768 & 0.108884 \tabularnewline
214 & 0.875684 & 0.248632 & 0.124316 \tabularnewline
215 & 0.85596 & 0.288081 & 0.14404 \tabularnewline
216 & 0.836519 & 0.326961 & 0.163481 \tabularnewline
217 & 0.831273 & 0.337454 & 0.168727 \tabularnewline
218 & 0.808305 & 0.38339 & 0.191695 \tabularnewline
219 & 0.831478 & 0.337044 & 0.168522 \tabularnewline
220 & 0.808769 & 0.382461 & 0.191231 \tabularnewline
221 & 0.788259 & 0.423481 & 0.211741 \tabularnewline
222 & 0.766987 & 0.466026 & 0.233013 \tabularnewline
223 & 0.751345 & 0.497311 & 0.248655 \tabularnewline
224 & 0.720725 & 0.55855 & 0.279275 \tabularnewline
225 & 0.71108 & 0.57784 & 0.28892 \tabularnewline
226 & 0.680562 & 0.638877 & 0.319438 \tabularnewline
227 & 0.641013 & 0.717974 & 0.358987 \tabularnewline
228 & 0.604791 & 0.790418 & 0.395209 \tabularnewline
229 & 0.610321 & 0.779357 & 0.389679 \tabularnewline
230 & 0.572895 & 0.854209 & 0.427105 \tabularnewline
231 & 0.536096 & 0.927808 & 0.463904 \tabularnewline
232 & 0.537102 & 0.925796 & 0.462898 \tabularnewline
233 & 0.564058 & 0.871884 & 0.435942 \tabularnewline
234 & 0.556472 & 0.887057 & 0.443528 \tabularnewline
235 & 0.633114 & 0.733771 & 0.366886 \tabularnewline
236 & 0.60228 & 0.795439 & 0.39772 \tabularnewline
237 & 0.601248 & 0.797504 & 0.398752 \tabularnewline
238 & 0.629399 & 0.741202 & 0.370601 \tabularnewline
239 & 0.588099 & 0.823803 & 0.411901 \tabularnewline
240 & 0.567954 & 0.864092 & 0.432046 \tabularnewline
241 & 0.545426 & 0.909148 & 0.454574 \tabularnewline
242 & 0.507217 & 0.985567 & 0.492783 \tabularnewline
243 & 0.67662 & 0.64676 & 0.32338 \tabularnewline
244 & 0.645855 & 0.708289 & 0.354145 \tabularnewline
245 & 0.683578 & 0.632844 & 0.316422 \tabularnewline
246 & 0.652184 & 0.695631 & 0.347816 \tabularnewline
247 & 0.612782 & 0.774436 & 0.387218 \tabularnewline
248 & 0.584674 & 0.830652 & 0.415326 \tabularnewline
249 & 0.621011 & 0.757977 & 0.378989 \tabularnewline
250 & 0.600939 & 0.798122 & 0.399061 \tabularnewline
251 & 0.592054 & 0.815893 & 0.407946 \tabularnewline
252 & 0.616157 & 0.767685 & 0.383843 \tabularnewline
253 & 0.56871 & 0.862581 & 0.43129 \tabularnewline
254 & 0.511597 & 0.976806 & 0.488403 \tabularnewline
255 & 0.454828 & 0.909655 & 0.545172 \tabularnewline
256 & 0.397629 & 0.795259 & 0.602371 \tabularnewline
257 & 0.360635 & 0.721271 & 0.639365 \tabularnewline
258 & 0.317537 & 0.635073 & 0.682463 \tabularnewline
259 & 0.311777 & 0.623554 & 0.688223 \tabularnewline
260 & 0.346008 & 0.692016 & 0.653992 \tabularnewline
261 & 0.295958 & 0.591915 & 0.704042 \tabularnewline
262 & 0.246453 & 0.492906 & 0.753547 \tabularnewline
263 & 0.287601 & 0.575201 & 0.712399 \tabularnewline
264 & 0.251799 & 0.503599 & 0.748201 \tabularnewline
265 & 0.268669 & 0.537338 & 0.731331 \tabularnewline
266 & 0.833818 & 0.332364 & 0.166182 \tabularnewline
267 & 0.800269 & 0.399461 & 0.199731 \tabularnewline
268 & 0.999543 & 0.000913947 & 0.000456973 \tabularnewline
269 & 0.999992 & 1.59453e-05 & 7.97264e-06 \tabularnewline
270 & 0.999978 & 4.37649e-05 & 2.18825e-05 \tabularnewline
271 & 0.999974 & 5.14595e-05 & 2.57297e-05 \tabularnewline
272 & 0.999965 & 7.08526e-05 & 3.54263e-05 \tabularnewline
273 & 0.999912 & 0.000176317 & 8.81585e-05 \tabularnewline
274 & 0.999616 & 0.00076839 & 0.000384195 \tabularnewline
275 & 0.99925 & 0.00150001 & 0.000750007 \tabularnewline
276 & 0.996837 & 0.00632538 & 0.00316269 \tabularnewline
277 & 0.987781 & 0.0244379 & 0.012219 \tabularnewline
278 & 0.966239 & 0.0675219 & 0.033761 \tabularnewline
279 & 0.997518 & 0.00496357 & 0.00248178 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268752&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]0.976761[/C][C]0.0464775[/C][C]0.0232387[/C][/ROW]
[ROW][C]9[/C][C]0.952986[/C][C]0.0940277[/C][C]0.0470138[/C][/ROW]
