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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 13:46:04 +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/t1418655450g9s5qutfjcuyuo4.htm/, Retrieved Thu, 31 Oct 2024 23:08:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268567, Retrieved Thu, 31 Oct 2024 23:08:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2013-11-04 07:18:26] [0307e7a6407eb638caabc417e3a6b260]
- RMPD    [Multiple Regression] [] [2014-12-15 13:46:04] [baa7d013c3374cabca6c222951a47a9f] [Current]
- RM        [Multiple Regression] [] [2014-12-15 17:46:30] [ea990983fba95a758c0bb6d29c9aee24]
- RMPD        [Multiple Regression] [] [2014-12-17 12:33:34] [ea990983fba95a758c0bb6d29c9aee24]
- RMPD        [Skewness and Kurtosis Test] [] [2014-12-17 12:37:52] [ea990983fba95a758c0bb6d29c9aee24]
- RM        [Multiple Regression] [] [2014-12-16 11:38:14] [ea990983fba95a758c0bb6d29c9aee24]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
149	96	18	68	86	7.5
152	75	7	55	62	2.5
139	70	31	39	70	6.0
148	88	39	32	71	6.5
158	114	46	62	108	1.0
128	69	31	33	64	1.0
224	176	67	52	119	5.5
159	114	35	62	97	8.5
105	121	52	77	129	6.5
159	110	77	76	153	4.5
167	158	37	41	78	2.0
165	116	32	48	80	5.0
159	181	36	63	99	0.5
119	77	38	30	68	5.0
176	141	69	78	147	5.0
54	35	21	19	40	2.5
91	80	26	31	57	5.0
163	152	54	66	120	5.5
124	97	36	35	71	3.5
137	99	42	42	84	3.0
121	84	23	45	68	4.0
153	68	34	21	55	0.5
148	101	112	25	137	6.5
221	107	35	44	79	4.5
188	88	47	69	116	7.5
149	112	47	54	101	5.5
244	171	37	74	111	4.0
148	137	109	80	189	7.5
92	77	24	42	66	7.0
150	66	20	61	81	4.0
153	93	22	41	63	5.5
94	105	23	46	69	2.5
156	131	32	39	71	5.5
146	89	7	63	70	0.5
132	102	30	34	64	3.5
161	161	92	51	143	2.5
105	120	43	42	85	4.5
97	127	55	31	86	4.5
151	77	16	39	55	4.5
131	108	49	20	69	6.0
166	85	71	49	120	2.5
157	168	43	53	96	5.0
111	48	29	31	60	0.0
145	152	56	39	95	5.0
162	75	46	54	100	6.5
163	107	19	49	68	5.0
59	62	23	34	57	6.0
187	121	59	46	105	4.5
109	124	30	55	85	5.5
90	72	61	42	103	1.0
105	40	7	50	57	7.5
83	58	38	13	51	6.0
116	97	32	37	69	5.0
42	88	16	25	41	1.0
148	126	19	30	49	5.0
155	104	22	28	50	6.5
125	148	48	45	93	7.0
116	146	23	35	58	4.5
128	80	26	28	54	0.0
138	97	33	41	74	8.5
49	25	9	6	15	3.5
96	99	24	45	69	7.5
164	118	34	73	107	3.5
162	58	48	17	65	6.0
99	63	18	40	58	1.5
202	139	43	64	107	9.0
186	50	33	37	70	3.5
66	60	28	25	53	3.5
183	152	71	65	136	4.0
214	142	26	100	126	6.5
188	94	67	28	95	7.5
104	66	34	35	69	6.0
177	127	80	56	136	5.0
126	67	29	29	58	5.5
76	90	16	43	59	3.5
99	75	59	59	118	7.5
157	96	58	52	110	1.0
139	128	32	50	82	6.5
78	41	47	3	50	NA
162	146	43	59	102	6.5
108	69	38	27	65	6.5
159	186	29	61	90	7.0
74	81	36	28	64	3.5
110	85	32	51	83	1.5
96	54	35	35	70	4.0
116	46	21	29	50	7.5
87	106	29	48	77	4.5
97	34	12	25	37	0.0
127	60	37	44	81	3.5
106	95	37	64	101	5.5
80	57	47	32	79	5.0
74	62	51	20	71	4.5
91	36	32	28	60	2.5
133	56	21	34	55	7.5
74	54	13	31	44	7.0
114	64	14	26	40	0.0
140	76	-2	58	56	4.5
95	98	20	23	43	3.0
98	88	24	21	45	1.5
121	35	11	21	32	3.5
126	102	23	33	56	2.5
98	61	24	16	40	5.5
95	80	14	20	34	8.0
110	49	52	37	89	1.0
70	78	15	35	50	5.0
102	90	23	33	56	4.5
86	45	19	27	46	3.0
130	55	35	41	76	3.0
96	96	24	40	64	8.0
102	43	39	35	74	2.5
100	52	29	28	57	7.0
94	60	13	32	45	0.0
52	54	8	22	30	1.0
98	51	18	44	62	3.5
118	51	24	27	51	5.5
99	38	19	17	36	5.5
48	41	23	12	34	0.5
50	146	16	45	61	7.5
150	182	33	37	70	9
154	192	32	37	69	9.5
109	263	37	108	145	8.5
68	35	14	10	23	7
194	439	52	68	120	8
158	214	75	72	147	10
159	341	72	143	215	7
67	58	15	9	24	8.5
147	292	29	55	84	9
39	85	13	17	30	9.5
100	200	40	37	77	4
111	158	19	27	46	6
138	199	24	37	61	8
101	297	121	58	178	5.5
131	227	93	66	160	9.5
101	108	36	21	57	7.5
114	86	23	19	42	7
165	302	85	78	163	7.5
114	148	41	35	75	8
111	178	46	48	94	7
75	120	18	27	45	7
82	207	35	43	78	6
121	157	17	30	47	10
32	128	4	25	29	2.5
150	296	28	69	97	9
117	323	44	72	116	8
71	79	10	23	32	6
165	70	38	13	50	8.5
154	146	57	61	118	6
126	246	23	43	66	9
138	145	26	22	48	8
149	196	36	51	86	8
145	199	22	67	89	9
120	127	40	36	76	5.5
138	91	18	21	39	5
109	153	31	44	75	7
132	299	11	45	57	5.5
172	228	38	34	72	9
169	190	24	36	60	2
114	180	37	72	109	8.5
156	212	37	39	76	9
172	269	22	43	65	8.5
68	130	15	25	40	9
89	179	2	56	58	7.5
167	243	43	80	123	10
113	190	31	40	71	9
115	299	29	73	102	7.5
78	121	45	34	80	6
118	137	25	72	97	10.5
87	305	4	42	46	8.5
173	157	31	61	93	8
2	96	-4	23	19	10
162	183	66	74	140	10.5
49	52	61	16	78	6.5
122	238	32	66	98	9.5
96	40	31	9	40	8.5
100	226	39	41	80	7.5
82	190	19	57	76	5
100	214	31	48	79	8
115	145	36	51	87	10
141	119	42	53	95	7
165	222	21	29	49	7.5
165	222	21	29	49	7.5
110	159	25	55	80	9.5
118	165	32	54	86	6
158	249	26	43	69	10
146	125	28	51	79	7
49	122	32	20	52	3
90	186	41	79	120	6
121	148	29	39	69	7
155	274	33	61	94	10
104	172	17	55	72	7
147	84	13	30	43	3.5
110	168	32	55	87	8
108	102	30	22	52	10
113	106	34	37	71	5.5
115	2	59	2	61	6
61	139	13	38	51	6.5
60	95	23	27	50	6.5
109	130	10	56	67	8.5
68	72	5	25	30	4
111	141	31	39	70	9.5
77	113	19	33	52	8
73	206	32	43	75	8.5
151	268	30	57	87	5.5
89	175	25	43	69	7
78	77	48	23	72	9
110	125	35	44	79	8
220	255	67	54	121	10
65	111	15	28	43	8
141	132	22	36	58	6
117	211	18	39	57	8
122	92	33	16	50	5
63	76	46	23	69	9
44	171	24	40	64	4.5
52	83	14	24	38	8.5
62	119	23	29	53	7
131	266	12	78	90	9.5
101	186	38	57	96	8.5
42	50	12	37	49	7.5
152	117	28	27	56	7.5
107	219	41	61	102	5
77	246	12	27	40	7
154	279	31	69	100	8
103	148	33	34	67	5.5
96	137	34	44	78	8.5
154	130	41	21	62	7.5
175	181	21	34	55	9.5
57	98	20	39	59	7
112	226	44	51	96	8
143	234	52	34	86	8.5
49	138	7	31	38	3.5
110	85	29	13	43	6.5
131	66	11	12	23	6.5
167	236	26	51	77	10.5
56	106	24	24	48	8.5
137	135	7	19	26	8
86	122	60	30	91	10
121	218	13	81	94	10
149	199	20	42	62	9.5
168	112	52	22	74	9
140	278	28	85	114	10
88	94	25	27	52	7.5
168	113	39	25	64	4.5
94	84	9	22	31	4.5
51	86	19	19	38	0.5
48	62	13	14	27	6.5
145	222	60	45	105	4.5
66	167	19	45	64	5.5
85	82	34	28	62	5
109	207	14	51	65	6
63	184	17	41	58	4
102	83	45	31	76	8
162	183	66	74	140	10.5
128	85	24	24	48	8.5
86	89	48	19	68	6.5
114	225	29	51	80	8
164	237	-2	73	71	8.5
119	102	51	24	76	5.5
126	221	2	61	63	7
132	128	24	23	46	5
142	91	40	14	53	3.5
83	198	20	54	74	5
94	204	19	51	70	9
81	158	16	62	78	8.5
166	138	20	36	56	5
110	226	40	59	100	9.5
64	44	27	24	51	3
93	196	25	26	52	1.5
104	83	49	54	102	6
105	79	39	39	78	0.5
49	52	61	16	78	6.5
88	105	19	36	55	7.5
95	116	67	31	98	4.5
102	83	45	31	76	8
99	196	30	42	73	9
63	153	8	39	47	7.5
76	157	19	25	45	8.5
109	75	52	31	83	7
117	106	22	38	60	9.5
57	58	17	31	48	6.5
120	75	33	17	50	9.5
73	74	34	22	56	6
91	185	22	55	77	8
108	265	30	62	91	9.5
105	131	25	51	76	8
117	139	38	30	68	8
119	196	26	49	74	9
31	78	13	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 time10 seconds
R Server'George Udny Yule' @ yule.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 & 10 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268567&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268567&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268567&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 time10 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.369 -0.00211222LFM[t] + 0.017855B[t] -0.457237PRH[t] -0.463033CH[t] + 0.455683H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.369 -0.00211222LFM[t] +  0.017855B[t] -0.457237PRH[t] -0.463033CH[t] +  0.455683H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268567&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.369 -0.00211222LFM[t] +  0.017855B[t] -0.457237PRH[t] -0.463033CH[t] +  0.455683H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268567&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268567&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] = + 4.369 -0.00211222LFM[t] + 0.017855B[t] -0.457237PRH[t] -0.463033CH[t] + 0.455683H[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.3690.4585469.5288.02511e-194.01255e-19
LFM-0.002112220.00403175-0.52390.6007650.300383
B0.0178550.002431197.3442.26714e-121.13357e-12
PRH-0.4572370.373998-1.2230.2225230.111261
CH-0.4630330.373473-1.240.2160860.108043
H0.4556830.373341.2210.2232810.111641

\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) & 4.369 & 0.458546 & 9.528 & 8.02511e-19 & 4.01255e-19 \tabularnewline
LFM & -0.00211222 & 0.00403175 & -0.5239 & 0.600765 & 0.300383 \tabularnewline
B & 0.017855 & 0.00243119 & 7.344 & 2.26714e-12 & 1.13357e-12 \tabularnewline
PRH & -0.457237 & 0.373998 & -1.223 & 0.222523 & 0.111261 \tabularnewline
CH & -0.463033 & 0.373473 & -1.24 & 0.216086 & 0.108043 \tabularnewline
H & 0.455683 & 0.37334 & 1.221 & 0.223281 & 0.111641 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268567&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]4.369[/C][C]0.458546[/C][C]9.528[/C][C]8.02511e-19[/C][C]4.01255e-19[/C][/ROW]
[ROW][C]LFM[/C][C]-0.00211222[/C][C]0.00403175[/C][C]-0.5239[/C][C]0.600765[/C][C]0.300383[/C][/ROW]
[ROW][C]B[/C][C]0.017855[/C][C]0.00243119[/C][C]7.344[/C][C]2.26714e-12[/C][C]1.13357e-12[/C][/ROW]
[ROW][C]PRH[/C][C]-0.457237[/C][C]0.373998[/C][C]-1.223[/C][C]0.222523[/C][C]0.111261[/C][/ROW]
[ROW][C]CH[/C][C]-0.463033[/C][C]0.373473[/C][C]-1.24[/C][C]0.216086[/C][C]0.108043[/C][/ROW]
[ROW][C]H[/C][C]0.455683[/C][C]0.37334[/C][C]1.221[/C][C]0.223281[/C][C]0.111641[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268567&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268567&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)4.3690.4585469.5288.02511e-194.01255e-19
LFM-0.002112220.00403175-0.52390.6007650.300383
B0.0178550.002431197.3442.26714e-121.13357e-12
PRH-0.4572370.373998-1.2230.2225230.111261
CH-0.4630330.373473-1.240.2160860.108043
H0.4556830.373341.2210.2232810.111641






Multiple Linear Regression - Regression Statistics
Multiple R0.456449
R-squared0.208345
Adjusted R-squared0.194209
F-TEST (value)14.7379
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value7.79821e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29509
Sum Squared Residuals1474.88

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.456449 \tabularnewline
R-squared & 0.208345 \tabularnewline
Adjusted R-squared & 0.194209 \tabularnewline
F-TEST (value) & 14.7379 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 280 \tabularnewline
p-value & 7.79821e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.29509 \tabularnewline
Sum Squared Residuals & 1474.88 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268567&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.456449[/C][/ROW]
[ROW][C]R-squared[/C][C]0.208345[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.194209[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]14.7379[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]280[/C][/ROW]
[ROW][C]p-value[/C][C]7.79821e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.29509[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1474.88[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268567&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268567&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 R0.456449
R-squared0.208345
Adjusted R-squared0.194209
F-TEST (value)14.7379
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value7.79821e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29509
Sum Squared Residuals1474.88






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.240542.25946
22.54.9719-2.4719
364.99041.0096
46.55.33181.1682
515.54351-4.54351
615.03988-4.03988
75.56.55197-1.05197
88.55.558492.94151
96.55.660850.839146
104.55.31889-0.818886
1126.47846-4.47846
1255.6891-0.689097
130.56.74587-6.24587
1455.2129-0.212901
1555.83421-0.834214
162.54.70756-2.20756
1755.33691-0.336908
185.56.1696-0.669597
193.55.52579-2.02579
2035.47327-2.47327
2145.24672-1.24672
220.55.05276-4.55276
236.55.501910.998092
244.55.43486-0.934858
257.54.96292.5371
265.55.58406-0.0840563
2746.30537-2.30537
287.55.745071.75493
2975.203481.79652
3044.75113-0.751125
315.55.370780.129225
322.55.67135-3.17135
335.56.04209-0.542086
340.55.17574-4.67574
353.55.61485-2.11485
362.56.38572-3.88572
374.55.91426-1.41426
384.56.11835-1.61835
394.55.11335-0.613347
4065.797470.202532
412.55.06552-2.56552
4256.5806-1.5806
4304.71864-4.71864
4456.40297-1.40297
456.54.897521.60248
4655.54548-0.545481
4765.065720.93428
484.55.70464-1.20464
495.55.90188-0.401875
5015.06093-4.06093
517.54.483013.01699
5265.074660.925343
5355.53421-0.534208
5415.64289-4.64289
5556.05607-1.05607
566.55.658510.841487
5776.342130.657871
584.56.43779-1.93779
5905.28081-5.28081
608.55.456783.04322
613.54.65378-1.15378
627.55.565791.93421
633.55.54005-2.04005
6464.862851.13715
651.54.96275-3.46275
6695.88693.1131
673.54.54562-1.04562
683.55.07361-1.57361
6946.10828-2.10828
706.55.676920.823078
717.55.340322.15968
7265.017640.982356
7355.72675-0.726749
745.55.04090.459096
753.55.47448-1.97448
767.54.973632.52637
7715.27908-4.27908
786.55.943570.556427
79NANA0.36687
806.55.115351.38465
816.56.360720.139278
8278.89718-1.89718
833.57.22971-3.72971
841.52.31873-0.818728
8541.199512.80049
867.58.67996-1.17996
874.59.06877-4.56877
8801.29112-1.29112
893.53.313380.186616
905.55.409490.0905103
