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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 15:37:12 +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/t1418657843vrcx6dtwc26yieu.htm/, Retrieved Thu, 31 Oct 2024 22:46:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268645, Retrieved Thu, 31 Oct 2024 22:46:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-15 15:37:12] [023a69c6c348bca0f1811b046758af62] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
149	96	18	68	86	12.9
152	75	7	55	62	7.4
139	70	31	39	70	12.2
148	88	39	32	71	12.8
158	114	46	62	108	7.4
128	69	31	33	64	6.7
224	176	67	52	119	12.6
159	114	35	62	97	14.8
105	121	52	77	129	13.3
159	110	77	76	153	11.1
167	158	37	41	78	8.2
165	116	32	48	80	11.4
159	181	36	63	99	6.4
119	77	38	30	68	10.6
176	141	69	78	147	12.0
54	35	21	19	40	6.3
91	80	26	31	57	11.3
163	152	54	66	120	11.9
124	97	36	35	71	9.3
137	99	42	42	84	9.6
121	84	23	45	68	10.0
153	68	34	21	55	6.4
148	101	112	25	137	13.8
221	107	35	44	79	10.8
188	88	47	69	116	13.8
149	112	47	54	101	11.7
244	171	37	74	111	10.9
148	137	109	80	189	16.1
92	77	24	42	66	13.4
150	66	20	61	81	9.9
153	93	22	41	63	11.5
94	105	23	46	69	8.3
156	131	32	39	71	11.7
146	89	7	63	70	6.1
132	102	30	34	64	9.0
161	161	92	51	143	9.7
105	120	43	42	85	10.8
97	127	55	31	86	10.3
151	77	16	39	55	10.4
131	108	49	20	69	12.7
166	85	71	49	120	9.3
157	168	43	53	96	11.8
111	48	29	31	60	5.9
145	152	56	39	95	11.4
162	75	46	54	100	13.0
163	107	19	49	68	10.8
59	62	23	34	57	12.3
187	121	59	46	105	11.3
109	124	30	55	85	11.8
90	72	61	42	103	7.9
105	40	7	50	57	12.7
83	58	38	13	51	12.3
116	97	32	37	69	11.6
42	88	16	25	41	6.7
148	126	19	30	49	10.9
155	104	22	28	50	12.1
125	148	48	45	93	13.3
116	146	23	35	58	10.1
128	80	26	28	54	5.7
138	97	33	41	74	14.3
49	25	9	6	15	8.0
96	99	24	45	69	13.3
164	118	34	73	107	9.3
162	58	48	17	65	12.5
99	63	18	40	58	7.6
202	139	43	64	107	15.9
186	50	33	37	70	9.2
66	60	28	25	53	9.1
183	152	71	65	136	11.1
214	142	26	100	126	13.0
188	94	67	28	95	14.5
104	66	34	35	69	12.2
177	127	80	56	136	12.3
126	67	29	29	58	11.4
76	90	16	43	59	8.8
99	75	59	59	118	14.6
157	96	58	52	110	7.3
139	128	32	50	82	12.6
78	41	47	3	50	NA
162	146	43	59	102	13.0
108	69	38	27	65	12.6
159	186	29	61	90	13.2
74	81	36	28	64	9.9
110	85	32	51	83	7.7
96	54	35	35	70	10.5
116	46	21	29	50	13.4
87	106	29	48	77	10.9
97	34	12	25	37	4.3
127	60	37	44	81	10.3
106	95	37	64	101	11.8
80	57	47	32	79	11.2
74	62	51	20	71	11.4
91	36	32	28	60	8.6
133	56	21	34	55	13.2
74	54	13	31	44	12.6
114	64	14	26	40	5.6
140	76	-2	58	56	9.9
95	98	20	23	43	8.8
98	88	24	21	45	7.7
121	35	11	21	32	9.0
126	102	23	33	56	7.3
98	61	24	16	40	11.4
95	80	14	20	34	13.6
110	49	52	37	89	7.9
70	78	15	35	50	10.7
102	90	23	33	56	10.3
86	45	19	27	46	8.3
130	55	35	41	76	9.6
96	96	24	40	64	14.2
102	43	39	35	74	8.5
100	52	29	28	57	13.5
94	60	13	32	45	4.9
52	54	8	22	30	6.4
98	51	18	44	62	9.6
118	51	24	27	51	11.6
99	38	19	17	36	11.1
48	41	23	12	34	4.35
50	146	16	45	61	12.7
150	182	33	37	70	18.1
154	192	32	37	69	17.85
109	263	37	108	145	16.6
68	35	14	10	23	12.6
194	439	52	68	120	17.1
158	214	75	72	147	19.1
159	341	72	143	215	16.1
67	58	15	9	24	13.35
147	292	29	55	84	18.4
39	85	13	17	30	14.7
100	200	40	37	77	10.6
111	158	19	27	46	12.6
138	199	24	37	61	16.2
101	297	121	58	178	13.6
131	227	93	66	160	18.9
101	108	36	21	57	14.1
114	86	23	19	42	14.5
165	302	85	78	163	16.15
114	148	41	35	75	14.75
111	178	46	48	94	14.8
75	120	18	27	45	12.45
82	207	35	43	78	12.65
121	157	17	30	47	17.35
32	128	4	25	29	8.6
150	296	28	69	97	18.4
117	323	44	72	116	16.1
71	79	10	23	32	11.6
165	70	38	13	50	17.75
154	146	57	61	118	15.25
126	246	23	43	66	17.65
138	145	26	22	48	15.6
149	196	36	51	86	16.35
145	199	22	67	89	17.65
120	127	40	36	76	13.6
138	91	18	21	39	11.7
109	153	31	44	75	14.35
132	299	11	45	57	14.75
172	228	38	34	72	18.25
169	190	24	36	60	9.9
114	180	37	72	109	16
156	212	37	39	76	18.25
172	269	22	43	65	16.85
68	130	15	25	40	14.6
89	179	2	56	58	13.85
167	243	43	80	123	18.95
113	190	31	40	71	15.6
115	299	29	73	102	14.85
78	121	45	34	80	11.75
118	137	25	72	97	18.45
87	305	4	42	46	15.9
173	157	31	61	93	17.1
2	96	-4	23	19	16.1
162	183	66	74	140	19.9
49	52	61	16	78	10.95
122	238	32	66	98	18.45
96	40	31	9	40	15.1
100	226	39	41	80	15
82	190	19	57	76	11.35
100	214	31	48	79	15.95
115	145	36	51	87	18.1
141	119	42	53	95	14.6
165	222	21	29	49	15.4
165	222	21	29	49	15.4
110	159	25	55	80	17.6
118	165	32	54	86	13.35
158	249	26	43	69	19.1
146	125	28	51	79	15.35
49	122	32	20	52	7.6
90	186	41	79	120	13.4
121	148	29	39	69	13.9
155	274	33	61	94	19.1
104	172	17	55	72	15.25
147	84	13	30	43	12.9
110	168	32	55	87	16.1
108	102	30	22	52	17.35
113	106	34	37	71	13.15
115	2	59	2	61	12.15
61	139	13	38	51	12.6
60	95	23	27	50	10.35
109	130	10	56	67	15.4
68	72	5	25	30	9.6
111	141	31	39	70	18.2
77	113	19	33	52	13.6
73	206	32	43	75	14.85
151	268	30	57	87	14.75
89	175	25	43	69	14.1
78	77	48	23	72	14.9
110	125	35	44	79	16.25
220	255	67	54	121	19.25
65	111	15	28	43	13.6
141	132	22	36	58	13.6
117	211	18	39	57	15.65
122	92	33	16	50	12.75
63	76	46	23	69	14.6
44	171	24	40	64	9.85
52	83	14	24	38	12.65
62	119	23	29	53	11.9
131	266	12	78	90	19.2
101	186	38	57	96	16.6
42	50	12	37	49	11.2
152	117	28	27	56	15.25
107	219	41	61	102	11.9
77	246	12	27	40	13.2
154	279	31	69	100	16.35
103	148	33	34	67	12.4
96	137	34	44	78	15.85
154	130	41	21	62	14.35
175	181	21	34	55	18.15
57	98	20	39	59	11.15
112	226	44	51	96	15.65
143	234	52	34	86	17.75
49	138	7	31	38	7.65
110	85	29	13	43	12.35
131	66	11	12	23	15.6
167	236	26	51	77	19.3
56	106	24	24	48	15.2
137	135	7	19	26	17.1
86	122	60	30	91	15.6
121	218	13	81	94	18.4
149	199	20	42	62	19.05
168	112	52	22	74	18.55
140	278	28	85	114	19.1
88	94	25	27	52	13.1
168	113	39	25	64	12.85
94	84	9	22	31	9.5
51	86	19	19	38	4.5
48	62	13	14	27	11.85
145	222	60	45	105	13.6
66	167	19	45	64	11.7
85	82	34	28	62	12.4
109	207	14	51	65	13.35
63	184	17	41	58	11.4
102	83	45	31	76	14.9
162	183	66	74	140	19.9
128	85	24	24	48	17.75
86	89	48	19	68	11.2
114	225	29	51	80	14.6
164	237	-2	73	71	17.6
119	102	51	24	76	14.05
126	221	2	61	63	16.1