[ROW][C]10[/C][C]0.932034[/C][C]0.135932[/C][C]0.0679661[/C][/ROW]
[ROW][C]11[/C][C]0.942749[/C][C]0.114502[/C][C]0.0572512[/C][/ROW]
[ROW][C]12[/C][C]0.907493[/C][C]0.185015[/C][C]0.0925073[/C][/ROW]
[ROW][C]13[/C][C]0.929069[/C][C]0.141862[/C][C]0.0709312[/C][/ROW]
[ROW][C]14[/C][C]0.90009[/C][C]0.19982[/C][C]0.0999098[/C][/ROW]
[ROW][C]15[/C][C]0.856949[/C][C]0.286103[/C][C]0.143051[/C][/ROW]
[ROW][C]16[/C][C]0.809803[/C][C]0.380394[/C][C]0.190197[/C][/ROW]
[ROW][C]17[/C][C]0.781716[/C][C]0.436569[/C][C]0.218284[/C][/ROW]
[ROW][C]18[/C][C]0.734452[/C][C]0.531096[/C][C]0.265548[/C][/ROW]
[ROW][C]19[/C][C]0.670399[/C][C]0.659202[/C][C]0.329601[/C][/ROW]
[ROW][C]20[/C][C]0.622164[/C][C]0.755672[/C][C]0.377836[/C][/ROW]
[ROW][C]21[/C][C]0.551252[/C][C]0.897496[/C][C]0.448748[/C][/ROW]
[ROW][C]22[/C][C]0.624824[/C][C]0.750353[/C][C]0.375176[/C][/ROW]
[ROW][C]23[/C][C]0.593681[/C][C]0.812638[/C][C]0.406319[/C][/ROW]
[ROW][C]24[/C][C]0.52904[/C][C]0.94192[/C][C]0.47096[/C][/ROW]
[ROW][C]25[/C][C]0.48639[/C][C]0.97278[/C][C]0.51361[/C][/ROW]
[ROW][C]26[/C][C]0.429044[/C][C]0.858088[/C][C]0.570956[/C][/ROW]
[ROW][C]27[/C][C]0.376491[/C][C]0.752981[/C][C]0.623509[/C][/ROW]
[ROW][C]28[/C][C]0.319328[/C][C]0.638656[/C][C]0.680672[/C][/ROW]
[ROW][C]29[/C][C]0.362985[/C][C]0.725969[/C][C]0.637015[/C][/ROW]
[ROW][C]30[/C][C]0.327643[/C][C]0.655286[/C][C]0.672357[/C][/ROW]
[ROW][C]31[/C][C]0.30433[/C][C]0.60866[/C][C]0.69567[/C][/ROW]
[ROW][C]32[/C][C]0.275608[/C][C]0.551216[/C][C]0.724392[/C][/ROW]
[ROW][C]33[/C][C]0.275687[/C][C]0.551374[/C][C]0.724313[/C][/ROW]
[ROW][C]34[/C][C]0.38312[/C][C]0.766241[/C][C]0.61688[/C][/ROW]
[ROW][C]35[/C][C]0.336445[/C][C]0.67289[/C][C]0.663555[/C][/ROW]
[ROW][C]36[/C][C]0.370758[/C][C]0.741517[/C][C]0.629242[/C][/ROW]
[ROW][C]37[/C][C]0.328719[/C][C]0.657438[/C][C]0.671281[/C][/ROW]
[ROW][C]38[/C][C]0.290707[/C][C]0.581415[/C][C]0.709293[/C][/ROW]
[ROW][C]39[/C][C]0.251153[/C][C]0.502306[/C][C]0.748847[/C][/ROW]
[ROW][C]40[/C][C]0.250896[/C][C]0.501791[/C][C]0.749104[/C][/ROW]
[ROW][C]41[/C][C]0.297247[/C][C]0.594494[/C][C]0.702753[/C][/ROW]
[ROW][C]42[/C][C]0.268689[/C][C]0.537377[/C][C]0.731311[/C][/ROW]
[ROW][C]43[/C][C]0.392895[/C][C]0.785791[/C][C]0.607105[/C][/ROW]
[ROW][C]44[/C][C]0.355289[/C][C]0.710578[/C][C]0.644711[/C][/ROW]
[ROW][C]45[/C][C]0.33617[/C][C]0.67234[/C][C]0.66383[/C][/ROW]
[ROW][C]46[/C][C]0.304481[/C][C]0.608963[/C][C]0.695519[/C][/ROW]
[ROW][C]47[/C][C]0.295112[/C][C]0.590225[/C][C]0.704888[/C][/ROW]
[ROW][C]48[/C][C]0.259394[/C][C]0.518788[/C][C]0.740606[/C][/ROW]
[ROW][C]49[/C][C]0.230701[/C][C]0.461401[/C][C]0.769299[/C][/ROW]
[ROW][C]50[/C][C]0.321796[/C][C]0.643591[/C][C]0.678204[/C][/ROW]
[ROW][C]51[/C][C]0.366462[/C][C]0.732924[/C][C]0.633538[/C][/ROW]
[ROW][C]52[/C][C]0.361734[/C][C]0.723468[/C][C]0.638266[/C][/ROW]
[ROW][C]53[/C][C]0.325934[/C][C]0.651867[/C][C]0.674066[/C][/ROW]
[ROW][C]54[/C][C]0.363524[/C][C]0.727049[/C][C]0.636476[/C][/ROW]
[ROW][C]55[/C][C]0.342133[/C][C]0.684265[/C][C]0.657867[/C][/ROW]
[ROW][C]56[/C][C]0.352751[/C][C]0.705502[/C][C]0.647249[/C][/ROW]
[ROW][C]57[/C][C]0.363663[/C][C]0.727327[/C][C]0.636337[/C][/ROW]
[ROW][C]58[/C][C]0.332474[/C][C]0.664948[/C][C]0.667526[/C][/ROW]
[ROW][C]59[/C][C]0.455561[/C][C]0.911121[/C][C]0.544439[/C][/ROW]
[ROW][C]60[/C][C]0.54713[/C][C]0.905739[/C][C]0.45287[/C][/ROW]
[ROW][C]61[/C][C]0.507763[/C][C]0.984474[/C][C]0.492237[/C][/ROW]
[ROW][C]62[/C][C]0.536697[/C][C]0.926605[/C][C]0.463303[/C][/ROW]
[ROW][C]63[/C][C]0.52509[/C][C]0.94982[/C][C]0.47491[/C][/ROW]
[ROW][C]64[/C][C]0.505851[/C][C]0.988298[/C][C]0.494149[/C][/ROW]
[ROW][C]65[/C][C]0.541339[/C][C]0.917323[/C][C]0.458661[/C][/ROW]
[ROW][C]66[/C][C]0.60974[/C][C]0.780519[/C][C]0.39026[/C][/ROW]
[ROW][C]67[/C][C]0.58482[/C][C]0.83036[/C][C]0.41518[/C][/ROW]