9155.59343-0.593428
924.56.56402-2.06402
932.5-0.1946052.69461
947.55.428792.07121
95712.0581-5.05805
9600.507041-0.507041
974.57.21798-2.71798
9837.04158-4.04158
991.52.56689-1.06689
1003.56.64575-3.14575
1012.52.096250.403755
1025.52.927972.57203
103811.6588-3.65876
10411.33325-0.333248
10555.98218-0.982184
1064.56.26283-1.76283
10734.72066-1.72066
10830.5489792.45102
109810.1034-2.10343
1102.50.3353482.16465
111711.9863-4.98633
11204.04919-4.04919
11312.2212-1.2212
1143.52.794590.705405
1155.54.683890.816111
1165.59.42003-3.92003
1170.5-0.4854310.985431
1187.55.478512.02149
11996.650162.34984
1209.58.983250.516746
1218.55.799352.70065
122710.2169-3.2169
12385.210422.78958
1241011.9587-1.95866
12573.67363.3264
1268.58.32280.177203
12795.159133.84087
1289.512.8946-3.39463
12944.72763-0.727631
13065.321380.678622
131810.8885-2.88851
1325.53.971381.52862
1339.57.873691.62631
1347.55.988331.51167
13578.20723-1.20723
1367.55.494072.00593
13787.888410.111595
13876.126740.873263
13978.5213-1.5213
14062.669713.33029
1411013.8969-3.89686
1422.52.286530.213474
143910.2914-1.29139
14486.989291.01071
14562.160033.83997
1468.58.61357-0.113568
14765.143360.856642
14897.464361.53564
14986.667341.33266
15086.089181.91082
15199.55632-0.556325
1525.56.01998-0.519977
15354.498970.501029
154711.0366-4.03663
1555.54.267651.23235
156914.1026-5.10255
15720.2553521.74465
1588.56.980571.51943
15998.958410.0415863
1608.55.839442.66056
16198.462310.537691
1627.55.200142.29986
163108.180561.81944
164910.3831-1.38306
1657.58.00052-0.500521
16661.497794.50221
16710.511.3161-0.816057
1688.57.265931.23407
16983.9164.084
170106.147763.85224
17110.59.437231.06277
1726.54.825921.67408
1739.55.766093.73391
1748.58.83101-0.331011
1757.59.63973-2.13973
17654.577730.422269
17784.284233.71577
178108.741061.25894
17976.78280.217204
1807.57.28280.217204
1817.54.532462.96754
1829.510.1192-0.61916
18364.124671.87533
184108.874091.12591
185710.2471-3.24706
18633.8555-0.855504
18765.879890.120107
18875.434191.56581
189109.789680.210322
19078.8176-1.8176
1913.52.182271.31773
19283.753754.24625
1931010.1981-0.198131
1945.53.555411.94459
19565.922470.0775331
1966.55.704280.795724
1976.54.488422.01158
1988.59.81939-1.31939
19940.817243.18276
2009.57.451872.04813
20187.027120.97288
2028.511.3696-2.86957
2035.55.90638-0.406382
20473.79113.2089
20596.99072.0093
20685.956262.04374
207107.984482.01552
20888.12922-0.129218
20965.574620.425382
21089.04075-1.04075
21151.352353.64765
212911.4979-2.49794
2134.51.542952.95705
2148.58.069550.430449
21575.749721.25028
2169.58.454331.04567
2178.55.882412.61759
2187.56.350671.14933
2197.510.0411-2.54112
22056.83724-1.83724
22177.46988-0.469881
22288.99277-0.992767
2235.53.236092.26391
2248.57.146781.35322
2257.54.948552.55145
2269.58.180631.31937
22777.18007-0.18007
22887.414270.585726
2298.511.4907-2.99074
2303.52.969380.530619
2316.55.165421.33458
2326.53.814742.68526
23310.57.929632.57037
2348.56.83951.6605
23584.507573.49243
236107.39022.6098
237107.767612.23239
2389.56.271373.22863
23997.824331.17567
240108.124171.87583
2417.58.78738-1.28738
2424.55.49457-0.994567
2434.59.62761-5.12761
2440.5-0.7484921.24849
2456.59.6025-3.1025
2464.55.85107-1.35107
2475.55.89491-0.394909
24856.43811-1.43811
24969.19345-3.19345
25041.337712.66229
25184.147763.85224
25210.57.402593.09741
2538.58.017860.482139
2546.56.225620.274379
25587.220740.779264
2568.59.13886-0.638856
2575.56.09731-0.597312
25877.71357-0.713575
25956.57311-1.57311
2603.55.80095-2.30095
26153.408451.59155
26297.038391.96161
2638.59.68665-1.18665
26453.631711.36829
2659.511.3011-1.80106
26639.39785-6.39785
2671.50.2025221.29748
268610.7105-4.71047
2690.5-0.5627731.06277
2706.54.763741.73626
2717.58.90752-1.40752
2724.51.837712.66229
27386.759791.24021
27498.168630.831368
2757.56.254091.24591
2768.56.66921.8308
27773.200983.79902
2789.58.02991.4701
2796.52.278414.22159
2809.58.821520.67848
28165.041480.958519
28286.41441.5856
2839.57.572481.92752
28486.324131.67587
28585.760952.23905
28699.55839-0.558394
2875NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.24054 & 2.25946 \tabularnewline
2 & 2.5 & 4.9719 & -2.4719 \tabularnewline
3 & 6 & 4.9904 & 1.0096 \tabularnewline
4 & 6.5 & 5.3318 & 1.1682 \tabularnewline
5 & 1 & 5.54351 & -4.54351 \tabularnewline
6 & 1 & 5.03988 & -4.03988 \tabularnewline
7 & 5.5 & 6.55197 & -1.05197 \tabularnewline
8 & 8.5 & 5.55849 & 2.94151 \tabularnewline
9 & 6.5 & 5.66085 & 0.839146 \tabularnewline
10 & 4.5 & 5.31889 & -0.818886 \tabularnewline
11 & 2 & 6.47846 & -4.47846 \tabularnewline
12 & 5 & 5.6891 & -0.689097 \tabularnewline
13 & 0.5 & 6.74587 & -6.24587 \tabularnewline
14 & 5 & 5.2129 & -0.212901 \tabularnewline
15 & 5 & 5.83421 & -0.834214 \tabularnewline
16 & 2.5 & 4.70756 & -2.20756 \tabularnewline
17 & 5 & 5.33691 & -0.336908 \tabularnewline
18 & 5.5 & 6.1696 & -0.669597 \tabularnewline
19 & 3.5 & 5.52579 & -2.02579 \tabularnewline
20 & 3 & 5.47327 & -2.47327 \tabularnewline
21 & 4 & 5.24672 & -1.24672 \tabularnewline
22 & 0.5 & 5.05276 & -4.55276 \tabularnewline
23 & 6.5 & 5.50191 & 0.998092 \tabularnewline
24 & 4.5 & 5.43486 & -0.934858 \tabularnewline
25 & 7.5 & 4.9629 & 2.5371 \tabularnewline
26 & 5.5 & 5.58406 & -0.0840563 \tabularnewline
27 & 4 & 6.30537 & -2.30537 \tabularnewline
28 & 7.5 & 5.74507 & 1.75493 \tabularnewline
29 & 7 & 5.20348 & 1.79652 \tabularnewline
30 & 4 & 4.75113 & -0.751125 \tabularnewline
31 & 5.5 & 5.37078 & 0.129225 \tabularnewline
32 & 2.5 & 5.67135 & -3.17135 \tabularnewline
33 & 5.5 & 6.04209 & -0.542086 \tabularnewline
34 & 0.5 & 5.17574 & -4.67574 \tabularnewline
35 & 3.5 & 5.61485 & -2.11485 \tabularnewline
36 & 2.5 & 6.38572 & -3.88572 \tabularnewline
37 & 4.5 & 5.91426 & -1.41426 \tabularnewline
38 & 4.5 & 6.11835 & -1.61835 \tabularnewline
39 & 4.5 & 5.11335 & -0.613347 \tabularnewline
40 & 6 & 5.79747 & 0.202532 \tabularnewline
41 & 2.5 & 5.06552 & -2.56552 \tabularnewline
42 & 5 & 6.5806 & -1.5806 \tabularnewline
43 & 0 & 4.71864 & -4.71864 \tabularnewline
44 & 5 & 6.40297 & -1.40297 \tabularnewline
45 & 6.5 & 4.89752 & 1.60248 \tabularnewline
46 & 5 & 5.54548 & -0.545481 \tabularnewline
47 & 6 & 5.06572 & 0.93428 \tabularnewline
48 & 4.5 & 5.70464 & -1.20464 \tabularnewline
49 & 5.5 & 5.90188 & -0.401875 \tabularnewline
50 & 1 & 5.06093 & -4.06093 \tabularnewline
51 & 7.5 & 4.48301 & 3.01699 \tabularnewline
52 & 6 & 5.07466 & 0.925343 \tabularnewline
53 & 5 & 5.53421 & -0.534208 \tabularnewline
54 & 1 & 5.64289 & -4.64289 \tabularnewline
55 & 5 & 6.05607 & -1.05607 \tabularnewline
56 & 6.5 & 5.65851 & 0.841487 \tabularnewline
57 & 7 & 6.34213 & 0.657871 \tabularnewline
58 & 4.5 & 6.43779 & -1.93779 \tabularnewline
59 & 0 & 5.28081 & -5.28081 \tabularnewline
60 & 8.5 & 5.45678 & 3.04322 \tabularnewline
61 & 3.5 & 4.65378 & -1.15378 \tabularnewline
62 & 7.5 & 5.56579 & 1.93421 \tabularnewline
63 & 3.5 & 5.54005 & -2.04005 \tabularnewline
64 & 6 & 4.86285 & 1.13715 \tabularnewline
65 & 1.5 & 4.96275 & -3.46275 \tabularnewline
66 & 9 & 5.8869 & 3.1131 \tabularnewline
67 & 3.5 & 4.54562 & -1.04562 \tabularnewline
68 & 3.5 & 5.07361 & -1.57361 \tabularnewline
69 & 4 & 6.10828 & -2.10828 \tabularnewline
70 & 6.5 & 5.67692 & 0.823078 \tabularnewline
71 & 7.5 & 5.34032 & 2.15968 \tabularnewline
72 & 6 & 5.01764 & 0.982356 \tabularnewline
73 & 5 & 5.72675 & -0.726749 \tabularnewline
74 & 5.5 & 5.0409 & 0.459096 \tabularnewline
75 & 3.5 & 5.47448 & -1.97448 \tabularnewline
76 & 7.5 & 4.97363 & 2.52637 \tabularnewline
77 & 1 & 5.27908 & -4.27908 \tabularnewline
78 & 6.5 & 5.94357 & 0.556427 \tabularnewline
79 & NA & NA & 0.36687 \tabularnewline
80 & 6.5 & 5.11535 & 1.38465 \tabularnewline
81 & 6.5 & 6.36072 & 0.139278 \tabularnewline
82 & 7 & 8.89718 & -1.89718 \tabularnewline
83 & 3.5 & 7.22971 & -3.72971 \tabularnewline
84 & 1.5 & 2.31873 & -0.818728 \tabularnewline
85 & 4 & 1.19951 & 2.80049 \tabularnewline
86 & 7.5 & 8.67996 & -1.17996 \tabularnewline
87 & 4.5 & 9.06877 & -4.56877 \tabularnewline
88 & 0 & 1.29112 & -1.29112 \tabularnewline
89 & 3.5 & 3.31338 & 0.186616 \tabularnewline
90 & 5.5 & 5.40949 & 0.0905103 \tabularnewline
91 & 5 & 5.59343 & -0.593428 \tabularnewline
92 & 4.5 & 6.56402 & -2.06402 \tabularnewline
93 & 2.5 & -0.194605 & 2.69461 \tabularnewline
94 & 7.5 & 5.42879 & 2.07121 \tabularnewline
95 & 7 & 12.0581 & -5.05805 \tabularnewline
96 & 0 & 0.507041 & -0.507041 \tabularnewline
97 & 4.5 & 7.21798 & -2.71798 \tabularnewline
98 & 3 & 7.04158 & -4.04158 \tabularnewline
99 & 1.5 & 2.56689 & -1.06689 \tabularnewline
100 & 3.5 & 6.64575 & -3.14575 \tabularnewline
101 & 2.5 & 2.09625 & 0.403755 \tabularnewline
102 & 5.5 & 2.92797 & 2.57203 \tabularnewline
103 & 8 & 11.6588 & -3.65876 \tabularnewline
104 & 1 & 1.33325 & -0.333248 \tabularnewline
105 & 5 & 5.98218 & -0.982184 \tabularnewline
106 & 4.5 & 6.26283 & -1.76283 \tabularnewline
107 & 3 & 4.72066 & -1.72066 \tabularnewline
108 & 3 & 0.548979 & 2.45102 \tabularnewline
109 & 8 & 10.1034 & -2.10343 \tabularnewline
110 & 2.5 & 0.335348 & 2.16465 \tabularnewline
111 & 7 & 11.9863 & -4.98633 \tabularnewline
112 & 0 & 4.04919 & -4.04919 \tabularnewline
113 & 1 & 2.2212 & -1.2212 \tabularnewline
114 & 3.5 & 2.79459 & 0.705405 \tabularnewline
115 & 5.5 & 4.68389 & 0.816111 \tabularnewline
116 & 5.5 & 9.42003 & -3.92003 \tabularnewline
117 & 0.5 & -0.485431 & 0.985431 \tabularnewline
118 & 7.5 & 5.47851 & 2.02149 \tabularnewline
119 & 9 & 6.65016 & 2.34984 \tabularnewline
120 & 9.5 & 8.98325 & 0.516746 \tabularnewline
121 & 8.5 & 5.79935 & 2.70065 \tabularnewline
122 & 7 & 10.2169 & -3.2169 \tabularnewline
123 & 8 & 5.21042 & 2.78958 \tabularnewline
124 & 10 & 11.9587 & -1.95866 \tabularnewline
125 & 7 & 3.6736 & 3.3264 \tabularnewline
126 & 8.5 & 8.3228 & 0.177203 \tabularnewline
127 & 9 & 5.15913 & 3.84087 \tabularnewline
128 & 9.5 & 12.8946 & -3.39463 \tabularnewline
129 & 4 & 4.72763 & -0.727631 \tabularnewline
130 & 6 & 5.32138 & 0.678622 \tabularnewline
131 & 8 & 10.8885 & -2.88851 \tabularnewline
132 & 5.5 & 3.97138 & 1.52862 \tabularnewline
133 & 9.5 & 7.87369 & 1.62631 \tabularnewline
134 & 7.5 & 5.98833 & 1.51167 \tabularnewline
135 & 7 & 8.20723 & -1.20723 \tabularnewline
136 & 7.5 & 5.49407 & 2.00593 \tabularnewline
137 & 8 & 7.88841 & 0.111595 \tabularnewline
138 & 7 & 6.12674 & 0.873263 \tabularnewline
139 & 7 & 8.5213 & -1.5213 \tabularnewline
140 & 6 & 2.66971 & 3.33029 \tabularnewline
141 & 10 & 13.8969 & -3.89686 \tabularnewline
142 & 2.5 & 2.28653 & 0.213474 \tabularnewline
143 & 9 & 10.2914 & -1.29139 \tabularnewline
144 & 8 & 6.98929 & 1.01071 \tabularnewline
145 & 6 & 2.16003 & 3.83997 \tabularnewline
146 & 8.5 & 8.61357 & -0.113568 \tabularnewline
147 & 6 & 5.14336 & 0.856642 \tabularnewline
148 & 9 & 7.46436 & 1.53564 \tabularnewline
149 & 8 & 6.66734 & 1.33266 \tabularnewline
150 & 8 & 6.08918 & 1.91082 \tabularnewline
151 & 9 & 9.55632 & -0.556325 \tabularnewline
152 & 5.5 & 6.01998 & -0.519977 \tabularnewline
153 & 5 & 4.49897 & 0.501029 \tabularnewline
154 & 7 & 11.0366 & -4.03663 \tabularnewline
155 & 5.5 & 4.26765 & 1.23235 \tabularnewline
156 & 9 & 14.1026 & -5.10255 \tabularnewline
157 & 2 & 0.255352 & 1.74465 \tabularnewline
158 & 8.5 & 6.98057 & 1.51943 \tabularnewline
159 & 9 & 8.95841 & 0.0415863 \tabularnewline
160 & 8.5 & 5.83944 & 2.66056 \tabularnewline
161 & 9 & 8.46231 & 0.537691 \tabularnewline
162 & 7.5 & 5.20014 & 2.29986 \tabularnewline
163 & 10 & 8.18056 & 1.81944 \tabularnewline
164 & 9 & 10.3831 & -1.38306 \tabularnewline
165 & 7.5 & 8.00052 & -0.500521 \tabularnewline
166 & 6 & 1.49779 & 4.50221 \tabularnewline
167 & 10.5 & 11.3161 & -0.816057 \tabularnewline
168 & 8.5 & 7.26593 & 1.23407 \tabularnewline
169 & 8 & 3.916 & 4.084 \tabularnewline
170 & 10 & 6.14776 & 3.85224 \tabularnewline
171 & 10.5 & 9.43723 & 1.06277 \tabularnewline
172 & 6.5 & 4.82592 & 1.67408 \tabularnewline
173 & 9.5 & 5.76609 & 3.73391 \tabularnewline
174 & 8.5 & 8.83101 & -0.331011 \tabularnewline
175 & 7.5 & 9.63973 & -2.13973 \tabularnewline
176 & 5 & 4.57773 & 0.422269 \tabularnewline
177 & 8 & 4.28423 & 3.71577 \tabularnewline
178 & 10 & 8.74106 & 1.25894 \tabularnewline
179 & 7 & 6.7828 & 0.217204 \tabularnewline
180 & 7.5 & 7.2828 & 0.217204 \tabularnewline
181 & 7.5 & 4.53246 & 2.96754 \tabularnewline
182 & 9.5 & 10.1192 & -0.61916 \tabularnewline
183 & 6 & 4.12467 & 1.87533 \tabularnewline
184 & 10 & 8.87409 & 1.12591 \tabularnewline
185 & 7 & 10.2471 & -3.24706 \tabularnewline
186 & 3 & 3.8555 & -0.855504 \tabularnewline
187 & 6 & 5.87989 & 0.120107 \tabularnewline
188 & 7 & 5.43419 & 1.56581 \tabularnewline
189 & 10 & 9.78968 & 0.210322 \tabularnewline
190 & 7 & 8.8176 & -1.8176 \tabularnewline
191 & 3.5 & 2.18227 & 1.31773 \tabularnewline
192 & 8 & 3.75375 & 4.24625 \tabularnewline
193 & 10 & 10.1981 & -0.198131 \tabularnewline
194 & 5.5 & 3.55541 & 1.94459 \tabularnewline
195 & 6 & 5.92247 & 0.0775331 \tabularnewline
196 & 6.5 & 5.70428 & 0.795724 \tabularnewline
197 & 6.5 & 4.48842 & 2.01158 \tabularnewline
198 & 8.5 & 9.81939 & -1.31939 \tabularnewline
199 & 4 & 0.81724 & 3.18276 \tabularnewline