132	128	24	23	46	13.35
142	91	40	14	53	11.85
83	198	20	54	74	11.95
94	204	19	51	70	14.75
81	158	16	62	78	15.15
166	138	20	36	56	13.2
110	226	40	59	100	16.85
64	44	27	24	51	7.85
93	196	25	26	52	7.7
104	83	49	54	102	12.6
105	79	39	39	78	7.85
49	52	61	16	78	10.95
88	105	19	36	55	12.35
95	116	67	31	98	9.95
102	83	45	31	76	14.9
99	196	30	42	73	16.65
63	153	8	39	47	13.4
76	157	19	25	45	13.95
109	75	52	31	83	15.7
117	106	22	38	60	16.85
57	58	17	31	48	10.95
120	75	33	17	50	15.35
73	74	34	22	56	12.2
91	185	22	55	77	15.1
108	265	30	62	91	17.75
105	131	25	51	76	15.2
117	139	38	30	68	14.6
119	196	26	49	74	16.65
31	78	13	16	29	8.1

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'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268645&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268645&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268645&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'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
EX[t] = + 8.27556 + 0.0104138LFM[t] + 0.0291282B[t] -0.330203PRH[t] -0.350336CH[t] + 0.335664H[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
EX[t] =  +  8.27556 +  0.0104138LFM[t] +  0.0291282B[t] -0.330203PRH[t] -0.350336CH[t] +  0.335664H[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268645&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]EX[t] =  +  8.27556 +  0.0104138LFM[t] +  0.0291282B[t] -0.330203PRH[t] -0.350336CH[t] +  0.335664H[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268645&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268645&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] = + 8.27556 + 0.0104138LFM[t] + 0.0291282B[t] -0.330203PRH[t] -0.350336CH[t] + 0.335664H[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.275560.54989915.056.52148e-383.26074e-38
LFM0.01041380.004834982.1540.03210530.0160527
B0.02912820.002915559.9912.66886e-201.33443e-20
PRH-0.3302030.448508-0.73620.462210.231105
CH-0.3503360.447878-0.78220.434750.217375
H0.3356640.4477190.74970.4540530.227026

\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) & 8.27556 & 0.549899 & 15.05 & 6.52148e-38 & 3.26074e-38 \tabularnewline
LFM & 0.0104138 & 0.00483498 & 2.154 & 0.0321053 & 0.0160527 \tabularnewline
B & 0.0291282 & 0.00291555 & 9.991 & 2.66886e-20 & 1.33443e-20 \tabularnewline
PRH & -0.330203 & 0.448508 & -0.7362 & 0.46221 & 0.231105 \tabularnewline
CH & -0.350336 & 0.447878 & -0.7822 & 0.43475 & 0.217375 \tabularnewline
H & 0.335664 & 0.447719 & 0.7497 & 0.454053 & 0.227026 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268645&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]8.27556[/C][C]0.549899[/C][C]15.05[/C][C]6.52148e-38[/C][C]3.26074e-38[/C][/ROW]
[ROW][C]LFM[/C][C]0.0104138[/C][C]0.00483498[/C][C]2.154[/C][C]0.0321053[/C][C]0.0160527[/C][/ROW]
[ROW][C]B[/C][C]0.0291282[/C][C]0.00291555[/C][C]9.991[/C][C]2.66886e-20[/C][C]1.33443e-20[/C][/ROW]
[ROW][C]PRH[/C][C]-0.330203[/C][C]0.448508[/C][C]-0.7362[/C][C]0.46221[/C][C]0.231105[/C][/ROW]
[ROW][C]CH[/C][C]-0.350336[/C][C]0.447878[/C][C]-0.7822[/C][C]0.43475[/C][C]0.217375[/C][/ROW]
[ROW][C]H[/C][C]0.335664[/C][C]0.447719[/C][C]0.7497[/C][C]0.454053[/C][C]0.227026[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268645&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268645&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)8.275560.54989915.056.52148e-383.26074e-38
LFM0.01041380.004834982.1540.03210530.0160527
B0.02912820.002915559.9912.66886e-201.33443e-20
PRH-0.3302030.448508-0.73620.462210.231105
CH-0.3503360.447878-0.78220.434750.217375
H0.3356640.4477190.74970.4540530.227026






Multiple Linear Regression - Regression Statistics
Multiple R0.603467
R-squared0.364172
Adjusted R-squared0.352818
F-TEST (value)32.0741
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.75233
Sum Squared Residuals2121.08

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.603467 \tabularnewline
R-squared & 0.364172 \tabularnewline
Adjusted R-squared & 0.352818 \tabularnewline
F-TEST (value) & 32.0741 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 280 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.75233 \tabularnewline
Sum Squared Residuals & 2121.08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268645&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.603467[/C][/ROW]
[ROW][C]R-squared[/C][C]0.364172[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.352818[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]32.0741[/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]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.75233[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2121.08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268645&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268645&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 R0.603467
R-squared0.364172
Adjusted R-squared0.352818
F-TEST (value)32.0741
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.75233
Sum Squared Residuals2121.08






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.72411.17591
27.411.2743-3.87431
312.211.35910.840879
412.812.12360.67645
57.412.5831-5.18307
66.711.3035-4.60348
712.615.3377-2.73774
814.812.53342.26659
913.312.04771.25228
1011.112.4409-1.34085
118.214.2174-6.01741
1211.412.8432-1.44318
136.414.4758-8.07579
1410.611.525-0.925024
151213.4478-1.44783
166.39.6933-3.3933
1711.311.24060.059386
1811.913.727-1.82701
199.312.0754-2.77537
209.612.1991-2.59907
211011.4477-1.44774
226.411.7271-5.32715
2313.813.00360.796407
2410.813.2393-2.43928
2513.812.04091.75909
2611.712.5539-0.853933
2710.914.9137-4.01374
2816.113.22882.87117
2913.410.99132.40868
309.910.9743-1.07429
3111.512.0964-0.596367
328.311.7636-3.46359
3311.713.3184-1.61844
346.111.5022-5.40224
35912.2862-3.28623
369.714.396-4.69595
3710.812.483-1.68298
3810.312.8305-2.5305
3910.411.6061-1.20607
4012.712.7598-0.0597616
419.312.1489-2.84894
4211.814.2612-2.46125
435.910.5332-4.63317
4411.413.9466-2.54664
451311.60611.39389
4610.812.4745-1.67453