[ROW][C]68[/C][C]0.552104[/C][C]0.895792[/C][C]0.447896[/C][/ROW]
[ROW][C]69[/C][C]0.541232[/C][C]0.917537[/C][C]0.458768[/C][/ROW]
[ROW][C]70[/C][C]0.506536[/C][C]0.986927[/C][C]0.493464[/C][/ROW]
[ROW][C]71[/C][C]0.514769[/C][C]0.970461[/C][C]0.485231[/C][/ROW]
[ROW][C]72[/C][C]0.493587[/C][C]0.987173[/C][C]0.506413[/C][/ROW]
[ROW][C]73[/C][C]0.461438[/C][C]0.922877[/C][C]0.538562[/C][/ROW]
[ROW][C]74[/C][C]0.431719[/C][C]0.863439[/C][C]0.568281[/C][/ROW]
[ROW][C]75[/C][C]0.404868[/C][C]0.809735[/C][C]0.595132[/C][/ROW]
[ROW][C]76[/C][C]0.407875[/C][C]0.81575[/C][C]0.592125[/C][/ROW]
[ROW][C]77[/C][C]0.526713[/C][C]0.946574[/C][C]0.473287[/C][/ROW]
[ROW][C]78[/C][C]0.5107[/C][C]0.9786[/C][C]0.4893[/C][/ROW]
[ROW][C]79[/C][C]0.487582[/C][C]0.975164[/C][C]0.512418[/C][/ROW]
[ROW][C]80[/C][C]0.478614[/C][C]0.957229[/C][C]0.521386[/C][/ROW]
[ROW][C]81[/C][C]0.467567[/C][C]0.935135[/C][C]0.532433[/C][/ROW]
[ROW][C]82[/C][C]0.442834[/C][C]0.885667[/C][C]0.557166[/C][/ROW]
[ROW][C]83[/C][C]0.502929[/C][C]0.994142[/C][C]0.497071[/C][/ROW]
[ROW][C]84[/C][C]0.471334[/C][C]0.942667[/C][C]0.528666[/C][/ROW]
[ROW][C]85[/C][C]0.504147[/C][C]0.991706[/C][C]0.495853[/C][/ROW]
[ROW][C]86[/C][C]0.473387[/C][C]0.946774[/C][C]0.526613[/C][/ROW]
[ROW][C]87[/C][C]0.582264[/C][C]0.835471[/C][C]0.417736[/C][/ROW]
[ROW][C]88[/C][C]0.565759[/C][C]0.868483[/C][C]0.434241[/C][/ROW]
[ROW][C]89[/C][C]0.534408[/C][C]0.931185[/C][C]0.465592[/C][/ROW]
[ROW][C]90[/C][C]0.501801[/C][C]0.996398[/C][C]0.498199[/C][/ROW]
[ROW][C]91[/C][C]0.468928[/C][C]0.937856[/C][C]0.531072[/C][/ROW]
[ROW][C]92[/C][C]0.466785[/C][C]0.933569[/C][C]0.533215[/C][/ROW]
[ROW][C]93[/C][C]0.492859[/C][C]0.985717[/C][C]0.507141[/C][/ROW]
[ROW][C]94[/C][C]0.509391[/C][C]0.981218[/C][C]0.490609[/C][/ROW]
[ROW][C]95[/C][C]0.639399[/C][C]0.721202[/C][C]0.360601[/C][/ROW]
[ROW][C]96[/C][C]0.616152[/C][C]0.767696[/C][C]0.383848[/C][/ROW]
[ROW][C]97[/C][C]0.611314[/C][C]0.777371[/C][C]0.388686[/C][/ROW]
[ROW][C]98[/C][C]0.65819[/C][C]0.68362[/C][C]0.34181[/C][/ROW]
[ROW][C]99[/C][C]0.640466[/C][C]0.719069[/C][C]0.359534[/C][/ROW]
[ROW][C]100[/C][C]0.664814[/C][C]0.670372[/C][C]0.335186[/C][/ROW]
[ROW][C]101[/C][C]0.646982[/C][C]0.706035[/C][C]0.353018[/C][/ROW]
[ROW][C]102[/C][C]0.701063[/C][C]0.597874[/C][C]0.298937[/C][/ROW]
[ROW][C]103[/C][C]0.781754[/C][C]0.436491[/C][C]0.218246[/C][/ROW]
[ROW][C]104[/C][C]0.761069[/C][C]0.477861[/C][C]0.238931[/C][/ROW]
[ROW][C]105[/C][C]0.742891[/C][C]0.514218[/C][C]0.257109[/C][/ROW]
[ROW][C]106[/C][C]0.73974[/C][C]0.52052[/C][C]0.26026[/C][/ROW]
[ROW][C]107[/C][C]0.753392[/C][C]0.493216[/C][C]0.246608[/C][/ROW]
[ROW][C]108[/C][C]0.777429[/C][C]0.445142[/C][C]0.222571[/C][/ROW]
[ROW][C]109[/C][C]0.796415[/C][C]0.40717[/C][C]0.203585[/C][/ROW]
[ROW][C]110[/C][C]0.800563[/C][C]0.398875[/C][C]0.199437[/C][/ROW]
[ROW][C]111[/C][C]0.899984[/C][C]0.200032[/C][C]0.100016[/C][/ROW]
[ROW][C]112[/C][C]0.93112[/C][C]0.137761[/C][C]0.0688804[/C][/ROW]
[ROW][C]113[/C][C]0.93451[/C][C]0.13098[/C][C]0.0654901[/C][/ROW]
[ROW][C]114[/C][C]0.928971[/C][C]0.142058[/C][C]0.071029[/C][/ROW]
[ROW][C]115[/C][C]0.923061[/C][C]0.153878[/C][C]0.076939[/C][/ROW]
[ROW][C]116[/C][C]0.955604[/C][C]0.0887913[/C][C]0.0443957[/C][/ROW]
[ROW][C]117[/C][C]0.95691[/C][C]0.0861805[/C][C]0.0430903[/C][/ROW]
[ROW][C]118[/C][C]0.963221[/C][C]0.0735577[/C][C]0.0367789[/C][/ROW]
[ROW][C]119[/C][C]0.969482[/C][C]0.0610351[/C][C]0.0305176[/C][/ROW]
[ROW][C]120[/C][C]0.96394[/C][C]0.0721197[/C][C]0.0360599[/C][/ROW]
[ROW][C]121[/C][C]0.967518[/C][C]0.0649647[/C][C]0.0324823[/C][/ROW]
[ROW][C]122[/C][C]0.963314[/C][C]0.0733716[/C][C]0.0366858[/C][/ROW]
[ROW][C]123[/C][C]0.967551[/C][C]0.064898[/C][C]0.032449[/C][/ROW]
[ROW][C]124[/C][C]0.971105[/C][C]0.0577899[/C][C]0.0288949[/C][/ROW]