200 & 9.5 & 7.45187 & 2.04813 \tabularnewline
201 & 8 & 7.02712 & 0.97288 \tabularnewline
202 & 8.5 & 11.3696 & -2.86957 \tabularnewline
203 & 5.5 & 5.90638 & -0.406382 \tabularnewline
204 & 7 & 3.7911 & 3.2089 \tabularnewline
205 & 9 & 6.9907 & 2.0093 \tabularnewline
206 & 8 & 5.95626 & 2.04374 \tabularnewline
207 & 10 & 7.98448 & 2.01552 \tabularnewline
208 & 8 & 8.12922 & -0.129218 \tabularnewline
209 & 6 & 5.57462 & 0.425382 \tabularnewline
210 & 8 & 9.04075 & -1.04075 \tabularnewline
211 & 5 & 1.35235 & 3.64765 \tabularnewline
212 & 9 & 11.4979 & -2.49794 \tabularnewline
213 & 4.5 & 1.54295 & 2.95705 \tabularnewline
214 & 8.5 & 8.06955 & 0.430449 \tabularnewline
215 & 7 & 5.74972 & 1.25028 \tabularnewline
216 & 9.5 & 8.45433 & 1.04567 \tabularnewline
217 & 8.5 & 5.88241 & 2.61759 \tabularnewline
218 & 7.5 & 6.35067 & 1.14933 \tabularnewline
219 & 7.5 & 10.0411 & -2.54112 \tabularnewline
220 & 5 & 6.83724 & -1.83724 \tabularnewline
221 & 7 & 7.46988 & -0.469881 \tabularnewline
222 & 8 & 8.99277 & -0.992767 \tabularnewline
223 & 5.5 & 3.23609 & 2.26391 \tabularnewline
224 & 8.5 & 7.14678 & 1.35322 \tabularnewline
225 & 7.5 & 4.94855 & 2.55145 \tabularnewline
226 & 9.5 & 8.18063 & 1.31937 \tabularnewline
227 & 7 & 7.18007 & -0.18007 \tabularnewline
228 & 8 & 7.41427 & 0.585726 \tabularnewline
229 & 8.5 & 11.4907 & -2.99074 \tabularnewline
230 & 3.5 & 2.96938 & 0.530619 \tabularnewline
231 & 6.5 & 5.16542 & 1.33458 \tabularnewline
232 & 6.5 & 3.81474 & 2.68526 \tabularnewline
233 & 10.5 & 7.92963 & 2.57037 \tabularnewline
234 & 8.5 & 6.8395 & 1.6605 \tabularnewline
235 & 8 & 4.50757 & 3.49243 \tabularnewline
236 & 10 & 7.3902 & 2.6098 \tabularnewline
237 & 10 & 7.76761 & 2.23239 \tabularnewline
238 & 9.5 & 6.27137 & 3.22863 \tabularnewline
239 & 9 & 7.82433 & 1.17567 \tabularnewline
240 & 10 & 8.12417 & 1.87583 \tabularnewline
241 & 7.5 & 8.78738 & -1.28738 \tabularnewline
242 & 4.5 & 5.49457 & -0.994567 \tabularnewline
243 & 4.5 & 9.62761 & -5.12761 \tabularnewline
244 & 0.5 & -0.748492 & 1.24849 \tabularnewline
245 & 6.5 & 9.6025 & -3.1025 \tabularnewline
246 & 4.5 & 5.85107 & -1.35107 \tabularnewline
247 & 5.5 & 5.89491 & -0.394909 \tabularnewline
248 & 5 & 6.43811 & -1.43811 \tabularnewline
249 & 6 & 9.19345 & -3.19345 \tabularnewline
250 & 4 & 1.33771 & 2.66229 \tabularnewline
251 & 8 & 4.14776 & 3.85224 \tabularnewline
252 & 10.5 & 7.40259 & 3.09741 \tabularnewline
253 & 8.5 & 8.01786 & 0.482139 \tabularnewline
254 & 6.5 & 6.22562 & 0.274379 \tabularnewline
255 & 8 & 7.22074 & 0.779264 \tabularnewline
256 & 8.5 & 9.13886 & -0.638856 \tabularnewline
257 & 5.5 & 6.09731 & -0.597312 \tabularnewline
258 & 7 & 7.71357 & -0.713575 \tabularnewline
259 & 5 & 6.57311 & -1.57311 \tabularnewline
260 & 3.5 & 5.80095 & -2.30095 \tabularnewline
261 & 5 & 3.40845 & 1.59155 \tabularnewline
262 & 9 & 7.03839 & 1.96161 \tabularnewline
263 & 8.5 & 9.68665 & -1.18665 \tabularnewline
264 & 5 & 3.63171 & 1.36829 \tabularnewline
265 & 9.5 & 11.3011 & -1.80106 \tabularnewline
266 & 3 & 9.39785 & -6.39785 \tabularnewline
267 & 1.5 & 0.202522 & 1.29748 \tabularnewline
268 & 6 & 10.7105 & -4.71047 \tabularnewline
269 & 0.5 & -0.562773 & 1.06277 \tabularnewline
270 & 6.5 & 4.76374 & 1.73626 \tabularnewline
271 & 7.5 & 8.90752 & -1.40752 \tabularnewline
272 & 4.5 & 1.83771 & 2.66229 \tabularnewline
273 & 8 & 6.75979 & 1.24021 \tabularnewline
274 & 9 & 8.16863 & 0.831368 \tabularnewline
275 & 7.5 & 6.25409 & 1.24591 \tabularnewline
276 & 8.5 & 6.6692 & 1.8308 \tabularnewline
277 & 7 & 3.20098 & 3.79902 \tabularnewline
278 & 9.5 & 8.0299 & 1.4701 \tabularnewline
279 & 6.5 & 2.27841 & 4.22159 \tabularnewline
280 & 9.5 & 8.82152 & 0.67848 \tabularnewline
281 & 6 & 5.04148 & 0.958519 \tabularnewline
282 & 8 & 6.4144 & 1.5856 \tabularnewline
283 & 9.5 & 7.57248 & 1.92752 \tabularnewline
284 & 8 & 6.32413 & 1.67587 \tabularnewline
285 & 8 & 5.76095 & 2.23905 \tabularnewline
286 & 9 & 9.55839 & -0.558394 \tabularnewline
287 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268567&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]5.24054[/C][C]2.25946[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]4.9719[/C][C]-2.4719[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]4.9904[/C][C]1.0096[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]5.3318[/C][C]1.1682[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.54351[/C][C]-4.54351[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]5.03988[/C][C]-4.03988[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]6.55197[/C][C]-1.05197[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]5.55849[/C][C]2.94151[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]5.66085[/C][C]0.839146[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]5.31889[/C][C]-0.818886[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]6.47846[/C][C]-4.47846[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]5.6891[/C][C]-0.689097[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]6.74587[/C][C]-6.24587[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]5.2129[/C][C]-0.212901[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]5.83421[/C][C]-0.834214[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]4.70756[/C][C]-2.20756[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]5.33691[/C][C]-0.336908[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]6.1696[/C][C]-0.669597[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]5.52579[/C][C]-2.02579[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]5.47327[/C][C]-2.47327[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]5.24672[/C][C]-1.24672[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]5.05276[/C][C]-4.55276[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]5.50191[/C][C]0.998092[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]5.43486[/C][C]-0.934858[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]4.9629[/C][C]2.5371[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]5.58406[/C][C]-0.0840563[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]6.30537[/C][C]-2.30537[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]5.74507[/C][C]1.75493[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]5.20348[/C][C]1.79652[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]4.75113[/C][C]-0.751125[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]5.37078[/C][C]0.129225[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]5.67135[/C][C]-3.17135[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]6.04209[/C][C]-0.542086[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]5.17574[/C][C]-4.67574[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]5.61485[/C][C]-2.11485[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]6.38572[/C][C]-3.88572[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.91426[/C][C]-1.41426[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]6.11835[/C][C]-1.61835[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]5.11335[/C][C]-0.613347[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.79747[/C][C]0.202532[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]5.06552[/C][C]-2.56552[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.5806[/C][C]-1.5806[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]4.71864[/C][C]-4.71864[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.40297[/C][C]-1.40297[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]4.89752[/C][C]1.60248[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]5.54548[/C][C]-0.545481[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]5.06572[/C][C]0.93428[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]5.70464[/C][C]-1.20464[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]5.90188[/C][C]-0.401875[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]5.06093[/C][C]-4.06093[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]4.48301[/C][C]3.01699[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]5.07466[/C][C]0.925343[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.53421[/C][C]-0.534208[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]5.64289[/C][C]-4.64289[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]6.05607[/C][C]-1.05607[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]5.65851[/C][C]0.841487[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]6.34213[/C][C]0.657871[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]6.43779[/C][C]-1.93779[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]5.28081[/C][C]-5.28081[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]5.45678[/C][C]3.04322[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.65378[/C][C]-1.15378[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]5.56579[/C][C]1.93421[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]5.54005[/C][C]-2.04005[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]4.86285[/C][C]1.13715[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]4.96275[/C][C]-3.46275[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]5.8869[/C][C]3.1131[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]4.54562[/C][C]-1.04562[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]5.07361[/C][C]-1.57361[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]6.10828[/C][C]-2.10828[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]5.67692[/C][C]0.823078[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]5.34032[/C][C]2.15968[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]5.01764[/C][C]0.982356[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]5.72675[/C][C]-0.726749[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]5.0409[/C][C]0.459096[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]5.47448[/C][C]-1.97448[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]4.97363[/C][C]2.52637[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]5.27908[/C][C]-4.27908[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.94357[/C][C]0.556427[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]0.36687[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]5.11535[/C][C]1.38465[/C][/ROW]
[ROW][C]81[/C][C]6.5[/C][C]6.36072[/C][C]0.139278[/C][/ROW]
[ROW][C]82[/C][C]7[/C][C]8.89718[/C][C]-1.89718[/C][/ROW]
[ROW][C]83[/C][C]3.5[/C][C]7.22971[/C][C]-3.72971[/C][/ROW]
[ROW][C]84[/C][C]1.5[/C][C]2.31873[/C][C]-0.818728[/C][/ROW]
[ROW][C]85[/C][C]4[/C][C]1.19951[/C][C]2.80049[/C][/ROW]
[ROW][C]86[/C][C]7.5[/C][C]8.67996[/C][C]-1.17996[/C][/ROW]
[ROW][C]87[/C][C]4.5[/C][C]9.06877[/C][C]-4.56877[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]1.29112[/C][C]-1.29112[/C][/ROW]
[ROW][C]89[/C][C]3.5[/C][C]3.31338[/C][C]0.186616[/C][/ROW]
[ROW][C]90[/C][C]5.5[/C][C]5.40949[/C][C]0.0905103[/C][/ROW]
[ROW][C]91[/C][C]5[/C][C]5.59343[/C][C]-0.593428[/C][/ROW]
[ROW][C]92[/C][C]4.5[/C][C]6.56402[/C][C]-2.06402[/C][/ROW]
[ROW][C]93[/C][C]2.5[/C][C]-0.194605[/C][C]2.69461[/C][/ROW]
[ROW][C]94[/C][C]7.5[/C][C]5.42879[/C][C]2.07121[/C][/ROW]
[ROW][C]95[/C][C]7[/C][C]12.0581[/C][C]-5.05805[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.507041[/C][C]-0.507041[/C][/ROW]
[ROW][C]97[/C][C]4.5[/C][C]7.21798[/C][C]-2.71798[/C][/ROW]
[ROW][C]98[/C][C]3[/C][C]7.04158[/C][C]-4.04158[/C][/ROW]
[ROW][C]99[/C][C]1.5[/C][C]2.56689[/C][C]-1.06689[/C][/ROW]
[ROW][C]100[/C][C]3.5[/C][C]6.64575[/C][C]-3.14575[/C][/ROW]
[ROW][C]101[/C][C]2.5[/C][C]2.09625[/C][C]0.403755[/C][/ROW]
[ROW][C]102[/C][C]5.5[/C][C]2.92797[/C][C]2.57203[/C][/ROW]
[ROW][C]103[/C][C]8[/C][C]11.6588[/C][C]-3.65876[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]1.33325[/C][C]-0.333248[/C][/ROW]
[ROW][C]105[/C][C]5[/C][C]5.98218[/C][C]-0.982184[/C][/ROW]
[ROW][C]106[/C][C]4.5[/C][C]6.26283[/C][C]-1.76283[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]4.72066[/C][C]-1.72066[/C][/ROW]
[ROW][C]108[/C][C]3[/C][C]0.548979[/C][C]2.45102[/C][/ROW]
[ROW][C]109[/C][C]8[/C][C]10.1034[/C][C]-2.10343[/C][/ROW]
[ROW][C]110[/C][C]2.5[/C][C]0.335348[/C][C]2.16465[/C][/ROW]
[ROW][C]111[/C][C]7[/C][C]11.9863[/C][C]-4.98633[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]4.04919[/C][C]-4.04919[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]2.2212[/C][C]-1.2212[/C][/ROW]
[ROW][C]114[/C][C]3.5[/C][C]2.79459[/C][C]0.705405[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]4.68389[/C][C]0.816111[/C][/ROW]
[ROW][C]116[/C][C]5.5[/C][C]9.42003[/C][C]-3.92003[/C][/ROW]
[ROW][C]117[/C][C]0.5[/C][C]-0.485431[/C][C]0.985431[/C][/ROW]
[ROW][C]118[/C][C]7.5[/C][C]5.47851[/C][C]2.02149[/C][/ROW]
[ROW][C]119[/C][C]9[/C][C]6.65016[/C][C]2.34984[/C][/ROW]
[ROW][C]120[/C][C]9.5[/C][C]8.98325[/C][C]0.516746[/C][/ROW]
[ROW][C]121[/C][C]8.5[/C][C]5.79935[/C][C]2.70065[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]10.2169[/C][C]-3.2169[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]5.21042[/C][C]2.78958[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]11.9587[/C][C]-1.95866[/C][/ROW]
[ROW][C]125[/C][C]7[/C][C]3.6736[/C][C]3.3264[/C][/ROW]
[ROW][C]126[/C][C]8.5[/C][C]8.3228[/C][C]0.177203[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]5.15913[/C][C]3.84087[/C][/ROW]