4712.310.32271.97734
4811.313.3947-2.09473
4911.812.3794-0.579405
507.911.0269-3.12692
5112.79.838742.86126
5212.310.84611.45388
5311.611.9409-0.34087
546.710.9968-4.29679
5510.913.1505-2.25054
5612.112.6283-0.528347
5713.313.4901-0.19013
5810.113.3483-3.24834
595.711.6699-5.96994
6014.312.11672.18325
6189.47516-1.47516
6213.311.62981.67022
639.312.5351-3.23513
6412.511.66470.835261
657.610.653-3.053
6615.913.72382.17624
679.211.3063-2.10628
689.110.4967-1.39666
6911.114.0428-2.9428
701313.3151-0.315053
7114.512.92651.57352
7212.210.95321.2468
7312.313.4333-1.13332
7411.411.27220.127839
758.811.145-2.34501
7614.610.94773.65233
777.312.2606-4.96061
7812.612.8926-0.292618
79NANA-0.584463
801311.62151.37854
8112.614.0125-1.41255
8213.214.4913-1.29134
839.913.5234-3.62343
847.77.72581-0.0258115
8510.57.612642.88736
8613.414.2232-0.823241
8710.916.5748-5.67478
884.34.90228-0.602278
8910.39.909620.390378
9011.811.15610.643873
9111.210.63720.562799
9211.412.8358-1.43576
938.66.307592.29241
9413.210.83532.36475
9512.618.0219-5.42191
965.66.78531-1.18531
979.912.9912-3.09119
988.812.7823-3.98234
997.79.00707-1.30707
100913.9002-4.90019
1017.36.869240.430758
10211.49.178132.22187
10313.616.2895-2.68946
1047.98.0449-0.144904
10510.712.0007-1.30072
10610.312.1895-1.88952
1078.39.52097-1.22097
1089.67.015762.58424
10914.215.9897-1.78973
1108.55.579152.92085
11113.519.2036-5.70362
1124.98.61089-3.71089
1136.47.03436-0.634361
1149.68.724840.875162
11511.610.76770.832271
11611.116.3336-5.23355
1174.354.126080.223922
11812.79.37633.3237
11918.115.35382.74623
12017.8516.93880.911199
12116.613.59733.00275
12212.617.8694-5.26935
12317.113.50753.59246
12419.121.1591-2.05909
12516.113.36262.73741
12613.3512.61320.7368
12718.414.67923.72084
12814.718.9181-4.21814
12910.611.7413-1.14135
13012.611.49741.10264
13116.220.0526-3.85255
13213.610.8272.77297
13318.917.16171.73832
13414.111.41462.68541
13514.516.4603-1.96029
13616.1514.54841.60159
13714.7514.11320.636759
13814.814.60410.19588
13912.4514.5192-2.06925
14012.659.061423.58858
14117.3520.7422-3.39224
1428.67.800080.799923
14318.420.3862-1.98624
14416.115.19750.902453
14511.65.563936.03607
14617.7516.04831.70174
14715.2513.84791.40208
14817.6515.80541.84455
14915.613.8991.70102
15016.3513.41922.93085
15117.6516.96470.685267
15213.614.0535-0.45351
15311.710.7410.959019
15414.3517.695-3.34498
15514.7512.91661.83338
15618.2523.5227-5.2727
1579.97.751452.14855
1581613.45512.54488
15918.2518.7914-0.54144
16016.8514.73552.11453
16114.614.35560.244409
16213.8511.05382.79616
16318.9517.91911.03093
16415.618.0197-2.41975
16514.8515.7949-0.944898
16611.755.875065.87494
16718.4520.0212-1.57125
16815.913.06022.83979
16917.111.73345.36662
17016.110.76775.33228
17119.919.68450.21546
17210.958.184922.76508
17318.4513.82774.62234
17415.115.6113-0.51132
1751517.5813-2.58127
17611.3510.41540.934616
17715.9510.9954.95496
17818.116.16191.93811
17914.615.0138-0.413811
18015.415.8138-0.413811
18115.411.1824.218
18217.617.943-0.342979
18313.3510.93492.41507
18419.116.59162.50839
18515.3519.9708-4.62078
1867.67.89542-0.29542
18713.413.26840.131589
18813.911.9561.94399
18919.117.50451.59551
19015.2514.2341.01602
19112.910.48242.41762
19216.110.96245.13763
19317.3516.38270.967295
19413.1510.82432.32573
19512.1512.02310.126943
19612.613.647-1.04701
19710.357.715942.63406
19815.416.5414-1.14142
1999.64.535635.06437
20018.216.58851.61152
20113.613.330.26999
20214.8517.0819-2.2319
20314.7514.7911-0.0410933
20414.110.7913.30896
20514.911.25773.64235
20616.2514.56791.68213
20719.2517.50681.74323
20813.613.18080.419238
20913.613.11610.483908
21015.6515.4070.243039
21112.759.209123.54088
21214.618.0089-3.40885
2139.858.159031.69097
21412.6513.1732-0.523237
21511.99.008942.89106
21619.217.0522.14795
21716.615.0921.508
21811.29.308881.89112
21915.2518.4478-3.19779
22011.914.948-3.04799
22113.214.0129-0.812937
22216.3517.2905-0.940506
22312.49.355933.04407
22415.8515.08170.768263
22514.3511.1863.164
22618.1518.2607-0.110703
22711.1511.3525-0.20253
22815.6514.26581.38416
22917.7522.4889-4.7389
2307.657.500270.149729
23112.358.196234.15377
23215.612.58263.01739
23319.315.82523.47475
23415.211.4943.70599
23517.114.44792.65205
23615.611.96813.63191
23718.414.46673.9333
23819.0513.74865.30138
23918.5516.52252.02747
24019.117.67041.4296
24113.113.4127-0.312739
24212.8514.7776-1.92758
2439.516.1367-6.63667
2444.53.096951.40305
24511.8514.1694-2.31942
24613.615.1708-1.57077
24711.710.62411.07591
24812.413.8184-1.41835
24913.3515.7325-2.38248
25011.48.046313.35369
25114.99.567725.33228
25219.914.01345.88665
25317.7518.6326-0.88258
25411.212.0266-0.826647
25514.612.80481.79522
25617.616.29791.30208
25714.0513.09090.959078
25816.115.58650.513473
25913.3513.5824-0.232356
26011.8514.1242-2.27419
26111.9511.75210.197933
26214.7512.4992.25099
26315.1515.555-0.404954
26413.212.04251.15752
26516.8519.019-2.169
2667.8515.1939-7.34387
2677.76.015851.68415
26812.616.0609-3.46089
2697.857.634540.21546
27010.9510.4260.524015
27112.3514.9548-2.60479
2729.956.596313.35369
27314.913.14891.7511
27416.6516.10970.5403
27513.413.16270.237254
27613.959.674414.27559
27715.710.99424.70585
27816.8516.09660.753427
27910.957.240623.70938
28015.3514.20411.14586
28112.211.02511.17492
28215.113.38771.71231
28317.7515.1232.62697
28415.213.91011.28986
28514.612.26132.3387
28616.6519.2566-2.60662
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 11.7241 & 1.17591 \tabularnewline
2 & 7.4 & 11.2743 & -3.87431 \tabularnewline
3 & 12.2 & 11.3591 & 0.840879 \tabularnewline
4 & 12.8 & 12.1236 & 0.67645 \tabularnewline
5 & 7.4 & 12.5831 & -5.18307 \tabularnewline
6 & 6.7 & 11.3035 & -4.60348 \tabularnewline
7 & 12.6 & 15.3377 & -2.73774 \tabularnewline
8 & 14.8 & 12.5334 & 2.26659 \tabularnewline
9 & 13.3 & 12.0477 & 1.25228 \tabularnewline
10 & 11.1 & 12.4409 & -1.34085 \tabularnewline
11 & 8.2 & 14.2174 & -6.01741 \tabularnewline
12 & 11.4 & 12.8432 & -1.44318 \tabularnewline
13 & 6.4 & 14.4758 & -8.07579 \tabularnewline
14 & 10.6 & 11.525 & -0.925024 \tabularnewline