[ROW][C]125[/C][C]0.980914[/C][C]0.0381711[/C][C]0.0190855[/C][/ROW]
[ROW][C]126[/C][C]0.978193[/C][C]0.0436144[/C][C]0.0218072[/C][/ROW]
[ROW][C]127[/C][C]0.988927[/C][C]0.022145[/C][C]0.0110725[/C][/ROW]
[ROW][C]128[/C][C]0.990491[/C][C]0.0190176[/C][C]0.00950882[/C][/ROW]
[ROW][C]129[/C][C]0.988373[/C][C]0.023253[/C][C]0.0116265[/C][/ROW]
[ROW][C]130[/C][C]0.986579[/C][C]0.0268423[/C][C]0.0134212[/C][/ROW]
[ROW][C]131[/C][C]0.98721[/C][C]0.025581[/C][C]0.0127905[/C][/ROW]
[ROW][C]132[/C][C]0.987149[/C][C]0.0257026[/C][C]0.0128513[/C][/ROW]
[ROW][C]133[/C][C]0.986438[/C][C]0.0271238[/C][C]0.0135619[/C][/ROW]
[ROW][C]134[/C][C]0.985099[/C][C]0.0298011[/C][C]0.0149005[/C][/ROW]
[ROW][C]135[/C][C]0.983262[/C][C]0.033475[/C][C]0.0167375[/C][/ROW]
[ROW][C]136[/C][C]0.98195[/C][C]0.0360999[/C][C]0.0180499[/C][/ROW]
[ROW][C]137[/C][C]0.978428[/C][C]0.0431431[/C][C]0.0215715[/C][/ROW]
[ROW][C]138[/C][C]0.975277[/C][C]0.0494458[/C][C]0.0247229[/C][/ROW]
[ROW][C]139[/C][C]0.971251[/C][C]0.0574988[/C][C]0.0287494[/C][/ROW]
[ROW][C]140[/C][C]0.97987[/C][C]0.040259[/C][C]0.0201295[/C][/ROW]
[ROW][C]141[/C][C]0.984952[/C][C]0.0300952[/C][C]0.0150476[/C][/ROW]
[ROW][C]142[/C][C]0.981817[/C][C]0.0363657[/C][C]0.0181829[/C][/ROW]
[ROW][C]143[/C][C]0.978108[/C][C]0.0437834[/C][C]0.0218917[/C][/ROW]
[ROW][C]144[/C][C]0.974107[/C][C]0.0517859[/C][C]0.025893[/C][/ROW]
[ROW][C]145[/C][C]0.978012[/C][C]0.0439753[/C][C]0.0219876[/C][/ROW]
[ROW][C]146[/C][C]0.976934[/C][C]0.0461313[/C][C]0.0230656[/C][/ROW]
[ROW][C]147[/C][C]0.974328[/C][C]0.0513436[/C][C]0.0256718[/C][/ROW]
[ROW][C]148[/C][C]0.971999[/C][C]0.0560021[/C][C]0.0280011[/C][/ROW]
[ROW][C]149[/C][C]0.967184[/C][C]0.0656322[/C][C]0.0328161[/C][/ROW]
[ROW][C]150[/C][C]0.964583[/C][C]0.0708337[/C][C]0.0354169[/C][/ROW]
[ROW][C]151[/C][C]0.960288[/C][C]0.079424[/C][C]0.039712[/C][/ROW]
[ROW][C]152[/C][C]0.95502[/C][C]0.089961[/C][C]0.0449805[/C][/ROW]
[ROW][C]153[/C][C]0.947538[/C][C]0.104923[/C][C]0.0524617[/C][/ROW]
[ROW][C]154[/C][C]0.951994[/C][C]0.096013[/C][C]0.0480065[/C][/ROW]
[ROW][C]155[/C][C]0.946929[/C][C]0.106142[/C][C]0.053071[/C][/ROW]
[ROW][C]156[/C][C]0.980805[/C][C]0.0383899[/C][C]0.0191949[/C][/ROW]
[ROW][C]157[/C][C]0.978754[/C][C]0.0424929[/C][C]0.0212465[/C][/ROW]
[ROW][C]158[/C][C]0.976607[/C][C]0.0467869[/C][C]0.0233934[/C][/ROW]
[ROW][C]159[/C][C]0.971602[/C][C]0.0567963[/C][C]0.0283982[/C][/ROW]
[ROW][C]160[/C][C]0.976381[/C][C]0.0472373[/C][C]0.0236187[/C][/ROW]
[ROW][C]161[/C][C]0.971754[/C][C]0.0564916[/C][C]0.0282458[/C][/ROW]
[ROW][C]162[/C][C]0.969892[/C][C]0.0602158[/C][C]0.0301079[/C][/ROW]
[ROW][C]163[/C][C]0.968609[/C][C]0.0627828[/C][C]0.0313914[/C][/ROW]
[ROW][C]164[/C][C]0.963925[/C][C]0.0721499[/C][C]0.0360749[/C][/ROW]
[ROW][C]165[/C][C]0.957527[/C][C]0.084945[/C][C]0.0424725[/C][/ROW]
[ROW][C]166[/C][C]0.968973[/C][C]0.0620544[/C][C]0.0310272[/C][/ROW]
[ROW][C]167[/C][C]0.963421[/C][C]0.0731578[/C][C]0.0365789[/C][/ROW]
[ROW][C]168[/C][C]0.958475[/C][C]0.083051[/C][C]0.0415255[/C][/ROW]
[ROW][C]169[/C][C]0.981018[/C][C]0.0379643[/C][C]0.0189821[/C][/ROW]
[ROW][C]170[/C][C]0.982932[/C][C]0.0341366[/C][C]0.0170683[/C][/ROW]
[ROW][C]171[/C][C]0.980411[/C][C]0.0391777[/C][C]0.0195889[/C][/ROW]
[ROW][C]172[/C][C]0.977981[/C][C]0.0440377[/C][C]0.0220188[/C][/ROW]
[ROW][C]173[/C][C]0.98334[/C][C]0.0333197[/C][C]0.0166598[/C][/ROW]
[ROW][C]174[/C][C]0.979287[/C][C]0.0414253[/C][C]0.0207127[/C][/ROW]
[ROW][C]175[/C][C]0.979862[/C][C]0.0402766[/C][C]0.0201383[/C][/ROW]
[ROW][C]176[/C][C]0.97544[/C][C]0.0491204[/C][C]0.0245602[/C][/ROW]
[ROW][C]177[/C][C]0.979847[/C][C]0.040306[/C][C]0.020153[/C][/ROW]
[ROW][C]178[/C][C]0.976519[/C][C]0.0469627[/C][C]0.0234814[/C][/ROW]
[ROW][C]179[/C][C]0.971087[/C][C]0.0578259[/C][C]0.028913[/C][/ROW]
[ROW][C]180[/C][C]0.964639[/C][C]0.0707229[/C][C]0.0353614[/C][/ROW]