[ROW][C]128[/C][C]9.5[/C][C]12.8946[/C][C]-3.39463[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]4.72763[/C][C]-0.727631[/C][/ROW]
[ROW][C]130[/C][C]6[/C][C]5.32138[/C][C]0.678622[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]10.8885[/C][C]-2.88851[/C][/ROW]
[ROW][C]132[/C][C]5.5[/C][C]3.97138[/C][C]1.52862[/C][/ROW]
[ROW][C]133[/C][C]9.5[/C][C]7.87369[/C][C]1.62631[/C][/ROW]
[ROW][C]134[/C][C]7.5[/C][C]5.98833[/C][C]1.51167[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]8.20723[/C][C]-1.20723[/C][/ROW]
[ROW][C]136[/C][C]7.5[/C][C]5.49407[/C][C]2.00593[/C][/ROW]
[ROW][C]137[/C][C]8[/C][C]7.88841[/C][C]0.111595[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]6.12674[/C][C]0.873263[/C][/ROW]
[ROW][C]139[/C][C]7[/C][C]8.5213[/C][C]-1.5213[/C][/ROW]
[ROW][C]140[/C][C]6[/C][C]2.66971[/C][C]3.33029[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.8969[/C][C]-3.89686[/C][/ROW]
[ROW][C]142[/C][C]2.5[/C][C]2.28653[/C][C]0.213474[/C][/ROW]
[ROW][C]143[/C][C]9[/C][C]10.2914[/C][C]-1.29139[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]6.98929[/C][C]1.01071[/C][/ROW]
[ROW][C]145[/C][C]6[/C][C]2.16003[/C][C]3.83997[/C][/ROW]
[ROW][C]146[/C][C]8.5[/C][C]8.61357[/C][C]-0.113568[/C][/ROW]
[ROW][C]147[/C][C]6[/C][C]5.14336[/C][C]0.856642[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]7.46436[/C][C]1.53564[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]6.66734[/C][C]1.33266[/C][/ROW]
[ROW][C]150[/C][C]8[/C][C]6.08918[/C][C]1.91082[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]9.55632[/C][C]-0.556325[/C][/ROW]
[ROW][C]152[/C][C]5.5[/C][C]6.01998[/C][C]-0.519977[/C][/ROW]
[ROW][C]153[/C][C]5[/C][C]4.49897[/C][C]0.501029[/C][/ROW]
[ROW][C]154[/C][C]7[/C][C]11.0366[/C][C]-4.03663[/C][/ROW]
[ROW][C]155[/C][C]5.5[/C][C]4.26765[/C][C]1.23235[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]14.1026[/C][C]-5.10255[/C][/ROW]
[ROW][C]157[/C][C]2[/C][C]0.255352[/C][C]1.74465[/C][/ROW]
[ROW][C]158[/C][C]8.5[/C][C]6.98057[/C][C]1.51943[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.95841[/C][C]0.0415863[/C][/ROW]
[ROW][C]160[/C][C]8.5[/C][C]5.83944[/C][C]2.66056[/C][/ROW]
[ROW][C]161[/C][C]9[/C][C]8.46231[/C][C]0.537691[/C][/ROW]
[ROW][C]162[/C][C]7.5[/C][C]5.20014[/C][C]2.29986[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]8.18056[/C][C]1.81944[/C][/ROW]
[ROW][C]164[/C][C]9[/C][C]10.3831[/C][C]-1.38306[/C][/ROW]
[ROW][C]165[/C][C]7.5[/C][C]8.00052[/C][C]-0.500521[/C][/ROW]
[ROW][C]166[/C][C]6[/C][C]1.49779[/C][C]4.50221[/C][/ROW]
[ROW][C]167[/C][C]10.5[/C][C]11.3161[/C][C]-0.816057[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]7.26593[/C][C]1.23407[/C][/ROW]
[ROW][C]169[/C][C]8[/C][C]3.916[/C][C]4.084[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]6.14776[/C][C]3.85224[/C][/ROW]
[ROW][C]171[/C][C]10.5[/C][C]9.43723[/C][C]1.06277[/C][/ROW]
[ROW][C]172[/C][C]6.5[/C][C]4.82592[/C][C]1.67408[/C][/ROW]
[ROW][C]173[/C][C]9.5[/C][C]5.76609[/C][C]3.73391[/C][/ROW]
[ROW][C]174[/C][C]8.5[/C][C]8.83101[/C][C]-0.331011[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]9.63973[/C][C]-2.13973[/C][/ROW]
[ROW][C]176[/C][C]5[/C][C]4.57773[/C][C]0.422269[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]4.28423[/C][C]3.71577[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.74106[/C][C]1.25894[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]6.7828[/C][C]0.217204[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]7.2828[/C][C]0.217204[/C][/ROW]
[ROW][C]181[/C][C]7.5[/C][C]4.53246[/C][C]2.96754[/C][/ROW]
[ROW][C]182[/C][C]9.5[/C][C]10.1192[/C][C]-0.61916[/C][/ROW]
[ROW][C]183[/C][C]6[/C][C]4.12467[/C][C]1.87533[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]8.87409[/C][C]1.12591[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]10.2471[/C][C]-3.24706[/C][/ROW]
[ROW][C]186[/C][C]3[/C][C]3.8555[/C][C]-0.855504[/C][/ROW]
[ROW][C]187[/C][C]6[/C][C]5.87989[/C][C]0.120107[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]5.43419[/C][C]1.56581[/C][/ROW]
[ROW][C]189[/C][C]10[/C][C]9.78968[/C][C]0.210322[/C][/ROW]
[ROW][C]190[/C][C]7[/C][C]8.8176[/C][C]-1.8176[/C][/ROW]
[ROW][C]191[/C][C]3.5[/C][C]2.18227[/C][C]1.31773[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]3.75375[/C][C]4.24625[/C][/ROW]
[ROW][C]193[/C][C]10[/C][C]10.1981[/C][C]-0.198131[/C][/ROW]
[ROW][C]194[/C][C]5.5[/C][C]3.55541[/C][C]1.94459[/C][/ROW]
[ROW][C]195[/C][C]6[/C][C]5.92247[/C][C]0.0775331[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]5.70428[/C][C]0.795724[/C][/ROW]
[ROW][C]197[/C][C]6.5[/C][C]4.48842[/C][C]2.01158[/C][/ROW]
[ROW][C]198[/C][C]8.5[/C][C]9.81939[/C][C]-1.31939[/C][/ROW]
[ROW][C]199[/C][C]4[/C][C]0.81724[/C][C]3.18276[/C][/ROW]
[ROW][C]200[/C][C]9.5[/C][C]7.45187[/C][C]2.04813[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]7.02712[/C][C]0.97288[/C][/ROW]
[ROW][C]202[/C][C]8.5[/C][C]11.3696[/C][C]-2.86957[/C][/ROW]
[ROW][C]203[/C][C]5.5[/C][C]5.90638[/C][C]-0.406382[/C][/ROW]
[ROW][C]204[/C][C]7[/C][C]3.7911[/C][C]3.2089[/C][/ROW]
[ROW][C]205[/C][C]9[/C][C]6.9907[/C][C]2.0093[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]5.95626[/C][C]2.04374[/C][/ROW]
[ROW][C]207[/C][C]10[/C][C]7.98448[/C][C]2.01552[/C][/ROW]
[ROW][C]208[/C][C]8[/C][C]8.12922[/C][C]-0.129218[/C][/ROW]
[ROW][C]209[/C][C]6[/C][C]5.57462[/C][C]0.425382[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]9.04075[/C][C]-1.04075[/C][/ROW]
[ROW][C]211[/C][C]5[/C][C]1.35235[/C][C]3.64765[/C][/ROW]
[ROW][C]212[/C][C]9[/C][C]11.4979[/C][C]-2.49794[/C][/ROW]
[ROW][C]213[/C][C]4.5[/C][C]1.54295[/C][C]2.95705[/C][/ROW]
[ROW][C]214[/C][C]8.5[/C][C]8.06955[/C][C]0.430449[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]5.74972[/C][C]1.25028[/C][/ROW]
[ROW][C]216[/C][C]9.5[/C][C]8.45433[/C][C]1.04567[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]5.88241[/C][C]2.61759[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]6.35067[/C][C]1.14933[/C][/ROW]
[ROW][C]219[/C][C]7.5[/C][C]10.0411[/C][C]-2.54112[/C][/ROW]
[ROW][C]220[/C][C]5[/C][C]6.83724[/C][C]-1.83724[/C][/ROW]
[ROW][C]221[/C][C]7[/C][C]7.46988[/C][C]-0.469881[/C][/ROW]
[ROW][C]222[/C][C]8[/C][C]8.99277[/C][C]-0.992767[/C][/ROW]
[ROW][C]223[/C][C]5.5[/C][C]3.23609[/C][C]2.26391[/C][/ROW]
[ROW][C]224[/C][C]8.5[/C][C]7.14678[/C][C]1.35322[/C][/ROW]
[ROW][C]225[/C][C]7.5[/C][C]4.94855[/C][C]2.55145[/C][/ROW]
[ROW][C]226[/C][C]9.5[/C][C]8.18063[/C][C]1.31937[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]7.18007[/C][C]-0.18007[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]7.41427[/C][C]0.585726[/C][/ROW]
[ROW][C]229[/C][C]8.5[/C][C]11.4907[/C][C]-2.99074[/C][/ROW]
[ROW][C]230[/C][C]3.5[/C][C]2.96938[/C][C]0.530619[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]5.16542[/C][C]1.33458[/C][/ROW]
[ROW][C]232[/C][C]6.5[/C][C]3.81474[/C][C]2.68526[/C][/ROW]
[ROW][C]233[/C][C]10.5[/C][C]7.92963[/C][C]2.57037[/C][/ROW]
[ROW][C]234[/C][C]8.5[/C][C]6.8395[/C][C]1.6605[/C][/ROW]
[ROW][C]235[/C][C]8[/C][C]4.50757[/C][C]3.49243[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]7.3902[/C][C]2.6098[/C][/ROW]
[ROW][C]237[/C][C]10[/C][C]7.76761[/C][C]2.23239[/C][/ROW]
[ROW][C]238[/C][C]9.5[/C][C]6.27137[/C][C]3.22863[/C][/ROW]
[ROW][C]239[/C][C]9[/C][C]7.82433[/C][C]1.17567[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]8.12417[/C][C]1.87583[/C][/ROW]
[ROW][C]241[/C][C]7.5[/C][C]8.78738[/C][C]-1.28738[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]5.49457[/C][C]-0.994567[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]9.62761[/C][C]-5.12761[/C][/ROW]
[ROW][C]244[/C][C]0.5[/C][C]-0.748492[/C][C]1.24849[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]9.6025[/C][C]-3.1025[/C][/ROW]
[ROW][C]246[/C][C]4.5[/C][C]5.85107[/C][C]-1.35107[/C][/ROW]
[ROW][C]247[/C][C]5.5[/C][C]5.89491[/C][C]-0.394909[/C][/ROW]
[ROW][C]248[/C][C]5[/C][C]6.43811[/C][C]-1.43811[/C][/ROW]
[ROW][C]249[/C][C]6[/C][C]9.19345[/C][C]-3.19345[/C][/ROW]
[ROW][C]250[/C][C]4[/C][C]1.33771[/C][C]2.66229[/C][/ROW]
[ROW][C]251[/C][C]8[/C][C]4.14776[/C][C]3.85224[/C][/ROW]
[ROW][C]252[/C][C]10.5[/C][C]7.40259[/C][C]3.09741[/C][/ROW]
[ROW][C]253[/C][C]8.5[/C][C]8.01786[/C][C]0.482139[/C][/ROW]
[ROW][C]254[/C][C]6.5[/C][C]6.22562[/C][C]0.274379[/C][/ROW]
[ROW][C]255[/C][C]8[/C][C]7.22074[/C][C]0.779264[/C][/ROW]
[ROW][C]256[/C][C]8.5[/C][C]9.13886[/C][C]-0.638856[/C][/ROW]
[ROW][C]257[/C][C]5.5[/C][C]6.09731[/C][C]-0.597312[/C][/ROW]
[ROW][C]258[/C][C]7[/C][C]7.71357[/C][C]-0.713575[/C][/ROW]
[ROW][C]259[/C][C]5[/C][C]6.57311[/C][C]-1.57311[/C][/ROW]
[ROW][C]260[/C][C]3.5[/C][C]5.80095[/C][C]-2.30095[/C][/ROW]
[ROW][C]261[/C][C]5[/C][C]3.40845[/C][C]1.59155[/C][/ROW]
[ROW][C]262[/C][C]9[/C][C]7.03839[/C][C]1.96161[/C][/ROW]
[ROW][C]263[/C][C]8.5[/C][C]9.68665[/C][C]-1.18665[/C][/ROW]
[ROW][C]264[/C][C]5[/C][C]3.63171[/C][C]1.36829[/C][/ROW]
[ROW][C]265[/C][C]9.5[/C][C]11.3011[/C][C]-1.80106[/C][/ROW]
[ROW][C]266[/C][C]3[/C][C]9.39785[/C][C]-6.39785[/C][/ROW]
[ROW][C]267[/C][C]1.5[/C][C]0.202522[/C][C]1.29748[/C][/ROW]
[ROW][C]268[/C][C]6[/C][C]10.7105[/C][C]-4.71047[/C][/ROW]
[ROW][C]269[/C][C]0.5[/C][C]-0.562773[/C][C]1.06277[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]4.76374[/C][C]1.73626[/C][/ROW]
[ROW][C]271[/C][C]7.5[/C][C]8.90752[/C][C]-1.40752[/C][/ROW]
[ROW][C]272[/C][C]4.5[/C][C]1.83771[/C][C]2.66229[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]6.75979[/C][C]1.24021[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]8.16863[/C][C]0.831368[/C][/ROW]
[ROW][C]275[/C][C]7.5[/C][C]6.25409[/C][C]1.24591[/C][/ROW]
[ROW][C]276[/C][C]8.5[/C][C]6.6692[/C][C]1.8308[/C][/ROW]
[ROW][C]277[/C][C]7[/C][C]3.20098[/C][C]3.79902[/C][/ROW]
[ROW][C]278[/C][C]9.5[/C][C]8.0299[/C][C]1.4701[/C][/ROW]
[ROW][C]279[/C][C]6.5[/C][C]2.27841[/C][C]4.22159[/C][/ROW]
[ROW][C]280[/C][C]9.5[/C][C]8.82152[/C][C]0.67848[/C][/ROW]
[ROW][C]281[/C][C]6[/C][C]5.04148[/C][C]0.958519[/C][/ROW]
[ROW][C]282[/C][C]8[/C][C]6.4144[/C][C]1.5856[/C][/ROW]
[ROW][C]283[/C][C]9.5[/C][C]7.57248[/C][C]1.92752[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.32413[/C][C]1.67587[/C][/ROW]
[ROW][C]285[/C][C]8[/C][C]5.76095[/C][C]2.23905[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]9.55839[/C][C]-0.558394[/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=268567&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268567&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
17.55.240542.25946
22.54.9719-2.4719
364.99041.0096
46.55.33181.1682
515.54351-4.54351
615.03988-4.03988
75.56.55197-1.05197
88.55.558492.94151
96.55.660850.839146
104.55.31889-0.818886
1126.47846-4.47846
1255.6891-0.689097
130.56.74587-6.24587
1455.2129-0.212901
1555.83421-0.834214
162.54.70756-2.20756
1755.33691-0.336908
185.56.1696-0.669597
193.55.52579-2.02579
2035.47327-2.47327
2145.24672-1.24672
220.55.05276-4.55276
236.55.501910.998092
244.55.43486-0.934858
257.54.96292.5371
265.55.58406-0.0840563
2746.30537-2.30537
287.55.745071.75493
2975.203481.79652
3044.75113-0.751125
315.55.370780.129225
322.55.67135-3.17135
335.56.04209-0.542086
340.55.17574-4.67574
353.55.61485-2.11485
362.56.38572-3.88572
374.55.91426-1.41426
384.56.11835-1.61835
394.55.11335-0.613347
4065.797470.202532
412.55.06552-2.56552
4256.5806-1.5806
4304.71864-4.71864
4456.40297-1.40297
456.54.897521.60248
4655.54548-0.545481
4765.065720.93428
484.55.70464-1.20464
495.55.90188-0.401875
5015.06093-4.06093
517.54.483013.01699
5265.074660.925343
5355.53421-0.534208
5415.64289-4.64289
5556.05607-1.05607
566.55.658510.841487
5776.342130.657871
584.56.43779-1.93779
5905.28081-5.28081
608.55.456783.04322
613.54.65378-1.15378
627.55.565791.93421
633.55.54005-2.04005
6464.862851.13715
651.54.96275-3.46275
6695.88693.1131
673.54.54562-1.04562
683.55.07361-1.57361
6946.10828-2.10828
706.55.676920.823078
717.55.340322.15968
7265.017640.982356
7355.72675-0.726749
745.55.04090.459096
753.55.47448-1.97448
767.54.973632.52637
7715.27908-4.27908
786.55.943570.556427
79NANA0.36687
806.55.115351.38465
816.56.360720.139278
8278.89718-1.89718
833.57.22971-3.72971
841.52.31873-0.818728
8541.199512.80049
867.58.67996-1.17996
874.59.06877-4.56877
8801.29112-1.29112
893.53.313380.186616
905.55.409490.0905103
9155.59343-0.593428
924.56.56402-2.06402
932.5-0.1946052.69461
947.55.428792.07121
95712.0581-5.05805
9600.507041-0.507041
974.57.21798-2.71798
9837.04158-4.04158
991.52.56689-1.06689
1003.56.64575-3.14575
1012.52.096250.403755
1025.52.927972.57203
103811.6588-3.65876
10411.33325-0.333248
10555.98218-0.982184
1064.56.26283-1.76283
10734.72066-1.72066
10830.5489792.45102
109810.1034-2.10343
1102.50.3353482.16465
111711.9863-4.98633
11204.04919-4.04919
11312.2212-1.2212
1143.52.794590.705405
1155.54.683890.816111
1165.59.42003-3.92003
1170.5-0.4854310.985431
1187.55.478512.02149
11996.650162.34984
1209.58.983250.516746
1218.55.799352.70065
122710.2169-3.2169
12385.210422.78958
1241011.9587-1.95866
12573.67363.3264
1268.58.32280.177203
12795.159133.84087
1289.512.8946-3.39463
12944.72763-0.727631
13065.321380.678622
131810.8885-2.88851
1325.53.971381.52862
1339.57.873691.62631
1347.55.988331.51167