15 & 12 & 13.4478 & -1.44783 \tabularnewline
16 & 6.3 & 9.6933 & -3.3933 \tabularnewline
17 & 11.3 & 11.2406 & 0.059386 \tabularnewline
18 & 11.9 & 13.727 & -1.82701 \tabularnewline
19 & 9.3 & 12.0754 & -2.77537 \tabularnewline
20 & 9.6 & 12.1991 & -2.59907 \tabularnewline
21 & 10 & 11.4477 & -1.44774 \tabularnewline
22 & 6.4 & 11.7271 & -5.32715 \tabularnewline
23 & 13.8 & 13.0036 & 0.796407 \tabularnewline
24 & 10.8 & 13.2393 & -2.43928 \tabularnewline
25 & 13.8 & 12.0409 & 1.75909 \tabularnewline
26 & 11.7 & 12.5539 & -0.853933 \tabularnewline
27 & 10.9 & 14.9137 & -4.01374 \tabularnewline
28 & 16.1 & 13.2288 & 2.87117 \tabularnewline
29 & 13.4 & 10.9913 & 2.40868 \tabularnewline
30 & 9.9 & 10.9743 & -1.07429 \tabularnewline
31 & 11.5 & 12.0964 & -0.596367 \tabularnewline
32 & 8.3 & 11.7636 & -3.46359 \tabularnewline
33 & 11.7 & 13.3184 & -1.61844 \tabularnewline
34 & 6.1 & 11.5022 & -5.40224 \tabularnewline
35 & 9 & 12.2862 & -3.28623 \tabularnewline
36 & 9.7 & 14.396 & -4.69595 \tabularnewline
37 & 10.8 & 12.483 & -1.68298 \tabularnewline
38 & 10.3 & 12.8305 & -2.5305 \tabularnewline
39 & 10.4 & 11.6061 & -1.20607 \tabularnewline
40 & 12.7 & 12.7598 & -0.0597616 \tabularnewline
41 & 9.3 & 12.1489 & -2.84894 \tabularnewline
42 & 11.8 & 14.2612 & -2.46125 \tabularnewline
43 & 5.9 & 10.5332 & -4.63317 \tabularnewline
44 & 11.4 & 13.9466 & -2.54664 \tabularnewline
45 & 13 & 11.6061 & 1.39389 \tabularnewline
46 & 10.8 & 12.4745 & -1.67453 \tabularnewline
47 & 12.3 & 10.3227 & 1.97734 \tabularnewline
48 & 11.3 & 13.3947 & -2.09473 \tabularnewline
49 & 11.8 & 12.3794 & -0.579405 \tabularnewline
50 & 7.9 & 11.0269 & -3.12692 \tabularnewline
51 & 12.7 & 9.83874 & 2.86126 \tabularnewline
52 & 12.3 & 10.8461 & 1.45388 \tabularnewline
53 & 11.6 & 11.9409 & -0.34087 \tabularnewline
54 & 6.7 & 10.9968 & -4.29679 \tabularnewline
55 & 10.9 & 13.1505 & -2.25054 \tabularnewline
56 & 12.1 & 12.6283 & -0.528347 \tabularnewline
57 & 13.3 & 13.4901 & -0.19013 \tabularnewline
58 & 10.1 & 13.3483 & -3.24834 \tabularnewline
59 & 5.7 & 11.6699 & -5.96994 \tabularnewline
60 & 14.3 & 12.1167 & 2.18325 \tabularnewline
61 & 8 & 9.47516 & -1.47516 \tabularnewline
62 & 13.3 & 11.6298 & 1.67022 \tabularnewline
63 & 9.3 & 12.5351 & -3.23513 \tabularnewline
64 & 12.5 & 11.6647 & 0.835261 \tabularnewline
65 & 7.6 & 10.653 & -3.053 \tabularnewline
66 & 15.9 & 13.7238 & 2.17624 \tabularnewline
67 & 9.2 & 11.3063 & -2.10628 \tabularnewline
68 & 9.1 & 10.4967 & -1.39666 \tabularnewline
69 & 11.1 & 14.0428 & -2.9428 \tabularnewline
70 & 13 & 13.3151 & -0.315053 \tabularnewline
71 & 14.5 & 12.9265 & 1.57352 \tabularnewline
72 & 12.2 & 10.9532 & 1.2468 \tabularnewline
73 & 12.3 & 13.4333 & -1.13332 \tabularnewline
74 & 11.4 & 11.2722 & 0.127839 \tabularnewline
75 & 8.8 & 11.145 & -2.34501 \tabularnewline
76 & 14.6 & 10.9477 & 3.65233 \tabularnewline
77 & 7.3 & 12.2606 & -4.96061 \tabularnewline
78 & 12.6 & 12.8926 & -0.292618 \tabularnewline
79 & NA & NA & -0.584463 \tabularnewline
80 & 13 & 11.6215 & 1.37854 \tabularnewline
81 & 12.6 & 14.0125 & -1.41255 \tabularnewline
82 & 13.2 & 14.4913 & -1.29134 \tabularnewline
83 & 9.9 & 13.5234 & -3.62343 \tabularnewline
84 & 7.7 & 7.72581 & -0.0258115 \tabularnewline
85 & 10.5 & 7.61264 & 2.88736 \tabularnewline
86 & 13.4 & 14.2232 & -0.823241 \tabularnewline
87 & 10.9 & 16.5748 & -5.67478 \tabularnewline
88 & 4.3 & 4.90228 & -0.602278 \tabularnewline
89 & 10.3 & 9.90962 & 0.390378 \tabularnewline
90 & 11.8 & 11.1561 & 0.643873 \tabularnewline
91 & 11.2 & 10.6372 & 0.562799 \tabularnewline
92 & 11.4 & 12.8358 & -1.43576 \tabularnewline
93 & 8.6 & 6.30759 & 2.29241 \tabularnewline
94 & 13.2 & 10.8353 & 2.36475 \tabularnewline
95 & 12.6 & 18.0219 & -5.42191 \tabularnewline
96 & 5.6 & 6.78531 & -1.18531 \tabularnewline
97 & 9.9 & 12.9912 & -3.09119 \tabularnewline
98 & 8.8 & 12.7823 & -3.98234 \tabularnewline
99 & 7.7 & 9.00707 & -1.30707 \tabularnewline
100 & 9 & 13.9002 & -4.90019 \tabularnewline
101 & 7.3 & 6.86924 & 0.430758 \tabularnewline
102 & 11.4 & 9.17813 & 2.22187 \tabularnewline
103 & 13.6 & 16.2895 & -2.68946 \tabularnewline
104 & 7.9 & 8.0449 & -0.144904 \tabularnewline
105 & 10.7 & 12.0007 & -1.30072 \tabularnewline
106 & 10.3 & 12.1895 & -1.88952 \tabularnewline
107 & 8.3 & 9.52097 & -1.22097 \tabularnewline
108 & 9.6 & 7.01576 & 2.58424 \tabularnewline
109 & 14.2 & 15.9897 & -1.78973 \tabularnewline
110 & 8.5 & 5.57915 & 2.92085 \tabularnewline
111 & 13.5 & 19.2036 & -5.70362 \tabularnewline
112 & 4.9 & 8.61089 & -3.71089 \tabularnewline
113 & 6.4 & 7.03436 & -0.634361 \tabularnewline
114 & 9.6 & 8.72484 & 0.875162 \tabularnewline
115 & 11.6 & 10.7677 & 0.832271 \tabularnewline
116 & 11.1 & 16.3336 & -5.23355 \tabularnewline
117 & 4.35 & 4.12608 & 0.223922 \tabularnewline
118 & 12.7 & 9.3763 & 3.3237 \tabularnewline
119 & 18.1 & 15.3538 & 2.74623 \tabularnewline
120 & 17.85 & 16.9388 & 0.911199 \tabularnewline
121 & 16.6 & 13.5973 & 3.00275 \tabularnewline
122 & 12.6 & 17.8694 & -5.26935 \tabularnewline
123 & 17.1 & 13.5075 & 3.59246 \tabularnewline
124 & 19.1 & 21.1591 & -2.05909 \tabularnewline
125 & 16.1 & 13.3626 & 2.73741 \tabularnewline
126 & 13.35 & 12.6132 & 0.7368 \tabularnewline
127 & 18.4 & 14.6792 & 3.72084 \tabularnewline
128 & 14.7 & 18.9181 & -4.21814 \tabularnewline
129 & 10.6 & 11.7413 & -1.14135 \tabularnewline
130 & 12.6 & 11.4974 & 1.10264 \tabularnewline
131 & 16.2 & 20.0526 & -3.85255 \tabularnewline
132 & 13.6 & 10.827 & 2.77297 \tabularnewline
133 & 18.9 & 17.1617 & 1.73832 \tabularnewline
134 & 14.1 & 11.4146 & 2.68541 \tabularnewline
135 & 14.5 & 16.4603 & -1.96029 \tabularnewline
136 & 16.15 & 14.5484 & 1.60159 \tabularnewline
137 & 14.75 & 14.1132 & 0.636759 \tabularnewline
138 & 14.8 & 14.6041 & 0.19588 \tabularnewline
139 & 12.45 & 14.5192 & -2.06925 \tabularnewline
140 & 12.65 & 9.06142 & 3.58858 \tabularnewline
141 & 17.35 & 20.7422 & -3.39224 \tabularnewline
142 & 8.6 & 7.80008 & 0.799923 \tabularnewline
143 & 18.4 & 20.3862 & -1.98624 \tabularnewline