[ROW][C]181[/C][C]0.965983[/C][C]0.0680332[/C][C]0.0340166[/C][/ROW]
[ROW][C]182[/C][C]0.962218[/C][C]0.0755646[/C][C]0.0377823[/C][/ROW]
[ROW][C]183[/C][C]0.9613[/C][C]0.0774009[/C][C]0.0387004[/C][/ROW]
[ROW][C]184[/C][C]0.955061[/C][C]0.0898785[/C][C]0.0449393[/C][/ROW]
[ROW][C]185[/C][C]0.961491[/C][C]0.077017[/C][C]0.0385085[/C][/ROW]
[ROW][C]186[/C][C]0.961987[/C][C]0.076026[/C][C]0.038013[/C][/ROW]
[ROW][C]187[/C][C]0.954317[/C][C]0.0913668[/C][C]0.0456834[/C][/ROW]
[ROW][C]188[/C][C]0.949338[/C][C]0.101324[/C][C]0.0506621[/C][/ROW]
[ROW][C]189[/C][C]0.939775[/C][C]0.12045[/C][C]0.0602251[/C][/ROW]
[ROW][C]190[/C][C]0.950249[/C][C]0.0995028[/C][C]0.0497514[/C][/ROW]
[ROW][C]191[/C][C]0.941534[/C][C]0.116933[/C][C]0.0584663[/C][/ROW]
[ROW][C]192[/C][C]0.961659[/C][C]0.0766817[/C][C]0.0383409[/C][/ROW]
[ROW][C]193[/C][C]0.957269[/C][C]0.0854611[/C][C]0.0427306[/C][/ROW]
[ROW][C]194[/C][C]0.951241[/C][C]0.0975176[/C][C]0.0487588[/C][/ROW]
[ROW][C]195[/C][C]0.941046[/C][C]0.117909[/C][C]0.0589545[/C][/ROW]
[ROW][C]196[/C][C]0.930233[/C][C]0.139534[/C][C]0.0697671[/C][/ROW]
[ROW][C]197[/C][C]0.923327[/C][C]0.153346[/C][C]0.0766728[/C][/ROW]
[ROW][C]198[/C][C]0.919239[/C][C]0.161521[/C][C]0.0807607[/C][/ROW]
[ROW][C]199[/C][C]0.925401[/C][C]0.149198[/C][C]0.0745992[/C][/ROW]
[ROW][C]200[/C][C]0.920016[/C][C]0.159968[/C][C]0.0799839[/C][/ROW]
[ROW][C]201[/C][C]0.91202[/C][C]0.17596[/C][C]0.0879798[/C][/ROW]
[ROW][C]202[/C][C]0.922401[/C][C]0.155198[/C][C]0.0775992[/C][/ROW]
[ROW][C]203[/C][C]0.907441[/C][C]0.185118[/C][C]0.0925592[/C][/ROW]
[ROW][C]204[/C][C]0.922834[/C][C]0.154331[/C][C]0.0771657[/C][/ROW]
[ROW][C]205[/C][C]0.912462[/C][C]0.175075[/C][C]0.0875377[/C][/ROW]
[ROW][C]206[/C][C]0.901738[/C][C]0.196523[/C][C]0.0982616[/C][/ROW]
[ROW][C]207[/C][C]0.89855[/C][C]0.202899[/C][C]0.10145[/C][/ROW]
[ROW][C]208[/C][C]0.885936[/C][C]0.228128[/C][C]0.114064[/C][/ROW]
[ROW][C]209[/C][C]0.8681[/C][C]0.2638[/C][C]0.1319[/C][/ROW]
[ROW][C]210[/C][C]0.852803[/C][C]0.294394[/C][C]0.147197[/C][/ROW]
[ROW][C]211[/C][C]0.880318[/C][C]0.239364[/C][C]0.119682[/C][/ROW]
[ROW][C]212[/C][C]0.875865[/C][C]0.24827[/C][C]0.124135[/C][/ROW]
[ROW][C]213[/C][C]0.891116[/C][C]0.217768[/C][C]0.108884[/C][/ROW]
[ROW][C]214[/C][C]0.875684[/C][C]0.248632[/C][C]0.124316[/C][/ROW]
[ROW][C]215[/C][C]0.85596[/C][C]0.288081[/C][C]0.14404[/C][/ROW]
[ROW][C]216[/C][C]0.836519[/C][C]0.326961[/C][C]0.163481[/C][/ROW]
[ROW][C]217[/C][C]0.831273[/C][C]0.337454[/C][C]0.168727[/C][/ROW]
[ROW][C]218[/C][C]0.808305[/C][C]0.38339[/C][C]0.191695[/C][/ROW]
[ROW][C]219[/C][C]0.831478[/C][C]0.337044[/C][C]0.168522[/C][/ROW]
[ROW][C]220[/C][C]0.808769[/C][C]0.382461[/C][C]0.191231[/C][/ROW]
[ROW][C]221[/C][C]0.788259[/C][C]0.423481[/C][C]0.211741[/C][/ROW]
[ROW][C]222[/C][C]0.766987[/C][C]0.466026[/C][C]0.233013[/C][/ROW]
[ROW][C]223[/C][C]0.751345[/C][C]0.497311[/C][C]0.248655[/C][/ROW]
[ROW][C]224[/C][C]0.720725[/C][C]0.55855[/C][C]0.279275[/C][/ROW]
[ROW][C]225[/C][C]0.71108[/C][C]0.57784[/C][C]0.28892[/C][/ROW]
[ROW][C]226[/C][C]0.680562[/C][C]0.638877[/C][C]0.319438[/C][/ROW]
[ROW][C]227[/C][C]0.641013[/C][C]0.717974[/C][C]0.358987[/C][/ROW]
[ROW][C]228[/C][C]0.604791[/C][C]0.790418[/C][C]0.395209[/C][/ROW]
[ROW][C]229[/C][C]0.610321[/C][C]0.779357[/C][C]0.389679[/C][/ROW]
[ROW][C]230[/C][C]0.572895[/C][C]0.854209[/C][C]0.427105[/C][/ROW]
[ROW][C]231[/C][C]0.536096[/C][C]0.927808[/C][C]0.463904[/C][/ROW]
[ROW][C]232[/C][C]0.537102[/C][C]0.925796[/C][C]0.462898[/C][/ROW]
[ROW][C]233[/C][C]0.564058[/C][C]0.871884[/C][C]0.435942[/C][/ROW]
[ROW][C]234[/C][C]0.556472[/C][C]0.887057[/C][C]0.443528[/C][/ROW]
[ROW][C]235[/C][C]0.633114[/C][C]0.733771[/C][C]0.366886[/C][/ROW]
[ROW][C]236[/C][C]0.60228[/C][C]0.795439[/C][C]0.39772[/C][/ROW]