13578.20723-1.20723
1367.55.494072.00593
13787.888410.111595
13876.126740.873263
13978.5213-1.5213
14062.669713.33029
1411013.8969-3.89686
1422.52.286530.213474
143910.2914-1.29139
14486.989291.01071
14562.160033.83997
1468.58.61357-0.113568
14765.143360.856642
14897.464361.53564
14986.667341.33266
15086.089181.91082
15199.55632-0.556325
1525.56.01998-0.519977
15354.498970.501029
154711.0366-4.03663
1555.54.267651.23235
156914.1026-5.10255
15720.2553521.74465
1588.56.980571.51943
15998.958410.0415863
1608.55.839442.66056
16198.462310.537691
1627.55.200142.29986
163108.180561.81944
164910.3831-1.38306
1657.58.00052-0.500521
16661.497794.50221
16710.511.3161-0.816057
1688.57.265931.23407
16983.9164.084
170106.147763.85224
17110.59.437231.06277
1726.54.825921.67408
1739.55.766093.73391
1748.58.83101-0.331011
1757.59.63973-2.13973
17654.577730.422269
17784.284233.71577
178108.741061.25894
17976.78280.217204
1807.57.28280.217204
1817.54.532462.96754
1829.510.1192-0.61916
18364.124671.87533
184108.874091.12591
185710.2471-3.24706
18633.8555-0.855504
18765.879890.120107
18875.434191.56581
189109.789680.210322
19078.8176-1.8176
1913.52.182271.31773
19283.753754.24625
1931010.1981-0.198131
1945.53.555411.94459
19565.922470.0775331
1966.55.704280.795724
1976.54.488422.01158
1988.59.81939-1.31939
19940.817243.18276
2009.57.451872.04813
20187.027120.97288
2028.511.3696-2.86957
2035.55.90638-0.406382
20473.79113.2089
20596.99072.0093
20685.956262.04374
207107.984482.01552
20888.12922-0.129218
20965.574620.425382
21089.04075-1.04075
21151.352353.64765
212911.4979-2.49794
2134.51.542952.95705
2148.58.069550.430449
21575.749721.25028
2169.58.454331.04567
2178.55.882412.61759
2187.56.350671.14933
2197.510.0411-2.54112
22056.83724-1.83724
22177.46988-0.469881
22288.99277-0.992767
2235.53.236092.26391
2248.57.146781.35322
2257.54.948552.55145
2269.58.180631.31937
22777.18007-0.18007
22887.414270.585726
2298.511.4907-2.99074
2303.52.969380.530619
2316.55.165421.33458
2326.53.814742.68526
23310.57.929632.57037
2348.56.83951.6605
23584.507573.49243
236107.39022.6098
237107.767612.23239
2389.56.271373.22863
23997.824331.17567
240108.124171.87583
2417.58.78738-1.28738
2424.55.49457-0.994567
2434.59.62761-5.12761
2440.5-0.7484921.24849
2456.59.6025-3.1025
2464.55.85107-1.35107
2475.55.89491-0.394909
24856.43811-1.43811
24969.19345-3.19345
25041.337712.66229
25184.147763.85224
25210.57.402593.09741
2538.58.017860.482139
2546.56.225620.274379
25587.220740.779264
2568.59.13886-0.638856
2575.56.09731-0.597312
25877.71357-0.713575
25956.57311-1.57311
2603.55.80095-2.30095
26153.408451.59155
26297.038391.96161
2638.59.68665-1.18665
26453.631711.36829
2659.511.3011-1.80106
26639.39785-6.39785
2671.50.2025221.29748
268610.7105-4.71047
2690.5-0.5627731.06277
2706.54.763741.73626
2717.58.90752-1.40752
2724.51.837712.66229
27386.759791.24021
27498.168630.831368
2757.56.254091.24591
2768.56.66921.8308
27773.200983.79902
2789.58.02991.4701
2796.52.278414.22159
2809.58.821520.67848
28165.041480.958519
28286.41441.5856
2839.57.572481.92752
28486.324131.67587
28585.760952.23905
28699.55839-0.558394
2875NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9780830.04383440.0219172
100.9638650.07226960.0361348
110.9681120.06377690.0318884
120.9434920.1130150.0565077
130.9562060.08758790.0437939
140.9345340.1309310.0654655
150.9008240.1983510.0991756
160.8618450.2763090.138155
170.8367950.3264110.163205
180.7948120.4103750.205188
190.7364920.5270170.263508
200.6905190.6189620.309481
210.6219880.7560250.378012
220.6889830.6220340.311017
230.6582320.6835360.341768
240.5950550.8098910.404945
250.5516530.8966950.448347
260.4928890.9857780.507111
270.438170.876340.56183
280.3774020.7548040.622598
290.4217440.8434870.578256
300.3837240.7674470.616276
310.3579830.7159650.642017
320.326250.65250.67375
330.3253620.6507240.674638
340.4376350.875270.562365
350.388450.77690.61155
360.4226990.8453970.577301
370.3781020.7562050.621898
380.3370880.6741760.662912
390.2942330.5884670.705767
400.2932740.5865470.706726
410.3419120.6838240.658088
420.3109750.6219490.689025
430.4400260.8800510.559974
440.4006440.8012880.599356
450.3802010.7604030.619799
460.3466730.6933450.653327
470.3363610.6727210.663639
480.2980860.5961730.701914
490.266860.533720.73314
500.3622110.7244220.637789
510.4077710.8155430.592229
520.4024960.8049920.597504
530.3649950.7299890.635005
540.4029270.8058540.597073
550.3805670.7611350.619433
560.3910490.7820980.608951
570.4018590.8037190.598141
580.3692780.7385550.630722
590.4947420.9894830.505258
600.5851280.8297430.414872
610.5458750.9082490.454125
620.5741550.851690.425845
630.562680.8746410.43732
640.543280.913440.45672
650.5781590.8436820.421841
660.6442750.7114510.355725
670.6202680.7594630.379732
680.5877520.8244960.412248
690.5766990.8466030.423301
700.5423040.9153910.457696
710.5501220.8997570.449878
720.5288110.9423790.471189
730.496280.9925610.50372
740.4661170.9322340.533883
750.4385690.8771370.561431
760.441720.8834410.55828
770.5605640.8788710.439436
780.5444340.9111330.455566
790.5211990.9576020.478801
800.5120380.9759240.487962
810.5007590.9984820.499241
820.4752790.9505590.524721
830.5351840.9296320.464816
840.5033160.9933670.496684
850.5356480.9287040.464352
860.5045470.9909060.495453
870.6127260.7745480.387274
880.5964490.8071010.403551
890.5652570.8694860.434743
900.532530.9349390.46747
910.499150.9983010.50085
920.4966050.9932110.503395
930.5222070.9555850.477793
940.5384960.9230080.461504
950.6669250.666150.333075
960.6449710.7100570.355029
970.640030.7199410.35997
980.6853080.6293850.314692
990.6685830.6628340.331417
1000.6925020.6149960.307498
1010.6750850.649830.324915
1020.7268880.5462250.273112
1030.8028680.3942640.197132
1040.7831450.433710.216855
1050.7657760.4684480.234224
1060.7626930.4746130.237307
1070.7759150.448170.224085
1080.7985330.4029340.201467
1090.8161390.3677230.183861
1100.8199010.3601990.180099
1110.9122680.1754650.0877324
1120.940180.119640.0598202
1130.9433080.1133830.0566916
1140.9383590.1232830.0616415
1150.9330170.1339650.0669827
1160.9499240.1001530.0500763
1170.950940.09811980.0490599
1180.9580820.08383630.0419182
1190.9651830.06963320.0348166
1200.9590850.08183060.0409153
1210.9701320.0597370.0298685
1220.9661850.06763010.0338151
1230.9701520.05969610.029848
1240.973330.05334090.0266705
1250.9825330.03493420.0174671
1260.9799940.04001210.020006
1270.9900020.0199950.00999752
1280.9913590.01728250.00864125
1290.9893920.02121690.0106085
1300.9877180.02456470.0122824
1310.987140.02571960.0128598
1320.9852510.02949890.0147494
1330.9843350.031330.015665
1340.9827250.03454930.0172747
1350.9804980.03900390.019502
1360.9815790.03684110.0184206
1370.9779140.04417170.0220859
1380.9746060.05078860.0253943
1390.9704020.05919550.0295977
1400.9790890.04182280.0209114
1410.9843620.03127560.0156378
1420.9811040.03779160.0188958
1430.9772070.04558590.0227929
1440.9738120.05237590.0261879
1450.9783640.04327270.0216364
1460.9772060.04558820.0227941
1470.9746710.05065720.0253286
1480.9723890.05522250.0276112
1490.9672750.06544970.0327249
1500.9646340.07073160.0353658
1510.9601940.07961170.0398058
1520.9549370.09012550.0450627
1530.9474140.1051730.0525864
1540.9512330.09753310.0487666
1550.9461950.107610.0538052
1560.9806620.0386760.019338
1570.9785650.04287080.0214354
1580.9764590.04708210.023541
1590.9713960.05720740.0286037
1600.9765090.04698110.0234905
1610.9718720.05625690.0281285
1620.9699310.06013860.0300693
1630.9688480.0623040.031152
1640.9640390.07192210.035961
1650.958880.08224070.0411204
1660.969920.06015920.0300796
1670.9645830.07083440.0354172
1680.9613770.07724620.0386231
1690.9831780.03364390.016822
1700.9849450.03010980.0150549
1710.9827190.03456260.0172813
1720.9806010.03879740.0193987
1730.985550.02889980.0144499
1740.9819610.03607880.0180394
1750.9822830.03543370.0177168
1760.9783650.04327080.0216354
1770.9824580.03508470.0175424
1780.9794680.04106440.0205322
1790.9747350.05052930.0252647
1800.969170.06165910.0308295
1810.9704060.0591880.029594
1820.9669050.06619030.0330952
1830.9665580.06688410.0334421
1840.9611050.07779040.0388952
1850.9655040.06899280.0344964
1860.9657520.06849570.0342478
1870.959310.08138080.0406904
1880.9551360.08972730.0448637
1890.9463690.1072620.0536309
1900.9572080.08558440.0427922
1910.9494230.1011550.0505775
1920.9680220.06395690.0319785
1930.9640990.07180140.0359007
1940.958810.08237910.0411896
1950.9498220.1003550.0501777
1960.9404030.1191940.0595969
1970.9326070.1347860.0673929
1980.929130.141740.0708698
1990.9353570.1292860.0646431
2000.9309190.1381630.0690813
2010.9261120.1477770.0738885
2020.9336830.1326340.0663171
2030.9211750.1576490.0788245
2040.9283330.1433350.0716674
2050.9184920.1630160.0815079
2060.9088320.1823360.091168
2070.9067620.1864750.0932377
2080.8952140.2095720.104786
2090.8791710.2416580.120829
2100.8724510.2550980.127549
2110.9026440.1947120.097356
2120.8955010.2089980.104499
2130.9111290.1777420.0888712
2140.8943530.2112940.105647
2150.8764750.247050.123525
2160.8554140.2891710.144586
2170.8492390.3015230.150761
2180.8269040.3461920.173096
2190.8438560.3122880.156144
2200.8218830.3562350.178117
2210.8009250.398150.199075
2220.7784290.4431410.221571
2230.7643650.4712710.235635
2240.7345670.5308660.265433
2250.7235140.5529730.276486
2260.693810.6123810.30619
2270.655560.6888790.34444
2280.624670.750660.37533
2290.6259830.7480350.374017
2300.5835680.8328640.416432
2310.5444020.9111960.455598
2320.5458350.9083310.454165
2330.5814810.8370380.418519
2340.5695020.8609970.430498
2350.6217070.7565860.378293
2360.5893520.8212960.410648
2370.5873290.8253410.412671
2380.6149610.7700780.385039
2390.5702870.8594260.429713
2400.5503670.8992660.449633
2410.5306770.9386460.469323
2420.4935460.9870920.506454
2430.6547350.6905310.345265
2440.6254260.7491480.374574
2450.6556360.6887270.344364
2460.6206640.7586710.379336
2470.5790530.8418940.420947
2480.5498730.9002540.450127
2490.5788620.8422760.421138
2500.5584550.883090.441545
2510.5458920.9082170.454108
2520.5665470.8669070.433453
2530.5139970.9720060.486003
2540.4560670.9121340.543933
2550.4005570.8011130.599443
2560.3472540.6945090.652746
2570.3150510.6301030.684949
2580.2679820.5359650.732018
2590.2552540.5105070.744746
2600.2851040.5702080.714896
2610.2388180.4776360.761182
2620.1947040.3894070.805296
2630.228970.457940.77103
2640.1993730.3987460.800627
2650.2159160.4318330.784084
2660.7820480.4359050.217952
2670.7491060.5017890.250894
2680.9995870.0008266110.000413305
2690.9999862.79838e-051.39919e-05
2700.9999627.53932e-053.76966e-05
2710.9999549.28057e-054.64029e-05
2720.9999410.0001184975.92483e-05
2730.9997350.0005296270.000264813
2740.9988540.002291730.00114586
2750.9968450.006310810.00315541
2760.9873490.02530280.0126514
2770.9552550.08948960.0447448
2780.8753290.2493420.124671

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.978083 & 0.0438344 & 0.0219172 \tabularnewline
10 & 0.963865 & 0.0722696 & 0.0361348 \tabularnewline
11 & 0.968112 & 0.0637769 & 0.0318884 \tabularnewline
12 & 0.943492 & 0.113015 & 0.0565077 \tabularnewline
13 & 0.956206 & 0.0875879 & 0.0437939 \tabularnewline
14 & 0.934534 & 0.130931 & 0.0654655 \tabularnewline
15 & 0.900824 & 0.198351 & 0.0991756 \tabularnewline
16 & 0.861845 & 0.276309 & 0.138155 \tabularnewline
17 & 0.836795 & 0.326411 & 0.163205 \tabularnewline
18 & 0.794812 & 0.410375 & 0.205188 \tabularnewline
19 & 0.736492 & 0.527017 & 0.263508 \tabularnewline
20 & 0.690519 & 0.618962 & 0.309481 \tabularnewline
21 & 0.621988 & 0.756025 & 0.378012 \tabularnewline
22 & 0.688983 & 0.622034 & 0.311017 \tabularnewline
23 & 0.658232 & 0.683536 & 0.341768 \tabularnewline
24 & 0.595055 & 0.809891 & 0.404945 \tabularnewline
25 & 0.551653 & 0.896695 & 0.448347 \tabularnewline
26 & 0.492889 & 0.985778 & 0.507111 \tabularnewline
27 & 0.43817 & 0.87634 & 0.56183 \tabularnewline
28 & 0.377402 & 0.754804 & 0.622598 \tabularnewline
29 & 0.421744 & 0.843487 & 0.578256 \tabularnewline
30 & 0.383724 & 0.767447 & 0.616276 \tabularnewline
31 & 0.357983 & 0.715965 & 0.642017 \tabularnewline
32 & 0.32625 & 0.6525 & 0.67375 \tabularnewline
33 & 0.325362 & 0.650724 & 0.674638 \tabularnewline
34 & 0.437635 & 0.87527 & 0.562365 \tabularnewline
35 & 0.38845 & 0.7769 & 0.61155 \tabularnewline
36 & 0.422699 & 0.845397 & 0.577301 \tabularnewline
37 & 0.378102 & 0.756205 & 0.621898 \tabularnewline
38 & 0.337088 & 0.674176 & 0.662912 \tabularnewline
39 & 0.294233 & 0.588467 & 0.705767 \tabularnewline
40 & 0.293274 & 0.586547 & 0.706726 \tabularnewline
41 & 0.341912 & 0.683824 & 0.658088 \tabularnewline
42 & 0.310975 & 0.621949 & 0.689025 \tabularnewline
43 & 0.440026 & 0.880051 & 0.559974 \tabularnewline
44 & 0.400644 & 0.801288 & 0.599356 \tabularnewline
45 & 0.380201 & 0.760403 & 0.619799 \tabularnewline
46 & 0.346673 & 0.693345 & 0.653327 \tabularnewline
47 & 0.336361 & 0.672721 & 0.663639 \tabularnewline
48 & 0.298086 & 0.596173 & 0.701914 \tabularnewline
49 & 0.26686 & 0.53372 & 0.73314 \tabularnewline
50 & 0.362211 & 0.724422 & 0.637789 \tabularnewline
51 & 0.407771 & 0.815543 & 0.592229 \tabularnewline
52 & 0.402496 & 0.804992 & 0.597504 \tabularnewline