144 & 16.1 & 15.1975 & 0.902453 \tabularnewline
145 & 11.6 & 5.56393 & 6.03607 \tabularnewline
146 & 17.75 & 16.0483 & 1.70174 \tabularnewline
147 & 15.25 & 13.8479 & 1.40208 \tabularnewline
148 & 17.65 & 15.8054 & 1.84455 \tabularnewline
149 & 15.6 & 13.899 & 1.70102 \tabularnewline
150 & 16.35 & 13.4192 & 2.93085 \tabularnewline
151 & 17.65 & 16.9647 & 0.685267 \tabularnewline
152 & 13.6 & 14.0535 & -0.45351 \tabularnewline
153 & 11.7 & 10.741 & 0.959019 \tabularnewline
154 & 14.35 & 17.695 & -3.34498 \tabularnewline
155 & 14.75 & 12.9166 & 1.83338 \tabularnewline
156 & 18.25 & 23.5227 & -5.2727 \tabularnewline
157 & 9.9 & 7.75145 & 2.14855 \tabularnewline
158 & 16 & 13.4551 & 2.54488 \tabularnewline
159 & 18.25 & 18.7914 & -0.54144 \tabularnewline
160 & 16.85 & 14.7355 & 2.11453 \tabularnewline
161 & 14.6 & 14.3556 & 0.244409 \tabularnewline
162 & 13.85 & 11.0538 & 2.79616 \tabularnewline
163 & 18.95 & 17.9191 & 1.03093 \tabularnewline
164 & 15.6 & 18.0197 & -2.41975 \tabularnewline
165 & 14.85 & 15.7949 & -0.944898 \tabularnewline
166 & 11.75 & 5.87506 & 5.87494 \tabularnewline
167 & 18.45 & 20.0212 & -1.57125 \tabularnewline
168 & 15.9 & 13.0602 & 2.83979 \tabularnewline
169 & 17.1 & 11.7334 & 5.36662 \tabularnewline
170 & 16.1 & 10.7677 & 5.33228 \tabularnewline
171 & 19.9 & 19.6845 & 0.21546 \tabularnewline
172 & 10.95 & 8.18492 & 2.76508 \tabularnewline
173 & 18.45 & 13.8277 & 4.62234 \tabularnewline
174 & 15.1 & 15.6113 & -0.51132 \tabularnewline
175 & 15 & 17.5813 & -2.58127 \tabularnewline
176 & 11.35 & 10.4154 & 0.934616 \tabularnewline
177 & 15.95 & 10.995 & 4.95496 \tabularnewline
178 & 18.1 & 16.1619 & 1.93811 \tabularnewline
179 & 14.6 & 15.0138 & -0.413811 \tabularnewline
180 & 15.4 & 15.8138 & -0.413811 \tabularnewline
181 & 15.4 & 11.182 & 4.218 \tabularnewline
182 & 17.6 & 17.943 & -0.342979 \tabularnewline
183 & 13.35 & 10.9349 & 2.41507 \tabularnewline
184 & 19.1 & 16.5916 & 2.50839 \tabularnewline
185 & 15.35 & 19.9708 & -4.62078 \tabularnewline
186 & 7.6 & 7.89542 & -0.29542 \tabularnewline
187 & 13.4 & 13.2684 & 0.131589 \tabularnewline
188 & 13.9 & 11.956 & 1.94399 \tabularnewline
189 & 19.1 & 17.5045 & 1.59551 \tabularnewline
190 & 15.25 & 14.234 & 1.01602 \tabularnewline
191 & 12.9 & 10.4824 & 2.41762 \tabularnewline
192 & 16.1 & 10.9624 & 5.13763 \tabularnewline
193 & 17.35 & 16.3827 & 0.967295 \tabularnewline
194 & 13.15 & 10.8243 & 2.32573 \tabularnewline
195 & 12.15 & 12.0231 & 0.126943 \tabularnewline
196 & 12.6 & 13.647 & -1.04701 \tabularnewline
197 & 10.35 & 7.71594 & 2.63406 \tabularnewline
198 & 15.4 & 16.5414 & -1.14142 \tabularnewline
199 & 9.6 & 4.53563 & 5.06437 \tabularnewline
200 & 18.2 & 16.5885 & 1.61152 \tabularnewline
201 & 13.6 & 13.33 & 0.26999 \tabularnewline
202 & 14.85 & 17.0819 & -2.2319 \tabularnewline
203 & 14.75 & 14.7911 & -0.0410933 \tabularnewline
204 & 14.1 & 10.791 & 3.30896 \tabularnewline
205 & 14.9 & 11.2577 & 3.64235 \tabularnewline
206 & 16.25 & 14.5679 & 1.68213 \tabularnewline
207 & 19.25 & 17.5068 & 1.74323 \tabularnewline
208 & 13.6 & 13.1808 & 0.419238 \tabularnewline
209 & 13.6 & 13.1161 & 0.483908 \tabularnewline
210 & 15.65 & 15.407 & 0.243039 \tabularnewline
211 & 12.75 & 9.20912 & 3.54088 \tabularnewline
212 & 14.6 & 18.0089 & -3.40885 \tabularnewline
213 & 9.85 & 8.15903 & 1.69097 \tabularnewline
214 & 12.65 & 13.1732 & -0.523237 \tabularnewline
215 & 11.9 & 9.00894 & 2.89106 \tabularnewline
216 & 19.2 & 17.052 & 2.14795 \tabularnewline
217 & 16.6 & 15.092 & 1.508 \tabularnewline
218 & 11.2 & 9.30888 & 1.89112 \tabularnewline
219 & 15.25 & 18.4478 & -3.19779 \tabularnewline
220 & 11.9 & 14.948 & -3.04799 \tabularnewline
221 & 13.2 & 14.0129 & -0.812937 \tabularnewline
222 & 16.35 & 17.2905 & -0.940506 \tabularnewline
223 & 12.4 & 9.35593 & 3.04407 \tabularnewline
224 & 15.85 & 15.0817 & 0.768263 \tabularnewline
225 & 14.35 & 11.186 & 3.164 \tabularnewline
226 & 18.15 & 18.2607 & -0.110703 \tabularnewline
227 & 11.15 & 11.3525 & -0.20253 \tabularnewline
228 & 15.65 & 14.2658 & 1.38416 \tabularnewline
229 & 17.75 & 22.4889 & -4.7389 \tabularnewline
230 & 7.65 & 7.50027 & 0.149729 \tabularnewline
231 & 12.35 & 8.19623 & 4.15377 \tabularnewline
232 & 15.6 & 12.5826 & 3.01739 \tabularnewline
233 & 19.3 & 15.8252 & 3.47475 \tabularnewline
234 & 15.2 & 11.494 & 3.70599 \tabularnewline
235 & 17.1 & 14.4479 & 2.65205 \tabularnewline
236 & 15.6 & 11.9681 & 3.63191 \tabularnewline
237 & 18.4 & 14.4667 & 3.9333 \tabularnewline
238 & 19.05 & 13.7486 & 5.30138 \tabularnewline
239 & 18.55 & 16.5225 & 2.02747 \tabularnewline
240 & 19.1 & 17.6704 & 1.4296 \tabularnewline
241 & 13.1 & 13.4127 & -0.312739 \tabularnewline
242 & 12.85 & 14.7776 & -1.92758 \tabularnewline
243 & 9.5 & 16.1367 & -6.63667 \tabularnewline
244 & 4.5 & 3.09695 & 1.40305 \tabularnewline
245 & 11.85 & 14.1694 & -2.31942 \tabularnewline
246 & 13.6 & 15.1708 & -1.57077 \tabularnewline
247 & 11.7 & 10.6241 & 1.07591 \tabularnewline
248 & 12.4 & 13.8184 & -1.41835 \tabularnewline
249 & 13.35 & 15.7325 & -2.38248 \tabularnewline
250 & 11.4 & 8.04631 & 3.35369 \tabularnewline
251 & 14.9 & 9.56772 & 5.33228 \tabularnewline
252 & 19.9 & 14.0134 & 5.88665 \tabularnewline
253 & 17.75 & 18.6326 & -0.88258 \tabularnewline
254 & 11.2 & 12.0266 & -0.826647 \tabularnewline
255 & 14.6 & 12.8048 & 1.79522 \tabularnewline
256 & 17.6 & 16.2979 & 1.30208 \tabularnewline
257 & 14.05 & 13.0909 & 0.959078 \tabularnewline
258 & 16.1 & 15.5865 & 0.513473 \tabularnewline
259 & 13.35 & 13.5824 & -0.232356 \tabularnewline
260 & 11.85 & 14.1242 & -2.27419 \tabularnewline
261 & 11.95 & 11.7521 & 0.197933 \tabularnewline
262 & 14.75 & 12.499 & 2.25099 \tabularnewline
263 & 15.15 & 15.555 & -0.404954 \tabularnewline
264 & 13.2 & 12.0425 & 1.15752 \tabularnewline
265 & 16.85 & 19.019 & -2.169 \tabularnewline
266 & 7.85 & 15.1939 & -7.34387 \tabularnewline
267 & 7.7 & 6.01585 & 1.68415 \tabularnewline
268 & 12.6 & 16.0609 & -3.46089 \tabularnewline
269 & 7.85 & 7.63454 & 0.21546 \tabularnewline