[ROW][C]237[/C][C]0.601248[/C][C]0.797504[/C][C]0.398752[/C][/ROW]
[ROW][C]238[/C][C]0.629399[/C][C]0.741202[/C][C]0.370601[/C][/ROW]
[ROW][C]239[/C][C]0.588099[/C][C]0.823803[/C][C]0.411901[/C][/ROW]
[ROW][C]240[/C][C]0.567954[/C][C]0.864092[/C][C]0.432046[/C][/ROW]
[ROW][C]241[/C][C]0.545426[/C][C]0.909148[/C][C]0.454574[/C][/ROW]
[ROW][C]242[/C][C]0.507217[/C][C]0.985567[/C][C]0.492783[/C][/ROW]
[ROW][C]243[/C][C]0.67662[/C][C]0.64676[/C][C]0.32338[/C][/ROW]
[ROW][C]244[/C][C]0.645855[/C][C]0.708289[/C][C]0.354145[/C][/ROW]
[ROW][C]245[/C][C]0.683578[/C][C]0.632844[/C][C]0.316422[/C][/ROW]
[ROW][C]246[/C][C]0.652184[/C][C]0.695631[/C][C]0.347816[/C][/ROW]
[ROW][C]247[/C][C]0.612782[/C][C]0.774436[/C][C]0.387218[/C][/ROW]
[ROW][C]248[/C][C]0.584674[/C][C]0.830652[/C][C]0.415326[/C][/ROW]
[ROW][C]249[/C][C]0.621011[/C][C]0.757977[/C][C]0.378989[/C][/ROW]
[ROW][C]250[/C][C]0.600939[/C][C]0.798122[/C][C]0.399061[/C][/ROW]
[ROW][C]251[/C][C]0.592054[/C][C]0.815893[/C][C]0.407946[/C][/ROW]
[ROW][C]252[/C][C]0.616157[/C][C]0.767685[/C][C]0.383843[/C][/ROW]
[ROW][C]253[/C][C]0.56871[/C][C]0.862581[/C][C]0.43129[/C][/ROW]
[ROW][C]254[/C][C]0.511597[/C][C]0.976806[/C][C]0.488403[/C][/ROW]
[ROW][C]255[/C][C]0.454828[/C][C]0.909655[/C][C]0.545172[/C][/ROW]
[ROW][C]256[/C][C]0.397629[/C][C]0.795259[/C][C]0.602371[/C][/ROW]
[ROW][C]257[/C][C]0.360635[/C][C]0.721271[/C][C]0.639365[/C][/ROW]
[ROW][C]258[/C][C]0.317537[/C][C]0.635073[/C][C]0.682463[/C][/ROW]
[ROW][C]259[/C][C]0.311777[/C][C]0.623554[/C][C]0.688223[/C][/ROW]
[ROW][C]260[/C][C]0.346008[/C][C]0.692016[/C][C]0.653992[/C][/ROW]
[ROW][C]261[/C][C]0.295958[/C][C]0.591915[/C][C]0.704042[/C][/ROW]
[ROW][C]262[/C][C]0.246453[/C][C]0.492906[/C][C]0.753547[/C][/ROW]
[ROW][C]263[/C][C]0.287601[/C][C]0.575201[/C][C]0.712399[/C][/ROW]
[ROW][C]264[/C][C]0.251799[/C][C]0.503599[/C][C]0.748201[/C][/ROW]
[ROW][C]265[/C][C]0.268669[/C][C]0.537338[/C][C]0.731331[/C][/ROW]
[ROW][C]266[/C][C]0.833818[/C][C]0.332364[/C][C]0.166182[/C][/ROW]
[ROW][C]267[/C][C]0.800269[/C][C]0.399461[/C][C]0.199731[/C][/ROW]
[ROW][C]268[/C][C]0.999543[/C][C]0.000913947[/C][C]0.000456973[/C][/ROW]
[ROW][C]269[/C][C]0.999992[/C][C]1.59453e-05[/C][C]7.97264e-06[/C][/ROW]
[ROW][C]270[/C][C]0.999978[/C][C]4.37649e-05[/C][C]2.18825e-05[/C][/ROW]
[ROW][C]271[/C][C]0.999974[/C][C]5.14595e-05[/C][C]2.57297e-05[/C][/ROW]
[ROW][C]272[/C][C]0.999965[/C][C]7.08526e-05[/C][C]3.54263e-05[/C][/ROW]
[ROW][C]273[/C][C]0.999912[/C][C]0.000176317[/C][C]8.81585e-05[/C][/ROW]
[ROW][C]274[/C][C]0.999616[/C][C]0.00076839[/C][C]0.000384195[/C][/ROW]
[ROW][C]275[/C][C]0.99925[/C][C]0.00150001[/C][C]0.000750007[/C][/ROW]
[ROW][C]276[/C][C]0.996837[/C][C]0.00632538[/C][C]0.00316269[/C][/ROW]
[ROW][C]277[/C][C]0.987781[/C][C]0.0244379[/C][C]0.012219[/C][/ROW]
[ROW][C]278[/C][C]0.966239[/C][C]0.0675219[/C][C]0.033761[/C][/ROW]
[ROW][C]279[/C][C]0.997518[/C][C]0.00496357[/C][C]0.00248178[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268752&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268752&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
80.9767610.04647750.0232387
90.9529860.09402770.0470138
100.9320340.1359320.0679661
110.9427490.1145020.0572512
120.9074930.1850150.0925073
130.9290690.1418620.0709312
140.900090.199820.0999098
150.8569490.2861030.143051
160.8098030.3803940.190197
170.7817160.4365690.218284
180.7344520.5310960.265548
190.6703990.6592020.329601
200.6221640.7556720.377836
210.5512520.8974960.448748
220.6248240.7503530.375176
230.5936810.8126380.406319
240.529040.941920.47096
250.486390.972780.51361
260.4290440.8580880.570956
270.3764910.7529810.623509
280.3193280.6386560.680672
290.3629850.7259690.637015
300.3276430.6552860.672357
310.304330.608660.69567
320.2756080.5512160.724392
330.2756870.5513740.724313
340.383120.7662410.61688
350.3364450.672890.663555