53 & 0.364995 & 0.729989 & 0.635005 \tabularnewline
54 & 0.402927 & 0.805854 & 0.597073 \tabularnewline
55 & 0.380567 & 0.761135 & 0.619433 \tabularnewline
56 & 0.391049 & 0.782098 & 0.608951 \tabularnewline
57 & 0.401859 & 0.803719 & 0.598141 \tabularnewline
58 & 0.369278 & 0.738555 & 0.630722 \tabularnewline
59 & 0.494742 & 0.989483 & 0.505258 \tabularnewline
60 & 0.585128 & 0.829743 & 0.414872 \tabularnewline
61 & 0.545875 & 0.908249 & 0.454125 \tabularnewline
62 & 0.574155 & 0.85169 & 0.425845 \tabularnewline
63 & 0.56268 & 0.874641 & 0.43732 \tabularnewline
64 & 0.54328 & 0.91344 & 0.45672 \tabularnewline
65 & 0.578159 & 0.843682 & 0.421841 \tabularnewline
66 & 0.644275 & 0.711451 & 0.355725 \tabularnewline
67 & 0.620268 & 0.759463 & 0.379732 \tabularnewline
68 & 0.587752 & 0.824496 & 0.412248 \tabularnewline
69 & 0.576699 & 0.846603 & 0.423301 \tabularnewline
70 & 0.542304 & 0.915391 & 0.457696 \tabularnewline
71 & 0.550122 & 0.899757 & 0.449878 \tabularnewline
72 & 0.528811 & 0.942379 & 0.471189 \tabularnewline
73 & 0.49628 & 0.992561 & 0.50372 \tabularnewline
74 & 0.466117 & 0.932234 & 0.533883 \tabularnewline
75 & 0.438569 & 0.877137 & 0.561431 \tabularnewline
76 & 0.44172 & 0.883441 & 0.55828 \tabularnewline
77 & 0.560564 & 0.878871 & 0.439436 \tabularnewline
78 & 0.544434 & 0.911133 & 0.455566 \tabularnewline
79 & 0.521199 & 0.957602 & 0.478801 \tabularnewline
80 & 0.512038 & 0.975924 & 0.487962 \tabularnewline
81 & 0.500759 & 0.998482 & 0.499241 \tabularnewline
82 & 0.475279 & 0.950559 & 0.524721 \tabularnewline
83 & 0.535184 & 0.929632 & 0.464816 \tabularnewline
84 & 0.503316 & 0.993367 & 0.496684 \tabularnewline
85 & 0.535648 & 0.928704 & 0.464352 \tabularnewline
86 & 0.504547 & 0.990906 & 0.495453 \tabularnewline
87 & 0.612726 & 0.774548 & 0.387274 \tabularnewline
88 & 0.596449 & 0.807101 & 0.403551 \tabularnewline
89 & 0.565257 & 0.869486 & 0.434743 \tabularnewline
90 & 0.53253 & 0.934939 & 0.46747 \tabularnewline
91 & 0.49915 & 0.998301 & 0.50085 \tabularnewline
92 & 0.496605 & 0.993211 & 0.503395 \tabularnewline
93 & 0.522207 & 0.955585 & 0.477793 \tabularnewline
94 & 0.538496 & 0.923008 & 0.461504 \tabularnewline
95 & 0.666925 & 0.66615 & 0.333075 \tabularnewline
96 & 0.644971 & 0.710057 & 0.355029 \tabularnewline
97 & 0.64003 & 0.719941 & 0.35997 \tabularnewline
98 & 0.685308 & 0.629385 & 0.314692 \tabularnewline
99 & 0.668583 & 0.662834 & 0.331417 \tabularnewline
100 & 0.692502 & 0.614996 & 0.307498 \tabularnewline
101 & 0.675085 & 0.64983 & 0.324915 \tabularnewline
102 & 0.726888 & 0.546225 & 0.273112 \tabularnewline
103 & 0.802868 & 0.394264 & 0.197132 \tabularnewline
104 & 0.783145 & 0.43371 & 0.216855 \tabularnewline
105 & 0.765776 & 0.468448 & 0.234224 \tabularnewline
106 & 0.762693 & 0.474613 & 0.237307 \tabularnewline
107 & 0.775915 & 0.44817 & 0.224085 \tabularnewline
108 & 0.798533 & 0.402934 & 0.201467 \tabularnewline
109 & 0.816139 & 0.367723 & 0.183861 \tabularnewline
110 & 0.819901 & 0.360199 & 0.180099 \tabularnewline
111 & 0.912268 & 0.175465 & 0.0877324 \tabularnewline
112 & 0.94018 & 0.11964 & 0.0598202 \tabularnewline
113 & 0.943308 & 0.113383 & 0.0566916 \tabularnewline
114 & 0.938359 & 0.123283 & 0.0616415 \tabularnewline
115 & 0.933017 & 0.133965 & 0.0669827 \tabularnewline
116 & 0.949924 & 0.100153 & 0.0500763 \tabularnewline
117 & 0.95094 & 0.0981198 & 0.0490599 \tabularnewline
118 & 0.958082 & 0.0838363 & 0.0419182 \tabularnewline
119 & 0.965183 & 0.0696332 & 0.0348166 \tabularnewline
120 & 0.959085 & 0.0818306 & 0.0409153 \tabularnewline
121 & 0.970132 & 0.059737 & 0.0298685 \tabularnewline
122 & 0.966185 & 0.0676301 & 0.0338151 \tabularnewline
123 & 0.970152 & 0.0596961 & 0.029848 \tabularnewline
124 & 0.97333 & 0.0533409 & 0.0266705 \tabularnewline
125 & 0.982533 & 0.0349342 & 0.0174671 \tabularnewline
126 & 0.979994 & 0.0400121 & 0.020006 \tabularnewline
127 & 0.990002 & 0.019995 & 0.00999752 \tabularnewline
128 & 0.991359 & 0.0172825 & 0.00864125 \tabularnewline
129 & 0.989392 & 0.0212169 & 0.0106085 \tabularnewline
130 & 0.987718 & 0.0245647 & 0.0122824 \tabularnewline
131 & 0.98714 & 0.0257196 & 0.0128598 \tabularnewline
132 & 0.985251 & 0.0294989 & 0.0147494 \tabularnewline
133 & 0.984335 & 0.03133 & 0.015665 \tabularnewline
134 & 0.982725 & 0.0345493 & 0.0172747 \tabularnewline
135 & 0.980498 & 0.0390039 & 0.019502 \tabularnewline
136 & 0.981579 & 0.0368411 & 0.0184206 \tabularnewline
137 & 0.977914 & 0.0441717 & 0.0220859 \tabularnewline
138 & 0.974606 & 0.0507886 & 0.0253943 \tabularnewline
139 & 0.970402 & 0.0591955 & 0.0295977 \tabularnewline
140 & 0.979089 & 0.0418228 & 0.0209114 \tabularnewline
141 & 0.984362 & 0.0312756 & 0.0156378 \tabularnewline
142 & 0.981104 & 0.0377916 & 0.0188958 \tabularnewline
143 & 0.977207 & 0.0455859 & 0.0227929 \tabularnewline
144 & 0.973812 & 0.0523759 & 0.0261879 \tabularnewline
145 & 0.978364 & 0.0432727 & 0.0216364 \tabularnewline
146 & 0.977206 & 0.0455882 & 0.0227941 \tabularnewline
147 & 0.974671 & 0.0506572 & 0.0253286 \tabularnewline
148 & 0.972389 & 0.0552225 & 0.0276112 \tabularnewline
149 & 0.967275 & 0.0654497 & 0.0327249 \tabularnewline
150 & 0.964634 & 0.0707316 & 0.0353658 \tabularnewline
151 & 0.960194 & 0.0796117 & 0.0398058 \tabularnewline
152 & 0.954937 & 0.0901255 & 0.0450627 \tabularnewline
153 & 0.947414 & 0.105173 & 0.0525864 \tabularnewline
154 & 0.951233 & 0.0975331 & 0.0487666 \tabularnewline
155 & 0.946195 & 0.10761 & 0.0538052 \tabularnewline
156 & 0.980662 & 0.038676 & 0.019338 \tabularnewline
157 & 0.978565 & 0.0428708 & 0.0214354 \tabularnewline
158 & 0.976459 & 0.0470821 & 0.023541 \tabularnewline
159 & 0.971396 & 0.0572074 & 0.0286037 \tabularnewline
160 & 0.976509 & 0.0469811 & 0.0234905 \tabularnewline
161 & 0.971872 & 0.0562569 & 0.0281285 \tabularnewline
162 & 0.969931 & 0.0601386 & 0.0300693 \tabularnewline
163 & 0.968848 & 0.062304 & 0.031152 \tabularnewline
164 & 0.964039 & 0.0719221 & 0.035961 \tabularnewline
165 & 0.95888 & 0.0822407 & 0.0411204 \tabularnewline
166 & 0.96992 & 0.0601592 & 0.0300796 \tabularnewline
167 & 0.964583 & 0.0708344 & 0.0354172 \tabularnewline
168 & 0.961377 & 0.0772462 & 0.0386231 \tabularnewline
169 & 0.983178 & 0.0336439 & 0.016822 \tabularnewline
170 & 0.984945 & 0.0301098 & 0.0150549 \tabularnewline
171 & 0.982719 & 0.0345626 & 0.0172813 \tabularnewline
172 & 0.980601 & 0.0387974 & 0.0193987 \tabularnewline
173 & 0.98555 & 0.0288998 & 0.0144499 \tabularnewline
174 & 0.981961 & 0.0360788 & 0.0180394 \tabularnewline
175 & 0.982283 & 0.0354337 & 0.0177168 \tabularnewline
176 & 0.978365 & 0.0432708 & 0.0216354 \tabularnewline
177 & 0.982458 & 0.0350847 & 0.0175424 \tabularnewline
178 & 0.979468 & 0.0410644 & 0.0205322 \tabularnewline
179 & 0.974735 & 0.0505293 & 0.0252647 \tabularnewline
180 & 0.96917 & 0.0616591 & 0.0308295 \tabularnewline
181 & 0.970406 & 0.059188 & 0.029594 \tabularnewline
182 & 0.966905 & 0.0661903 & 0.0330952 \tabularnewline
183 & 0.966558 & 0.0668841 & 0.0334421 \tabularnewline
184 & 0.961105 & 0.0777904 & 0.0388952 \tabularnewline
185 & 0.965504 & 0.0689928 & 0.0344964 \tabularnewline
186 & 0.965752 & 0.0684957 & 0.0342478 \tabularnewline
187 & 0.95931 & 0.0813808 & 0.0406904 \tabularnewline
188 & 0.955136 & 0.0897273 & 0.0448637 \tabularnewline
189 & 0.946369 & 0.107262 & 0.0536309 \tabularnewline
190 & 0.957208 & 0.0855844 & 0.0427922 \tabularnewline
191 & 0.949423 & 0.101155 & 0.0505775 \tabularnewline
192 & 0.968022 & 0.0639569 & 0.0319785 \tabularnewline
193 & 0.964099 & 0.0718014 & 0.0359007 \tabularnewline
194 & 0.95881 & 0.0823791 & 0.0411896 \tabularnewline
195 & 0.949822 & 0.100355 & 0.0501777 \tabularnewline
196 & 0.940403 & 0.119194 & 0.0595969 \tabularnewline
197 & 0.932607 & 0.134786 & 0.0673929 \tabularnewline
198 & 0.92913 & 0.14174 & 0.0708698 \tabularnewline
199 & 0.935357 & 0.129286 & 0.0646431 \tabularnewline
200 & 0.930919 & 0.138163 & 0.0690813 \tabularnewline
201 & 0.926112 & 0.147777 & 0.0738885 \tabularnewline
202 & 0.933683 & 0.132634 & 0.0663171 \tabularnewline
203 & 0.921175 & 0.157649 & 0.0788245 \tabularnewline
204 & 0.928333 & 0.143335 & 0.0716674 \tabularnewline
205 & 0.918492 & 0.163016 & 0.0815079 \tabularnewline
206 & 0.908832 & 0.182336 & 0.091168 \tabularnewline
207 & 0.906762 & 0.186475 & 0.0932377 \tabularnewline
208 & 0.895214 & 0.209572 & 0.104786 \tabularnewline
209 & 0.879171 & 0.241658 & 0.120829 \tabularnewline
210 & 0.872451 & 0.255098 & 0.127549 \tabularnewline
211 & 0.902644 & 0.194712 & 0.097356 \tabularnewline
212 & 0.895501 & 0.208998 & 0.104499 \tabularnewline
213 & 0.911129 & 0.177742 & 0.0888712 \tabularnewline
214 & 0.894353 & 0.211294 & 0.105647 \tabularnewline
215 & 0.876475 & 0.24705 & 0.123525 \tabularnewline
216 & 0.855414 & 0.289171 & 0.144586 \tabularnewline
217 & 0.849239 & 0.301523 & 0.150761 \tabularnewline
218 & 0.826904 & 0.346192 & 0.173096 \tabularnewline
219 & 0.843856 & 0.312288 & 0.156144 \tabularnewline
220 & 0.821883 & 0.356235 & 0.178117 \tabularnewline
221 & 0.800925 & 0.39815 & 0.199075 \tabularnewline
222 & 0.778429 & 0.443141 & 0.221571 \tabularnewline
223 & 0.764365 & 0.471271 & 0.235635 \tabularnewline
224 & 0.734567 & 0.530866 & 0.265433 \tabularnewline
225 & 0.723514 & 0.552973 & 0.276486 \tabularnewline
226 & 0.69381 & 0.612381 & 0.30619 \tabularnewline
227 & 0.65556 & 0.688879 & 0.34444 \tabularnewline
228 & 0.62467 & 0.75066 & 0.37533 \tabularnewline
229 & 0.625983 & 0.748035 & 0.374017 \tabularnewline
230 & 0.583568 & 0.832864 & 0.416432 \tabularnewline
231 & 0.544402 & 0.911196 & 0.455598 \tabularnewline
232 & 0.545835 & 0.908331 & 0.454165 \tabularnewline
233 & 0.581481 & 0.837038 & 0.418519 \tabularnewline
234 & 0.569502 & 0.860997 & 0.430498 \tabularnewline
235 & 0.621707 & 0.756586 & 0.378293 \tabularnewline
236 & 0.589352 & 0.821296 & 0.410648 \tabularnewline
237 & 0.587329 & 0.825341 & 0.412671 \tabularnewline
238 & 0.614961 & 0.770078 & 0.385039 \tabularnewline
239 & 0.570287 & 0.859426 & 0.429713 \tabularnewline
240 & 0.550367 & 0.899266 & 0.449633 \tabularnewline
241 & 0.530677 & 0.938646 & 0.469323 \tabularnewline
242 & 0.493546 & 0.987092 & 0.506454 \tabularnewline
243 & 0.654735 & 0.690531 & 0.345265 \tabularnewline
244 & 0.625426 & 0.749148 & 0.374574 \tabularnewline
245 & 0.655636 & 0.688727 & 0.344364 \tabularnewline
246 & 0.620664 & 0.758671 & 0.379336 \tabularnewline
247 & 0.579053 & 0.841894 & 0.420947 \tabularnewline
248 & 0.549873 & 0.900254 & 0.450127 \tabularnewline
249 & 0.578862 & 0.842276 & 0.421138 \tabularnewline
250 & 0.558455 & 0.88309 & 0.441545 \tabularnewline
251 & 0.545892 & 0.908217 & 0.454108 \tabularnewline
252 & 0.566547 & 0.866907 & 0.433453 \tabularnewline
253 & 0.513997 & 0.972006 & 0.486003 \tabularnewline
254 & 0.456067 & 0.912134 & 0.543933 \tabularnewline
255 & 0.400557 & 0.801113 & 0.599443 \tabularnewline
256 & 0.347254 & 0.694509 & 0.652746 \tabularnewline
257 & 0.315051 & 0.630103 & 0.684949 \tabularnewline
258 & 0.267982 & 0.535965 & 0.732018 \tabularnewline
259 & 0.255254 & 0.510507 & 0.744746 \tabularnewline
260 & 0.285104 & 0.570208 & 0.714896 \tabularnewline
261 & 0.238818 & 0.477636 & 0.761182 \tabularnewline
262 & 0.194704 & 0.389407 & 0.805296 \tabularnewline
263 & 0.22897 & 0.45794 & 0.77103 \tabularnewline
264 & 0.199373 & 0.398746 & 0.800627 \tabularnewline
265 & 0.215916 & 0.431833 & 0.784084 \tabularnewline
266 & 0.782048 & 0.435905 & 0.217952 \tabularnewline
267 & 0.749106 & 0.501789 & 0.250894 \tabularnewline
268 & 0.999587 & 0.000826611 & 0.000413305 \tabularnewline
269 & 0.999986 & 2.79838e-05 & 1.39919e-05 \tabularnewline
270 & 0.999962 & 7.53932e-05 & 3.76966e-05 \tabularnewline
271 & 0.999954 & 9.28057e-05 & 4.64029e-05 \tabularnewline
272 & 0.999941 & 0.000118497 & 5.92483e-05 \tabularnewline
273 & 0.999735 & 0.000529627 & 0.000264813 \tabularnewline
274 & 0.998854 & 0.00229173 & 0.00114586 \tabularnewline
275 & 0.996845 & 0.00631081 & 0.00315541 \tabularnewline
276 & 0.987349 & 0.0253028 & 0.0126514 \tabularnewline
277 & 0.955255 & 0.0894896 & 0.0447448 \tabularnewline
278 & 0.875329 & 0.249342 & 0.124671 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268567&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]9[/C][C]0.978083[/C][C]0.0438344[/C][C]0.0219172[/C][/ROW]
[ROW][C]10[/C][C]0.963865[/C][C]0.0722696[/C][C]0.0361348[/C][/ROW]
[ROW][C]11[/C][C]0.968112[/C][C]0.0637769[/C][C]0.0318884[/C][/ROW]
[ROW][C]12[/C][C]0.943492[/C][C]0.113015[/C][C]0.0565077[/C][/ROW]
[ROW][C]13[/C][C]0.956206[/C][C]0.0875879[/C][C]0.0437939[/C][/ROW]
[ROW][C]14[/C][C]0.934534[/C][C]0.130931[/C][C]0.0654655[/C][/ROW]
[ROW][C]15[/C][C]0.900824[/C][C]0.198351[/C][C]0.0991756[/C][/ROW]
[ROW][C]16[/C][C]0.861845[/C][C]0.276309[/C][C]0.138155[/C][/ROW]
[ROW][C]17[/C][C]0.836795[/C][C]0.326411[/C][C]0.163205[/C][/ROW]
[ROW][C]18[/C][C]0.794812[/C][C]0.410375[/C][C]0.205188[/C][/ROW]
[ROW][C]19[/C][C]0.736492[/C][C]0.527017[/C][C]0.263508[/C][/ROW]
[ROW][C]20[/C][C]0.690519[/C][C]0.618962[/C][C]0.309481[/C][/ROW]
[ROW][C]21[/C][C]0.621988[/C][C]0.756025[/C][C]0.378012[/C][/ROW]