270 & 10.95 & 10.426 & 0.524015 \tabularnewline
271 & 12.35 & 14.9548 & -2.60479 \tabularnewline
272 & 9.95 & 6.59631 & 3.35369 \tabularnewline
273 & 14.9 & 13.1489 & 1.7511 \tabularnewline
274 & 16.65 & 16.1097 & 0.5403 \tabularnewline
275 & 13.4 & 13.1627 & 0.237254 \tabularnewline
276 & 13.95 & 9.67441 & 4.27559 \tabularnewline
277 & 15.7 & 10.9942 & 4.70585 \tabularnewline
278 & 16.85 & 16.0966 & 0.753427 \tabularnewline
279 & 10.95 & 7.24062 & 3.70938 \tabularnewline
280 & 15.35 & 14.2041 & 1.14586 \tabularnewline
281 & 12.2 & 11.0251 & 1.17492 \tabularnewline
282 & 15.1 & 13.3877 & 1.71231 \tabularnewline
283 & 17.75 & 15.123 & 2.62697 \tabularnewline
284 & 15.2 & 13.9101 & 1.28986 \tabularnewline
285 & 14.6 & 12.2613 & 2.3387 \tabularnewline
286 & 16.65 & 19.2566 & -2.60662 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268645&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]12.9[/C][C]11.7241[/C][C]1.17591[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]11.2743[/C][C]-3.87431[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]11.3591[/C][C]0.840879[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]12.1236[/C][C]0.67645[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]12.5831[/C][C]-5.18307[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]11.3035[/C][C]-4.60348[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]15.3377[/C][C]-2.73774[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]12.5334[/C][C]2.26659[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]12.0477[/C][C]1.25228[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]12.4409[/C][C]-1.34085[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]14.2174[/C][C]-6.01741[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]12.8432[/C][C]-1.44318[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]14.4758[/C][C]-8.07579[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]11.525[/C][C]-0.925024[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]13.4478[/C][C]-1.44783[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]9.6933[/C][C]-3.3933[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]11.2406[/C][C]0.059386[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]13.727[/C][C]-1.82701[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]12.0754[/C][C]-2.77537[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]12.1991[/C][C]-2.59907[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]11.4477[/C][C]-1.44774[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]11.7271[/C][C]-5.32715[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]13.0036[/C][C]0.796407[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]13.2393[/C][C]-2.43928[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]12.0409[/C][C]1.75909[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]12.5539[/C][C]-0.853933[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]14.9137[/C][C]-4.01374[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]13.2288[/C][C]2.87117[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]10.9913[/C][C]2.40868[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]10.9743[/C][C]-1.07429[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.0964[/C][C]-0.596367[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]11.7636[/C][C]-3.46359[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]13.3184[/C][C]-1.61844[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]11.5022[/C][C]-5.40224[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]12.2862[/C][C]-3.28623[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]14.396[/C][C]-4.69595[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]12.483[/C][C]-1.68298[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]12.8305[/C][C]-2.5305[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]11.6061[/C][C]-1.20607[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]12.7598[/C][C]-0.0597616[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]12.1489[/C][C]-2.84894[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]14.2612[/C][C]-2.46125[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]10.5332[/C][C]-4.63317[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]13.9466[/C][C]-2.54664[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]11.6061[/C][C]1.39389[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]12.4745[/C][C]-1.67453[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]10.3227[/C][C]1.97734[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]13.3947[/C][C]-2.09473[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]12.3794[/C][C]-0.579405[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]11.0269[/C][C]-3.12692[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]9.83874[/C][C]2.86126[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]10.8461[/C][C]1.45388[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]11.9409[/C][C]-0.34087[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]10.9968[/C][C]-4.29679[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]13.1505[/C][C]-2.25054[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]12.6283[/C][C]-0.528347[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.4901[/C][C]-0.19013[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]13.3483[/C][C]-3.24834[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]11.6699[/C][C]-5.96994[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]12.1167[/C][C]2.18325[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]9.47516[/C][C]-1.47516[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]11.6298[/C][C]1.67022[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]12.5351[/C][C]-3.23513[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]11.6647[/C][C]0.835261[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]10.653[/C][C]-3.053[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]13.7238[/C][C]2.17624[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]11.3063[/C][C]-2.10