360.3707580.7415170.629242
370.3287190.6574380.671281
380.2907070.5814150.709293
390.2511530.5023060.748847
400.2508960.5017910.749104
410.2972470.5944940.702753
420.2686890.5373770.731311
430.3928950.7857910.607105
440.3552890.7105780.644711
450.336170.672340.66383
460.3044810.6089630.695519
470.2951120.5902250.704888
480.2593940.5187880.740606
490.2307010.4614010.769299
500.3217960.6435910.678204
510.3664620.7329240.633538
520.3617340.7234680.638266
530.3259340.6518670.674066
540.3635240.7270490.636476
550.3421330.6842650.657867
560.3527510.7055020.647249
570.3636630.7273270.636337
580.3324740.6649480.667526
590.4555610.9111210.544439
600.547130.9057390.45287
610.5077630.9844740.492237
620.5366970.9266050.463303
630.525090.949820.47491
640.5058510.9882980.494149
650.5413390.9173230.458661
660.609740.7805190.39026
670.584820.830360.41518
680.5521040.8957920.447896
690.5412320.9175370.458768
700.5065360.9869270.493464
710.5147690.9704610.485231
720.4935870.9871730.506413
730.4614380.9228770.538562
740.4317190.8634390.568281
750.4048680.8097350.595132
760.4078750.815750.592125
770.5267130.9465740.473287
780.51070.97860.4893
790.4875820.9751640.512418
800.4786140.9572290.521386
810.4675670.9351350.532433
820.4428340.8856670.557166
830.5029290.9941420.497071
840.4713340.9426670.528666
850.5041470.9917060.495853
860.4733870.9467740.526613
870.5822640.8354710.417736
880.5657590.8684830.434241
890.5344080.9311850.465592
900.5018010.9963980.498199
910.4689280.9378560.531072
920.4667850.9335690.533215
930.4928590.9857170.507141
940.5093910.9812180.490609
950.6393990.7212020.360601
960.6161520.7676960.383848
970.6113140.7773710.388686
980.658190.683620.34181
990.6404660.7190690.359534
1000.6648140.6703720.335186
1010.6469820.7060350.353018
1020.7010630.5978740.298937
1030.7817540.4364910.218246
1040.7610690.4778610.238931
1050.7428910.5142180.257109
1060.739740.520520.26026
1070.7533920.4932160.246608
1080.7774290.4451420.222571
1090.7964150.407170.203585
1100.8005630.3988750.199437
1110.8999840.2000320.100016
1120.931120.1377610.0688804
1130.934510.130980.0654901
1140.9289710.1420580.071029
1150.9230610.1538780.076939
1160.9556040.08879130.0443957
1170.956910.08618050.0430903
1180.9632210.07355770.0367789
1190.9694820.06103510.0305176
1200.963940.07211970.0360599
1210.9675180.06496470.0324823
1220.9633140.07337160.0366858
1230.9675510.0648980.032449
1240.9711050.05778990.0288949
1250.9809140.03817110.0190855
1260.9781930.04361440.0218072
1270.9889270.0221450.0110725
1280.9904910.01901760.00950882
1290.9883730.0232530.0116265
1300.9865790.02684230.0134212
1310.987210.0255810.0127905
1320.9871490.02570260.0128513
1330.9864380.02712380.0135619
1340.9850990.02980110.0149005
1350.9832620.0334750.0167375
1360.981950.03609990.0180499
1370.9784280.04314310.0215715
1380.9752770.04944580.0247229
1390.9712510.05749880.0287494
1400.979870.0402590.0201295
1410.9849520.03009520.0150476
1420.9818170.03636570.0181829
1430.9781080.04378340.0218917
1440.9741070.05178590.025893
1450.9780120.04397530.0219876
1460.9769340.04613130.0230656
1470.9743280.05134360.0256718
1480.9719990.05600210.0280011
1490.9671840.06563220.0328161
1500.9645830.07083370.0354169
1510.9602880.0794240.039712
1520.955020.0899610.0449805
1530.9475380.1049230.0524617
1540.9519940.0960130.0480065
1550.9469290.1061420.053071
1560.9808050.03838990.0191949
1570.9787540.04249290.0212465
1580.9766070.04678690.0233934
1590.9716020.05679630.0283982
1600.9763810.04723730.0236187
1610.9717540.05649160.0282458
1620.9698920.06021580.0301079
1630.9686090.06278280.0313914
1640.9639250.07214990.0360749
1650.9575270.0849450.0424725
1660.9689730.06205440.0310272
1670.9634210.07315780.0365789
1680.9584750.0830510.0415255
1690.9810180.03796430.0189821
1700.9829320.03413660.0170683
1710.9804110.03917770.0195889