[ROW][C]22[/C][C]0.688983[/C][C]0.622034[/C][C]0.311017[/C][/ROW]
[ROW][C]23[/C][C]0.658232[/C][C]0.683536[/C][C]0.341768[/C][/ROW]
[ROW][C]24[/C][C]0.595055[/C][C]0.809891[/C][C]0.404945[/C][/ROW]
[ROW][C]25[/C][C]0.551653[/C][C]0.896695[/C][C]0.448347[/C][/ROW]
[ROW][C]26[/C][C]0.492889[/C][C]0.985778[/C][C]0.507111[/C][/ROW]
[ROW][C]27[/C][C]0.43817[/C][C]0.87634[/C][C]0.56183[/C][/ROW]
[ROW][C]28[/C][C]0.377402[/C][C]0.754804[/C][C]0.622598[/C][/ROW]
[ROW][C]29[/C][C]0.421744[/C][C]0.843487[/C][C]0.578256[/C][/ROW]
[ROW][C]30[/C][C]0.383724[/C][C]0.767447[/C][C]0.616276[/C][/ROW]
[ROW][C]31[/C][C]0.357983[/C][C]0.715965[/C][C]0.642017[/C][/ROW]
[ROW][C]32[/C][C]0.32625[/C][C]0.6525[/C][C]0.67375[/C][/ROW]
[ROW][C]33[/C][C]0.325362[/C][C]0.650724[/C][C]0.674638[/C][/ROW]
[ROW][C]34[/C][C]0.437635[/C][C]0.87527[/C][C]0.562365[/C][/ROW]
[ROW][C]35[/C][C]0.38845[/C][C]0.7769[/C][C]0.61155[/C][/ROW]
[ROW][C]36[/C][C]0.422699[/C][C]0.845397[/C][C]0.577301[/C][/ROW]
[ROW][C]37[/C][C]0.378102[/C][C]0.756205[/C][C]0.621898[/C][/ROW]
[ROW][C]38[/C][C]0.337088[/C][C]0.674176[/C][C]0.662912[/C][/ROW]
[ROW][C]39[/C][C]0.294233[/C][C]0.588467[/C][C]0.705767[/C][/ROW]
[ROW][C]40[/C][C]0.293274[/C][C]0.586547[/C][C]0.706726[/C][/ROW]
[ROW][C]41[/C][C]0.341912[/C][C]0.683824[/C][C]0.658088[/C][/ROW]
[ROW][C]42[/C][C]0.310975[/C][C]0.621949[/C][C]0.689025[/C][/ROW]
[ROW][C]43[/C][C]0.440026[/C][C]0.880051[/C][C]0.559974[/C][/ROW]
[ROW][C]44[/C][C]0.400644[/C][C]0.801288[/C][C]0.599356[/C][/ROW]
[ROW][C]45[/C][C]0.380201[/C][C]0.760403[/C][C]0.619799[/C][/ROW]
[ROW][C]46[/C][C]0.346673[/C][C]0.693345[/C][C]0.653327[/C][/ROW]
[ROW][C]47[/C][C]0.336361[/C][C]0.672721[/C][C]0.663639[/C][/ROW]
[ROW][C]48[/C][C]0.298086[/C][C]0.596173[/C][C]0.701914[/C][/ROW]
[ROW][C]49[/C][C]0.26686[/C][C]0.53372[/C][C]0.73314[/C][/ROW]
[ROW][C]50[/C][C]0.362211[/C][C]0.724422[/C][C]0.637789[/C][/ROW]
[ROW][C]51[/C][C]0.407771[/C][C]0.815543[/C][C]0.592229[/C][/ROW]
[ROW][C]52[/C][C]0.402496[/C][C]0.804992[/C][C]0.597504[/C][/ROW]
[ROW][C]53[/C][C]0.364995[/C][C]0.729989[/C][C]0.635005[/C][/ROW]
[ROW][C]54[/C][C]0.402927[/C][C]0.805854[/C][C]0.597073[/C][/ROW]
[ROW][C]55[/C][C]0.380567[/C][C]0.761135[/C][C]0.619433[/C][/ROW]
[ROW][C]56[/C][C]0.391049[/C][C]0.782098[/C][C]0.608951[/C][/ROW]
[ROW][C]57[/C][C]0.401859[/C][C]0.803719[/C][C]0.598141[/C][/ROW]
[ROW][C]58[/C][C]0.369278[/C][C]0.738555[/C][C]0.630722[/C][/ROW]
[ROW][C]59[/C][C]0.494742[/C][C]0.989483[/C][C]0.505258[/C][/ROW]
[ROW][C]60[/C][C]0.585128[/C][C]0.829743[/C][C]0.414872[/C][/ROW]
[ROW][C]61[/C][C]0.545875[/C][C]0.908249[/C][C]0.454125[/C][/ROW]
[ROW][C]62[/C][C]0.574155[/C][C]0.85169[/C][C]0.425845[/C][/ROW]
[ROW][C]63[/C][C]0.56268[/C][C]0.874641[/C][C]0.43732[/C][/ROW]
[ROW][C]64[/C][C]0.54328[/C][C]0.91344[/C][C]0.45672[/C][/ROW]
[ROW][C]65[/C][C]0.578159[/C][C]0.843682[/C][C]0.421841[/C][/ROW]
[ROW][C]66[/C][C]0.644275[/C][C]0.711451[/C][C]0.355725[/C][/ROW]
[ROW][C]67[/C][C]0.620268[/C][C]0.759463[/C][C]0.379732[/C][/ROW]
[ROW][C]68[/C][C]0.587752[/C][C]0.824496[/C][C]0.412248[/C][/ROW]
[ROW][C]69[/C][C]0.576699[/C][C]0.846603[/C][C]0.423301[/C][/ROW]
[ROW][C]70[/C][C]0.542304[/C][C]0.915391[/C][C]0.457696[/C][/ROW]
[ROW][C]71[/C][C]0.550122[/C][C]0.899757[/C][C]0.449878[/C][/ROW]
[ROW][C]72[/C][C]0.528811[/C][C]0.942379[/C][C]0.471189[/C][/ROW]
[ROW][C]73[/C][C]0.49628[/C][C]0.992561[/C][C]0.50372[/C][/ROW]
[ROW][C]74[/C][C]0.466117[/C][C]0.932234[/C][C]0.533883[/C][/ROW]
[ROW][C]75[/C][C]0.438569[/C][C]0.877137[/C][C]0.561431[/C][/ROW]
[ROW][C]76[/C][C]0.44172[/C][C]0.883441[/C][C]0.55828[/C][/ROW]
[ROW][C]77[/C][C]0.560564[/C][C]0.878871[/C][C]0.439436[/C][/ROW]
[ROW][C]78[/C][C]0.544434[/C][C]0.911133[/C][C]0.455566[/C][/ROW]
[ROW][C]79[/C][C]0.521199[/C][C]0.957602[/C][C]0.478801[/C][/ROW]
[ROW][C]80[/C][C]0.512038[/C][C]0.975924[/C][C]0.487962[/C][/ROW]
[ROW][C]81[/C][C]0.500759[/C][C]0.998482[/C][C]0.499241[/C][/ROW]
[ROW][C]82[/C][C]0.475279[/C][C]0.950559[/C][C]0.524721[/C][/ROW]
[ROW][C]83[/C][C]0.535184[/C][C]0.929632[/C][C]0.464816[/C][/ROW]
[ROW][C]84[/C][C]0.503316[/C][C]0.993367[/C][C]0.496684[/C][/ROW]
[ROW][C]85[/C][C]0.535648[/C][C]0.928704[/C][C]0.464352[/C][/ROW]
[ROW][C]86[/C][C]0.504547[/C][C]0.990906[/C][C]0.495453[/C][/ROW]
[ROW][C]87[/C][C]0.612726[/C][C]0.774548[/C][C]0.387274[/C][/ROW]
[ROW][C]88[/C][C]0.596449[/C][C]0.807101[/C][C]0.403551[/C][/ROW]
[ROW][C]89[/C][C]0.565257[/C][C]0.869486[/C][C]0.434743[/C][/ROW]
[ROW][C]90[/C][C]0.53253[/C][C]0.934939[/C][C]0.46747[/C][/ROW]
[ROW][C]91[/C][C]0.49915[/C][C]0.998301[/C][C]0.50085[/C][/ROW]
[ROW][C]92[/C][C]0.496605[/C][C]0.993211[/C][C]0.503395[/C][/ROW]
[ROW][C]93[/C][C]0.522207[/C][C]0.955585[/C][C]0.477793[/C][/ROW]
[ROW][C]94[/C][C]0.538496[/C][C]0.923008[/C][C]0.461504[/C][/ROW]
[ROW][C]95[/C][C]0.666925[/C][C]0.66615[/C][C]0.333075[/C][/ROW]
[ROW][C]96[/C][C]0.644971[/C][C]0.710057[/C][C]0.355029[/C][/ROW]
[ROW][C]97[/C][C]0.64003[/C][C]0.719941[/C][C]0.35997[/C][/ROW]
[ROW][C]98[/C][C]0.685308[/C][C]0.629385[/C][C]0.314692[/C][/ROW]
[ROW][C]99[/C][C]0.668583[/C][C]0.662834[/C][C]0.331417[/C][/ROW]
[ROW][C]100[/C][C]0.692502[/C][C]0.614996[/C][C]0.307498[/C][/ROW]
[ROW][C]101[/C][C]0.675085[/C][C]0.64983[/C][C]0.324915[/C][/ROW]
[ROW][C]102[/C][C]0.726888[/C][C]0.546225[/C][C]0.273112[/C][/ROW]
[ROW][C]103[/C][C]0.802868[/C][C]0.394264[/C][C]0.197132[/C][/ROW]
[ROW][C]104[/C][C]0.783145[/C][C]0.43371[/C][C]0.216855[/C][/ROW]
[ROW][C]105[/C][C]0.765776[/C][C]0.468448[/C][C]0.234224[/C][/ROW]
[ROW][C]106[/C][C]0.762693[/C][C]0.474613[/C][C]0.237307[/C][/ROW]
[ROW][C]107[/C][C]0.775915[/C][C]0.44817[/C][C]0.224085[/C][/ROW]
[ROW][C]108[/C][C]0.798533[/C][C]0.402934[/C][C]0.201467[/C][/ROW]
[ROW][C]109[/C][C]0.816139[/C][C]0.367723[/C][C]0.183861[/C][/ROW]
[ROW][C]110[/C][C]0.819901[/C][C]0.360199[/C][C]0.180099[/C][/ROW]
[ROW][C]111[/C][C]0.912268[/C][C]0.175465[/C][C]0.0877324[/C][/ROW]
[ROW][C]112[/C][C]0.94018[/C][C]0.11964[/C][C]0.0598202[/C][/ROW]
[ROW][C]113[/C][C]0.943308[/C][C]0.113383[/C][C]0.0566916[/C][/ROW]
[ROW][C]114[/C][C]0.938359[/C][C]0.123283[/C][C]0.0616415[/C][/ROW]
[ROW][C]115[/C][C]0.933017[/C][C]0.133965[/C][C]0.0669827[/C][/ROW]
[ROW][C]116[/C][C]0.949924[/C][C]0.100153[/C][C]0.0500763[/C][/ROW]
[ROW][C]117[/C][C]0.95094[/C][C]0.0981198[/C][C]0.0490599[/C][/ROW]
[ROW][C]118[/C][C]0.958082[/C][C]0.0838363[/C][C]0.0419182[/C][/ROW]
[ROW][C]119[/C][C]0.965183[/C][C]0.0696332[/C][C]0.0348166[/C][/ROW]
[ROW][C]120[/C][C]0.959085[/C][C]0.0818306[/C][C]0.0409153[/C][/ROW]
[ROW][C]121[/C][C]0.970132[/C][C]0.059737[/C][C]0.0298685[/C][/ROW]
[ROW][C]122[/C][C]0.966185[/C][C]0.0676301[/C][C]0.0338151[/C][/ROW]
[ROW][C]123[/C][C]0.970152[/C][C]0.0596961[/C][C]0.029848[/C][/ROW]
[ROW][C]124[/C][C]0.97333[/C][C]0.0533409[/C][C]0.0266705[/C][/ROW]
[ROW][C]125[/C][C]0.982533[/C][C]0.0349342[/C][C]0.0174671[/C][/ROW]
[ROW][C]126[/C][C]0.979994[/C][C]0.0400121[/C][C]0.020006[/C][/ROW]
[ROW][C]127[/C][C]0.990002[/C][C]0.019995[/C][C]0.00999752[/C][/ROW]
[ROW][C]128[/C][C]0.991359[/C][C]0.0172825[/C][C]0.00864125[/C][/ROW]
[ROW][C]129[/C][C]0.989392[/C][C]0.0212169[/C][C]0.0106085[/C][/ROW]
[ROW][C]130[/C][C]0.987718[/C][C]0.0245647[/C][C]0.0122824[/C][/ROW]
[ROW][C]131[/C][C]0.98714[/C][C]0.0257196[/C][C]0.0128598[/C][/ROW]
[ROW][C]132[/C][C]0.985251[/C][C]0.0294989[/C][C]0.0147494[/C][/ROW]
[ROW][C]133[/C][C]0.984335[/C][C]0.03133[/C][C]0.015665[/C][/ROW]
[ROW][C]134[/C][C]0.982725[/C][C]0.0345493[/C][C]0.0172747[/C][/ROW]
[ROW][C]135[/C][C]0.980498[/C][C]0.0390039[/C][C]0.019502[/C][/ROW]
[ROW][C]136[/C][C]0.981579[/C][C]0.0368411[/C][C]0.0184206[/C][/ROW]
[ROW][C]137[/C][C]0.977914[/C][C]0.0441717[/C][C]0.0220859[/C][/ROW]
[ROW][C]138[/C][C]0.974606[/C][C]0.0507886[/C][C]0.0253943[/C][/ROW]
[ROW][C]139[/C][C]0.970402[/C][C]0.0591955[/C][C]0.0295977[/C][/ROW]
[ROW][C]140[/C][C]0.979089[/C][C]0.0418228[/C][C]0.0209114[/C][/ROW]
[ROW][C]141[/C][C]0.984362[/C][C]0.0312756[/C][C]0.0156378[/C][/ROW]
[ROW][C]142[/C][C]0.981104[/C][C]0.0377916[/C][C]0.0188958[/C][/ROW]
[ROW][C]143[/C][C]0.977207[/C][C]0.0455859[/C][C]0.0227929[/C][/ROW]
[ROW][C]144[/C][C]0.973812[/C][C]0.0523759[/C][C]0.0261879[/C][/ROW]
[ROW][C]145[/C][C]0.978364[/C][C]0.0432727[/C][C]0.0216364[/C][/ROW]
[ROW][C]146[/C][C]0.977206[/C][C]0.0455882[/C][C]0.0227941[/C][/ROW]
[ROW][C]147[/C][C]0.974671[/C][C]0.0506572[/C][C]0.0253286[/C][/ROW]
[ROW][C]148[/C][C]0.972389[/C][C]0.0552225[/C][C]0.0276112[/C][/ROW]
[ROW][C]149[/C][C]0.967275[/C][C]0.0654497[/C][C]0.0327249[/C][/ROW]
[ROW][C]150[/C][C]0.964634[/C][C]0.0707316[/C][C]0.0353658[/C][/ROW]
[ROW][C]151[/C][C]0.960194[/C][C]0.0796117[/C][C]0.0398058[/C][/ROW]
[ROW][C]152[/C][C]0.954937[/C][C]0.0901255[/C][C]0.0450627[/C][/ROW]
[ROW][C]153[/C][C]0.947414[/C][C]0.105173[/C][C]0.0525864[/C][/ROW]
[ROW][C]154[/C][C]0.951233[/C][C]0.0975331[/C][C]0.0487666[/C][/ROW]
[ROW][C]155[/C][C]0.946195[/C][C]0.10761[/C][C]0.0538052[/C][/ROW]
[ROW][C]156[/C][C]0.980662[/C][C]0.038676[/C][C]0.019338[/C][/ROW]
[ROW][C]157[/C][C]0.978565[/C][C]0.0428708[/C][C]0.0214354[/C][/ROW]
[ROW][C]158[/C][C]0.976459[/C][C]0.0470821[/C][C]0.023541[/C][/ROW]
[ROW][C]159[/C][C]0.971396[/C][C]0.0572074[/C][C]0.0286037[/C][/ROW]
[ROW][C]160[/C][C]0.976509[/C][C]0.0469811[/C][C]0.0234905[/C][/ROW]
[ROW][C]161[/C][C]0.971872[/C][C]0.0562569[/C][C]0.0281285[/C][/ROW]
[ROW][C]162[/C][C]0.969931[/C][C]0.0601386[/C][C]0.0300693[/C][/ROW]
[ROW][C]163[/C][C]0.968848[/C][C]0.062304[/C][C]0.031152[/C][/ROW]
[ROW][C]164[/C][C]0.964039[/C][C]0.0719221[/C][C]0.035961[/C][/ROW]
[ROW][C]165[/C][C]0.95888[/C][C]0.0822407[/C][C]0.0411204[/C][/ROW]
[ROW][C]166[/C][C]0.96992[/C][C]0.0601592[/C][C]0.0300796[/C][/ROW]
[ROW][C]167[/C][C]0.964583[/C][C]0.0708344[/C][C]0.0354172[/C][/ROW]
[ROW][C]168[/C][C]0.961377[/C][C]0.0772462[/C][C]0.0386231[/C][/ROW]
[ROW][C]169[/C][C]0.983178[/C][C]0.0336439[/C][C]0.016822[/C][/ROW]
[ROW][C]170[/C][C]0.984945[/C][C]0.0301098[/C][C]0.0150549[/C][/ROW]
[ROW][C]171[/C][C]0.982719[/C][C]0.0345626[/C][C]0.0172813[/C][/ROW]
[ROW][C]172[/C][C]0.980601[/C][C]0.0387974[/C][C]0.0193987[/C][/ROW]
[ROW][C]173[/C][C]0.98555[/C][C]0.0288998[/C][C]0.0144499[/C][/ROW]
[ROW][C]174[/C][C]0.981961[/C][C]0.0360788[/C][C]0.0180394[/C][/ROW]
[ROW][C]175[/C][C]0.982283[/C][C]0.0354337[/C][C]0.0177168[/C][/ROW]
[ROW][C]176[/C][C]0.978365[/C][C]0.0432708[/C][C]0.0216354[/C][/ROW]
[ROW][C]177[/C][C]0.982458[/C][C]0.0350847[/C][C]0.0175424[/C][/ROW]
[ROW][C]178[/C][C]0.979468[/C][C]0.0410644[/C][C]0.0205322[/C][/ROW]
[ROW][C]179[/C][C]0.974735[/C][C]0.0505293[/C][C]0.0252647[/C][/ROW]
[ROW][C]180[/C][C]0.96917[/C][C]0.0616591[/C][C]0.0308295[/C][/ROW]
[ROW][C]181[/C][C]0.970406[/C][C]0.059188[/C][C]0.029594[/C][/ROW]
[ROW][C]182[/C][C]0.966905[/C][C]0.0661903[/C][C]0.0330952[/C][/ROW]
[ROW][C]183[/C][C]0.966558[/C][C]0.0668841[/C][C]0.0334421[/C][/ROW]
[ROW][C]184[/C][C]0.961105[/C][C]0.0777904[/C][C]0.0388952[/C][/ROW]
[ROW][C]185[/C][C]0.965504[/C][C]0.0689928[/C][C]0.0344964[/C][/ROW]
[ROW][C]186[/C][C]0.965752[/C][C]0.0684957[/C][C]0.0342478[/C][/ROW]
[ROW][C]187[/C][C]0.95931[/C][C]0.0813808[/C][C]0.0406904[/C][/ROW]
[ROW][C]188[/C][C]0.955136[/C][C]0.0897273[/C][C]0.0448637[/C][/ROW]
[ROW][C]189[/C][C]0.946369[/C][C]0.107262[/C][C]0.0536309[/C][/ROW]
[ROW][C]190[/C][C]0.957208[/C][C]0.0855844[/C][C]0.0427922[/C][/ROW]
[ROW][C]191[/C][C]0.949423[/C][C]0.101155[/C][C]0.0505775[/C][/ROW]
[ROW][C]192[/C][C]0.968022[/C][C]0.0639569[/C][C]0.0319785[/C][/ROW]
[ROW][C]193[/C][C]0.964099[/C][C]0.0718014[/C][C]0.0359007[/C][/ROW]
[ROW][C]194[/C][C]0.95881[/C][C]0.0823791[/C][C]0.0411896[/C][/ROW]
[ROW][C]195[/C][C]0.949822[/C][C]0.100355[/C][C]0.0501777[/C][/ROW]
[ROW][C]196[/C][C]0.940403[/C][C]0.119194[/C][C]0.0595969[/C][/ROW]
[ROW][C]197[/C][C]0.932607[/C][C]0.134786[/C][C]0.0673929[/C][/ROW]
[ROW][C]198[/C][C]0.92913[/C][C]0.14174[/C][C]0.0708698[/C][/ROW]
[ROW][C]199[/C][C]0.935357[/C][C]0.129286[/C][C]0.0646431[/C][/ROW]
[ROW][C]200[/C][C]0.930919[/C][C]0.138163[/C][C]0.0690813[/C][/ROW]
[ROW][C]201[/C][C]0.926112[/C][C]0.147777[/C][C]0.0738885[/C][/ROW]
[ROW][C]202[/C][C]0.933683[/C][C]0.132634[/C][C]0.0663171[/C][/ROW]
[ROW][C]203[/C][C]0.921175[/C][C]0.157649[/C][C]0.0788245[/C][/ROW]
[ROW][C]204[/C][C]0.928333[/C][C]0.143335[/C][C]0.0716674[/C][/ROW]
[ROW][C]205[/C][C]0.918492[/C][C]0.163016[/C][C]0.0815079[/C][/ROW]
[ROW][C]206[/C][C]0.908832[/C][C]0.182336[/C][C]0.091168[/C][/ROW]
[ROW][C]207[/C][C]0.906762[/C][C]0.186475[/C][C]0.0932377[/C][/ROW]
[ROW][C]208[/C][C]0.895214[/C][C]0.209572[/C][C]0.104786[/C][/ROW]
[ROW][C]209[/C][C]0.879171[/C][C]0.241658[/C][C]0.120829[/C][/ROW]
[ROW][C]210[/C][C]0.872451[/C][C]0.255098[/C][C]0.127549[/C][/ROW]
[ROW][C]211[/C][C]0.902644[/C][C]0.194712[/C][C]0.097356[/C][/ROW]
[ROW][C]212[/C][C]0.895501[/C][C]0.208998[/C][C]0.104499[/C][/ROW]
[ROW][C]213[/C][C]0.911129[/C][C]0.177742[/C][C]0.0888712[/C][/ROW]
[ROW][C]214[/C][C]0.894353[/C][C]0.211294[/C][C]0.105647[/C][/ROW]
[ROW][C]215[/C][C]0.876475[/C][C]0.24705[/C][C]0.123525[/C][/ROW]
[ROW][C]216[/C][C]0.855414[/C][C]0.289171[/C][C]0.144586[/C][/ROW]