628[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]10.4967[/C][C]-1.39666[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]14.0428[/C][C]-2.9428[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]13.3151[/C][C]-0.315053[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]12.9265[/C][C]1.57352[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]10.9532[/C][C]1.2468[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]13.4333[/C][C]-1.13332[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]11.2722[/C][C]0.127839[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]11.145[/C][C]-2.34501[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]10.9477[/C][C]3.65233[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]12.2606[/C][C]-4.96061[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.8926[/C][C]-0.292618[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]-0.584463[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]11.6215[/C][C]1.37854[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]14.0125[/C][C]-1.41255[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]14.4913[/C][C]-1.29134[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]13.5234[/C][C]-3.62343[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]7.72581[/C][C]-0.0258115[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]7.61264[/C][C]2.88736[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]14.2232[/C][C]-0.823241[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]16.5748[/C][C]-5.67478[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]4.90228[/C][C]-0.602278[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]9.90962[/C][C]0.390378[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]11.1561[/C][C]0.643873[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]10.6372[/C][C]0.562799[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]12.8358[/C][C]-1.43576[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]6.30759[/C][C]2.29241[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]10.8353[/C][C]2.36475[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]18.0219[/C][C]-5.42191[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]6.78531[/C][C]-1.18531[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]12.9912[/C][C]-3.09119[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]12.7823[/C][C]-3.98234[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]9.00707[/C][C]-1.30707[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]13.9002[/C][C]-4.90019[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]6.86924[/C][C]0.430758[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]9.17813[/C][C]2.22187[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]16.2895[/C][C]-2.68946[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]8.0449[/C][C]-0.144904[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]12.0007[/C][C]-1.30072[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]12.1895[/C][C]-1.88952[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]9.52097[/C][C]-1.22097[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]7.01576[/C][C]2.58424[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]15.9897[/C][C]-1.78973[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]5.57915[/C][C]2.92085[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]19.2036[/C][C]-5.70362[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]8.61089[/C][C]-3.71089[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]7.03436[/C][C]-0.634361[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]8.72484[/C][C]0.875162[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]10.7677[/C][C]0.832271[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]16.3336[/C][C]-5.23355[/C][/ROW]
[ROW][C]117[/C][C]4.35[/C][C]4.12608[/C][C]0.223922[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]9.3763[/C][C]3.3237[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]15.3538[/C][C]2.74623[/C][/ROW]
[ROW][C]120[/C][C]17.85[/C][C]16.9388[/C][C]0.911199[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]13.5973[/C][C]3.00275[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]17.8694[/C][C]-5.26935[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]13.5075[/C][C]3.59246[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]21.1591[/C][C]-2.05909[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]13.3626[/C][C]2.73741[/C][/ROW]
[ROW][C]126[/C][C]13.35[/C][C]12.6132[/C][C]0.7368[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]14.6792[/C][C]3.72084[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]18.9181[/C][C]-4.21814[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]11.7413[/C][C]-1.14135[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]11.4974[/C][C]1.10264[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]20.0526[/C][C]-3.85255[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]10.827[/C][C]2.77297[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]17.1617[/C][C]1.73832[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]11.4146[/C][C]2.68541[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]16.4603[/C][C]-1.96029[/C][/ROW]
[ROW][C]136[/C][C]16.15[/C][C]14.5484[/C][C]1.60159[/C][/ROW]
[ROW][C]137[/C][C]14.75[/C][C]14.1132[/C][C]0.636759[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]14.6041[/C][C]0.19588[/C][/ROW]
[ROW][C]139[/C][C]12.45[/C][C]14.5192[/C][C]-2.06925[/C][/ROW]
[ROW][C]140[/C][C]12.65[/C][C]9.06142[/C][C]3.58858[/C][/ROW]
[ROW][C]141[/C][C]17.35[/C][C]20.7422[/C][C]-3.39224[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]7.80008[/C][C]0.799923[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]20.3862[/C][C]-1.98624[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]15.1975[/C][C]0.902453[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]5.56393[/C][C]6.03607[/C][/ROW]
[ROW][C]146[/C][C]17.75[/C][C]16.0483[/C][C]1.70174[/C][/ROW]
[ROW][C]147[/C][C]15.25[/C][C]13.8479[/C][C]1.40208[/C][/ROW]