1720.9779810.04403770.0220188
1730.983340.03331970.0166598
1740.9792870.04142530.0207127
1750.9798620.04027660.0201383
1760.975440.04912040.0245602
1770.9798470.0403060.020153
1780.9765190.04696270.0234814
1790.9710870.05782590.028913
1800.9646390.07072290.0353614
1810.9659830.06803320.0340166
1820.9622180.07556460.0377823
1830.96130.07740090.0387004
1840.9550610.08987850.0449393
1850.9614910.0770170.0385085
1860.9619870.0760260.038013
1870.9543170.09136680.0456834
1880.9493380.1013240.0506621
1890.9397750.120450.0602251
1900.9502490.09950280.0497514
1910.9415340.1169330.0584663
1920.9616590.07668170.0383409
1930.9572690.08546110.0427306
1940.9512410.09751760.0487588
1950.9410460.1179090.0589545
1960.9302330.1395340.0697671
1970.9233270.1533460.0766728
1980.9192390.1615210.0807607
1990.9254010.1491980.0745992
2000.9200160.1599680.0799839
2010.912020.175960.0879798
2020.9224010.1551980.0775992
2030.9074410.1851180.0925592
2040.9228340.1543310.0771657
2050.9124620.1750750.0875377
2060.9017380.1965230.0982616
2070.898550.2028990.10145
2080.8859360.2281280.114064
2090.86810.26380.1319
2100.8528030.2943940.147197
2110.8803180.2393640.119682
2120.8758650.248270.124135
2130.8911160.2177680.108884
2140.8756840.2486320.124316
2150.855960.2880810.14404
2160.8365190.3269610.163481
2170.8312730.3374540.168727
2180.8083050.383390.191695
2190.8314780.3370440.168522
2200.8087690.3824610.191231
2210.7882590.4234810.211741
2220.7669870.4660260.233013
2230.7513450.4973110.248655
2240.7207250.558550.279275
2250.711080.577840.28892
2260.6805620.6388770.319438
2270.6410130.7179740.358987
2280.6047910.7904180.395209
2290.6103210.7793570.389679
2300.5728950.8542090.427105
2310.5360960.9278080.463904
2320.5371020.9257960.462898
2330.5640580.8718840.435942
2340.5564720.8870570.443528
2350.6331140.7337710.366886
2360.602280.7954390.39772
2370.6012480.7975040.398752
2380.6293990.7412020.370601
2390.5880990.8238030.411901
2400.5679540.8640920.432046
2410.5454260.9091480.454574
2420.5072170.9855670.492783
2430.676620.646760.32338
2440.6458550.7082890.354145
2450.6835780.6328440.316422
2460.6521840.6956310.347816
2470.6127820.7744360.387218
2480.5846740.8306520.415326
2490.6210110.7579770.378989
2500.6009390.7981220.399061
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2520.6161570.7676850.383843
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2590.3117770.6235540.688223
2600.3460080.6920160.653992
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2620.2464530.4929060.753547
2630.2876010.5752010.712399
2640.2517990.5035990.748201
2650.2686690.5373380.731331
2660.8338180.3323640.166182
2670.8002690.3994610.199731
2680.9995430.0009139470.000456973
2690.9999921.59453e-057.97264e-06
2700.9999784.37649e-052.18825e-05
2710.9999745.14595e-052.57297e-05
2720.9999657.08526e-053.54263e-05
2730.9999120.0001763178.81585e-05
2740.9996160.000768390.000384195
2750.999250.001500010.000750007
2760.9968370.006325380.00316269
2770.9877810.02443790.012219
2780.9662390.06752190.033761
2790.9975180.004963570.00248178






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 level880.323529NOK

\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 & 88 & 0.323529 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268752&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]88[/C][C]0.323529[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268752&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268752&T=6

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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 level880.323529NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; 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):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '5'
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')
}