[ROW][C]217[/C][C]0.849239[/C][C]0.301523[/C][C]0.150761[/C][/ROW]
[ROW][C]218[/C][C]0.826904[/C][C]0.346192[/C][C]0.173096[/C][/ROW]
[ROW][C]219[/C][C]0.843856[/C][C]0.312288[/C][C]0.156144[/C][/ROW]
[ROW][C]220[/C][C]0.821883[/C][C]0.356235[/C][C]0.178117[/C][/ROW]
[ROW][C]221[/C][C]0.800925[/C][C]0.39815[/C][C]0.199075[/C][/ROW]
[ROW][C]222[/C][C]0.778429[/C][C]0.443141[/C][C]0.221571[/C][/ROW]
[ROW][C]223[/C][C]0.764365[/C][C]0.471271[/C][C]0.235635[/C][/ROW]
[ROW][C]224[/C][C]0.734567[/C][C]0.530866[/C][C]0.265433[/C][/ROW]
[ROW][C]225[/C][C]0.723514[/C][C]0.552973[/C][C]0.276486[/C][/ROW]
[ROW][C]226[/C][C]0.69381[/C][C]0.612381[/C][C]0.30619[/C][/ROW]
[ROW][C]227[/C][C]0.65556[/C][C]0.688879[/C][C]0.34444[/C][/ROW]
[ROW][C]228[/C][C]0.62467[/C][C]0.75066[/C][C]0.37533[/C][/ROW]
[ROW][C]229[/C][C]0.625983[/C][C]0.748035[/C][C]0.374017[/C][/ROW]
[ROW][C]230[/C][C]0.583568[/C][C]0.832864[/C][C]0.416432[/C][/ROW]
[ROW][C]231[/C][C]0.544402[/C][C]0.911196[/C][C]0.455598[/C][/ROW]
[ROW][C]232[/C][C]0.545835[/C][C]0.908331[/C][C]0.454165[/C][/ROW]
[ROW][C]233[/C][C]0.581481[/C][C]0.837038[/C][C]0.418519[/C][/ROW]
[ROW][C]234[/C][C]0.569502[/C][C]0.860997[/C][C]0.430498[/C][/ROW]
[ROW][C]235[/C][C]0.621707[/C][C]0.756586[/C][C]0.378293[/C][/ROW]
[ROW][C]236[/C][C]0.589352[/C][C]0.821296[/C][C]0.410648[/C][/ROW]
[ROW][C]237[/C][C]0.587329[/C][C]0.825341[/C][C]0.412671[/C][/ROW]
[ROW][C]238[/C][C]0.614961[/C][C]0.770078[/C][C]0.385039[/C][/ROW]
[ROW][C]239[/C][C]0.570287[/C][C]0.859426[/C][C]0.429713[/C][/ROW]
[ROW][C]240[/C][C]0.550367[/C][C]0.899266[/C][C]0.449633[/C][/ROW]
[ROW][C]241[/C][C]0.530677[/C][C]0.938646[/C][C]0.469323[/C][/ROW]
[ROW][C]242[/C][C]0.493546[/C][C]0.987092[/C][C]0.506454[/C][/ROW]
[ROW][C]243[/C][C]0.654735[/C][C]0.690531[/C][C]0.345265[/C][/ROW]
[ROW][C]244[/C][C]0.625426[/C][C]0.749148[/C][C]0.374574[/C][/ROW]
[ROW][C]245[/C][C]0.655636[/C][C]0.688727[/C][C]0.344364[/C][/ROW]
[ROW][C]246[/C][C]0.620664[/C][C]0.758671[/C][C]0.379336[/C][/ROW]
[ROW][C]247[/C][C]0.579053[/C][C]0.841894[/C][C]0.420947[/C][/ROW]
[ROW][C]248[/C][C]0.549873[/C][C]0.900254[/C][C]0.450127[/C][/ROW]
[ROW][C]249[/C][C]0.578862[/C][C]0.842276[/C][C]0.421138[/C][/ROW]
[ROW][C]250[/C][C]0.558455[/C][C]0.88309[/C][C]0.441545[/C][/ROW]
[ROW][C]251[/C][C]0.545892[/C][C]0.908217[/C][C]0.454108[/C][/ROW]
[ROW][C]252[/C][C]0.566547[/C][C]0.866907[/C][C]0.433453[/C][/ROW]
[ROW][C]253[/C][C]0.513997[/C][C]0.972006[/C][C]0.486003[/C][/ROW]
[ROW][C]254[/C][C]0.456067[/C][C]0.912134[/C][C]0.543933[/C][/ROW]
[ROW][C]255[/C][C]0.400557[/C][C]0.801113[/C][C]0.599443[/C][/ROW]
[ROW][C]256[/C][C]0.347254[/C][C]0.694509[/C][C]0.652746[/C][/ROW]
[ROW][C]257[/C][C]0.315051[/C][C]0.630103[/C][C]0.684949[/C][/ROW]
[ROW][C]258[/C][C]0.267982[/C][C]0.535965[/C][C]0.732018[/C][/ROW]
[ROW][C]259[/C][C]0.255254[/C][C]0.510507[/C][C]0.744746[/C][/ROW]
[ROW][C]260[/C][C]0.285104[/C][C]0.570208[/C][C]0.714896[/C][/ROW]
[ROW][C]261[/C][C]0.238818[/C][C]0.477636[/C][C]0.761182[/C][/ROW]
[ROW][C]262[/C][C]0.194704[/C][C]0.389407[/C][C]0.805296[/C][/ROW]
[ROW][C]263[/C][C]0.22897[/C][C]0.45794[/C][C]0.77103[/C][/ROW]
[ROW][C]264[/C][C]0.199373[/C][C]0.398746[/C][C]0.800627[/C][/ROW]
[ROW][C]265[/C][C]0.215916[/C][C]0.431833[/C][C]0.784084[/C][/ROW]
[ROW][C]266[/C][C]0.782048[/C][C]0.435905[/C][C]0.217952[/C][/ROW]
[ROW][C]267[/C][C]0.749106[/C][C]0.501789[/C][C]0.250894[/C][/ROW]
[ROW][C]268[/C][C]0.999587[/C][C]0.000826611[/C][C]0.000413305[/C][/ROW]
[ROW][C]269[/C][C]0.999986[/C][C]2.79838e-05[/C][C]1.39919e-05[/C][/ROW]
[ROW][C]270[/C][C]0.999962[/C][C]7.53932e-05[/C][C]3.76966e-05[/C][/ROW]
[ROW][C]271[/C][C]0.999954[/C][C]9.28057e-05[/C][C]4.64029e-05[/C][/ROW]
[ROW][C]272[/C][C]0.999941[/C][C]0.000118497[/C][C]5.92483e-05[/C][/ROW]
[ROW][C]273[/C][C]0.999735[/C][C]0.000529627[/C][C]0.000264813[/C][/ROW]
[ROW][C]274[/C][C]0.998854[/C][C]0.00229173[/C][C]0.00114586[/C][/ROW]
[ROW][C]275[/C][C]0.996845[/C][C]0.00631081[/C][C]0.00315541[/C][/ROW]
[ROW][C]276[/C][C]0.987349[/C][C]0.0253028[/C][C]0.0126514[/C][/ROW]
[ROW][C]277[/C][C]0.955255[/C][C]0.0894896[/C][C]0.0447448[/C][/ROW]
[ROW][C]278[/C][C]0.875329[/C][C]0.249342[/C][C]0.124671[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268567&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268567&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
90.9780830.04383440.0219172
100.9638650.07226960.0361348
110.9681120.06377690.0318884
120.9434920.1130150.0565077
130.9562060.08758790.0437939
140.9345340.1309310.0654655
150.9008240.1983510.0991756
160.8618450.2763090.138155
170.8367950.3264110.163205
180.7948120.4103750.205188
190.7364920.5270170.263508
200.6905190.6189620.309481
210.6219880.7560250.378012
220.6889830.6220340.311017
230.6582320.6835360.341768
240.5950550.8098910.404945
250.5516530.8966950.448347
260.4928890.9857780.507111
270.438170.876340.56183
280.3774020.7548040.622598
290.4217440.8434870.578256
300.3837240.7674470.616276
310.3579830.7159650.642017
320.326250.65250.67375
330.3253620.6507240.674638
340.4376350.875270.562365
350.388450.77690.61155
360.4226990.8453970.577301
370.3781020.7562050.621898
380.3370880.6741760.662912
390.2942330.5884670.705767
400.2932740.5865470.706726
410.3419120.6838240.658088
420.3109750.6219490.689025
430.4400260.8800510.559974
440.4006440.8012880.599356
450.3802010.7604030.619799
460.3466730.6933450.653327
470.3363610.6727210.663639
480.2980860.5961730.701914
490.266860.533720.73314
500.3622110.7244220.637789
510.4077710.8155430.592229
520.4024960.8049920.597504
530.3649950.7299890.635005
540.4029270.8058540.597073
550.3805670.7611350.619433
560.3910490.7820980.608951
570.4018590.8037190.598141
580.3692780.7385550.630722
590.4947420.9894830.505258
600.5851280.8297430.414872
610.5458750.9082490.454125
620.5741550.851690.425845
630.562680.8746410.43732
640.543280.913440.45672
650.5781590.8436820.421841
660.6442750.7114510.355725
670.6202680.7594630.379732
680.5877520.8244960.412248
690.5766990.8466030.423301
700.5423040.9153910.457696
710.5501220.8997570.449878
720.5288110.9423790.471189
730.496280.9925610.50372
740.4661170.9322340.533883
750.4385690.8771370.561431
760.441720.8834410.55828
770.5605640.8788710.439436
780.5444340.9111330.455566
790.5211990.9576020.478801
800.5120380.9759240.487962
810.5007590.9984820.499241
820.4752790.9505590.524721
830.5351840.9296320.464816
840.5033160.9933670.496684
850.5356480.9287040.464352
860.5045470.9909060.495453
870.6127260.7745480.387274
880.5964490.8071010.403551
890.5652570.8694860.434743
900.532530.9349390.46747
910.499150.9983010.50085
920.4966050.9932110.503395
930.5222070.9555850.477793
940.5384960.9230080.461504
950.6669250.666150.333075
960.6449710.7100570.355029
970.640030.7199410.35997
980.6853080.6293850.314692
990.6685830.6628340.331417
1000.6925020.6149960.307498
1010.6750850.649830.324915
1020.7268880.5462250.273112
1030.8028680.3942640.197132
1040.7831450.433710.216855
1050.7657760.4684480.234224
1060.7626930.4746130.237307
1070.7759150.448170.224085
1080.7985330.4029340.201467
1090.8161390.3677230.183861
1100.8199010.3601990.180099
1110.9122680.1754650.0877324
1120.940180.119640.0598202
1130.9433080.1133830.0566916
1140.9383590.1232830.0616415
1150.9330170.1339650.0669827
1160.9499240.1001530.0500763
1170.950940.09811980.0490599
1180.9580820.08383630.0419182
1190.9651830.06963320.0348166
1200.9590850.08183060.0409153
1210.9701320.0597370.0298685
1220.9661850.06763010.0338151
1230.9701520.05969610.029848
1240.973330.05334090.0266705
1250.9825330.03493420.0174671
1260.9799940.04001210.020006
1270.9900020.0199950.00999752
1280.9913590.01728250.00864125
1290.9893920.02121690.0106085
1300.9877180.02456470.0122824
1310.987140.02571960.0128598
1320.9852510.02949890.0147494
1330.9843350.031330.015665
1340.9827250.03454930.0172747
1350.9804980.03900390.019502
1360.9815790.03684110.0184206
1370.9779140.04417170.0220859
1380.9746060.05078860.0253943
1390.9704020.05919550.0295977
1400.9790890.04182280.0209114
1410.9843620.03127560.0156378
1420.9811040.03779160.0188958
1430.9772070.04558590.0227929
1440.9738120.05237590.0261879
1450.9783640.04327270.0216364
1460.9772060.04558820.0227941
1470.9746710.05065720.0253286
1480.9723890.05522250.0276112
1490.9672750.06544970.0327249
1500.9646340.07073160.0353658
1510.9601940.07961170.0398058
1520.9549370.09012550.0450627
1530.9474140.1051730.0525864
1540.9512330.09753310.0487666
1550.9461950.107610.0538052
1560.9806620.0386760.019338
1570.9785650.04287080.0214354
1580.9764590.04708210.023541
1590.9713960.05720740.0286037
1600.9765090.04698110.0234905
1610.9718720.05625690.0281285
1620.9699310.06013860.0300693
1630.9688480.0623040.031152
1640.9640390.07192210.035961
1650.958880.08224070.0411204
1660.969920.06015920.0300796
1670.9645830.07083440.0354172
1680.9613770.07724620.0386231
1690.9831780.03364390.016822
1700.9849450.03010980.0150549
1710.9827190.03456260.0172813
1720.9806010.03879740.0193987
1730.985550.02889980.0144499
1740.9819610.03607880.0180394
1750.9822830.03543370.0177168
1760.9783650.04327080.0216354
1770.9824580.03508470.0175424
1780.9794680.04106440.0205322
1790.9747350.05052930.0252647
1800.969170.06165910.0308295
1810.9704060.0591880.029594
1820.9669050.06619030.0330952
1830.9665580.06688410.0334421
1840.9611050.07779040.0388952
1850.9655040.06899280.0344964
1860.9657520.06849570.0342478
1870.959310.08138080.0406904
1880.9551360.08972730.0448637
1890.9463690.1072620.0536309
1900.9572080.08558440.0427922
1910.9494230.1011550.0505775
1920.9680220.06395690.0319785
1930.9640990.07180140.0359007
1940.958810.08237910.0411896
1950.9498220.1003550.0501777
1960.9404030.1191940.0595969
1970.9326070.1347860.0673929
1980.929130.141740.0708698
1990.9353570.1292860.0646431
2000.9309190.1381630.0690813
2010.9261120.1477770.0738885
2020.9336830.1326340.0663171
2030.9211750.1576490.0788245
2040.9283330.1433350.0716674
2050.9184920.1630160.0815079
2060.9088320.1823360.091168
2070.9067620.1864750.0932377
2080.8952140.2095720.104786
2090.8791710.2416580.120829
2100.8724510.2550980.127549
2110.9026440.1947120.097356
2120.8955010.2089980.104499
2130.9111290.1777420.0888712
2140.8943530.2112940.105647
2150.8764750.247050.123525
2160.8554140.2891710.144586
2170.8492390.3015230.150761
2180.8269040.3461920.173096
2190.8438560.3122880.156144
2200.8218830.3562350.178117
2210.8009250.398150.199075
2220.7784290.4431410.221571
2230.7643650.4712710.235635
2240.7345670.5308660.265433
2250.7235140.5529730.276486
2260.693810.6123810.30619
2270.655560.6888790.34444
2280.624670.750660.37533
2290.6259830.7480350.374017
2300.5835680.8328640.416432
2310.5444020.9111960.455598
2320.5458350.9083310.454165
2330.5814810.8370380.418519
2340.5695020.8609970.430498
2350.6217070.7565860.378293
2360.5893520.8212960.410648
2370.5873290.8253410.412671
2380.6149610.7700780.385039
2390.5702870.8594260.429713
2400.5503670.8992660.449633
2410.5306770.9386460.469323
2420.4935460.9870920.506454
2430.6547350.6905310.345265
2440.6254260.7491480.374574
2450.6556360.6887270.344364
2460.6206640.7586710.379336
2470.5790530.8418940.420947
2480.5498730.9002540.450127
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2500.5584550.883090.441545
2510.5458920.9082170.454108
2520.5665470.8669070.433453
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2580.2679820.5359650.732018
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2600.2851040.5702080.714896
2610.2388180.4776360.761182
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2630.228970.457940.77103
2640.1993730.3987460.800627
2650.2159160.4318330.784084
2660.7820480.4359050.217952
2670.7491060.5017890.250894
2680.9995870.0008266110.000413305
2690.9999862.79838e-051.39919e-05
2700.9999627.53932e-053.76966e-05
2710.9999549.28057e-054.64029e-05
2720.9999410.0001184975.92483e-05
2730.9997350.0005296270.000264813
2740.9988540.002291730.00114586
2750.9968450.006310810.00315541
2760.9873490.02530280.0126514
2770.9552550.08948960.0447448
2780.8753290.2493420.124671






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level80.0296296NOK
5% type I error level430.159259NOK
10% type I error level880.325926NOK

\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 & 8 & 0.0296296 & NOK \tabularnewline
5% type I error level & 43 & 0.159259 & NOK \tabularnewline
10% type I error level & 88 & 0.325926 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268567&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]8[/C][C]0.0296296[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]43[/C][C]0.159259[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]88[/C][C]0.325926[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268567&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268567&T=6

As an alternative you can also use a QR Code:  
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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 level80.0296296NOK
5% type I error level430.159259NOK
10% type I error level880.325926NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 6 ; 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 <- '6'
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')
}