[ROW][C]148[/C][C]17.65[/C][C]15.8054[/C][C]1.84455[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]13.899[/C][C]1.70102[/C][/ROW]
[ROW][C]150[/C][C]16.35[/C][C]13.4192[/C][C]2.93085[/C][/ROW]
[ROW][C]151[/C][C]17.65[/C][C]16.9647[/C][C]0.685267[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]14.0535[/C][C]-0.45351[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]10.741[/C][C]0.959019[/C][/ROW]
[ROW][C]154[/C][C]14.35[/C][C]17.695[/C][C]-3.34498[/C][/ROW]
[ROW][C]155[/C][C]14.75[/C][C]12.9166[/C][C]1.83338[/C][/ROW]
[ROW][C]156[/C][C]18.25[/C][C]23.5227[/C][C]-5.2727[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]7.75145[/C][C]2.14855[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]13.4551[/C][C]2.54488[/C][/ROW]
[ROW][C]159[/C][C]18.25[/C][C]18.7914[/C][C]-0.54144[/C][/ROW]
[ROW][C]160[/C][C]16.85[/C][C]14.7355[/C][C]2.11453[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]14.3556[/C][C]0.244409[/C][/ROW]
[ROW][C]162[/C][C]13.85[/C][C]11.0538[/C][C]2.79616[/C][/ROW]
[ROW][C]163[/C][C]18.95[/C][C]17.9191[/C][C]1.03093[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]18.0197[/C][C]-2.41975[/C][/ROW]
[ROW][C]165[/C][C]14.85[/C][C]15.7949[/C][C]-0.944898[/C][/ROW]
[ROW][C]166[/C][C]11.75[/C][C]5.87506[/C][C]5.87494[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]20.0212[/C][C]-1.57125[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]13.0602[/C][C]2.83979[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]11.7334[/C][C]5.36662[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]10.7677[/C][C]5.33228[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]19.6845[/C][C]0.21546[/C][/ROW]
[ROW][C]172[/C][C]10.95[/C][C]8.18492[/C][C]2.76508[/C][/ROW]
[ROW][C]173[/C][C]18.45[/C][C]13.8277[/C][C]4.62234[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]15.6113[/C][C]-0.51132[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]17.5813[/C][C]-2.58127[/C][/ROW]
[ROW][C]176[/C][C]11.35[/C][C]10.4154[/C][C]0.934616[/C][/ROW]
[ROW][C]177[/C][C]15.95[/C][C]10.995[/C][C]4.95496[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]16.1619[/C][C]1.93811[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]15.0138[/C][C]-0.413811[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]15.8138[/C][C]-0.413811[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]11.182[/C][C]4.218[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]17.943[/C][C]-0.342979[/C][/ROW]
[ROW][C]183[/C][C]13.35[/C][C]10.9349[/C][C]2.41507[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.5916[/C][C]2.50839[/C][/ROW]
[ROW][C]185[/C][C]15.35[/C][C]19.9708[/C][C]-4.62078[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]7.89542[/C][C]-0.29542[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]13.2684[/C][C]0.131589[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]11.956[/C][C]1.94399[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]17.5045[/C][C]1.59551[/C][/ROW]
[ROW][C]190[/C][C]15.25[/C][C]14.234[/C][C]1.01602[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]10.4824[/C][C]2.41762[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]10.9624[/C][C]5.13763[/C][/ROW]
[ROW][C]193[/C][C]17.35[/C][C]16.3827[/C][C]0.967295[/C][/ROW]
[ROW][C]194[/C][C]13.15[/C][C]10.8243[/C][C]2.32573[/C][/ROW]
[ROW][C]195[/C][C]12.15[/C][C]12.0231[/C][C]0.126943[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]13.647[/C][C]-1.04701[/C][/ROW]
[ROW][C]197[/C][C]10.35[/C][C]7.71594[/C][C]2.63406[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]16.5414[/C][C]-1.14142[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]4.53563[/C][C]5.06437[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]16.5885[/C][C]1.61152[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]13.33[/C][C]0.26999[/C][/ROW]
[ROW][C]202[/C][C]14.85[/C][C]17.0819[/C][C]-2.2319[/C][/ROW]
[ROW][C]203[/C][C]14.75[/C][C]14.7911[/C][C]-0.0410933[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]10.791[/C][C]3.30896[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]11.2577[/C][C]3.64235[/C][/ROW]
[ROW][C]206[/C][C]16.25[/C][C]14.5679[/C][C]1.68213[/C][/ROW]
[ROW][C]207[/C][C]19.25[/C][C]17.5068[/C][C]1.74323[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]13.1808[/C][C]0.419238[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]13.1161[/C][C]0.483908[/C][/ROW]
[ROW][C]210[/C][C]15.65[/C][C]15.407[/C][C]0.243039[/C][/ROW]
[ROW][C]211[/C][C]12.75[/C][C]9.20912[/C][C]3.54088[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]18.0089[/C][C]-3.40885[/C][/ROW]
[ROW][C]213[/C][C]9.85[/C][C]8.15903[/C][C]1.69097[/C][/ROW]
[ROW][C]214[/C][C]12.65[/C][C]13.1732[/C][C]-0.523237[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]9.00894[/C][C]2.89106[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]17.052[/C][C]2.14795[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]15.092[/C][C]1.508[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]9.30888[/C][C]1.89112[/C][/ROW]
[ROW][C]219[/C][C]15.25[/C][C]18.4478[/C][C]-3.19779[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]14.948[/C][C]-3.04799[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]14.0129[/C][C]-0.812937[/C][/ROW]
[ROW][C]222[/C][C]16.35[/C][C]17.2905[/C][C]-0.940506[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]9.35593[/C][C]3.04407[/C][/ROW]
[ROW][C]224[/C][C]15.85[/C][C]15.0817[/C][C]0.768263[/C][/ROW]
[ROW][C]225[/C][C]14.35[/C][C]11.186[/C][C]3.164[/C][/ROW]
[ROW][C]226[/C][C]18.15[/C][C]18.2607[/C][C]-0.110703[/C][/ROW]
[ROW][C]227[/C][C]11.15[/C][C]11.3525[/C][C]-0.20253[/C][/ROW]
[ROW][C]228[/C][C]15.65[/C][C]14.2658[/C][C]1.38416[/C][/ROW]
[ROW][C]229[/C][C]17.75[/C][C]22.4889[/C][C]-4.7389[/C][/ROW]
[ROW][C]230[/C][C]7.65[/C][C]7.50027[/C][C]0.149729[/C][/ROW]
[ROW][C]231[/C][C]12.35[/C][C]8.19623[/C][C]4.15377[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]12.5826[/C][C]3.01739[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]15.8252[/C][C]3.47475[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]11.494[/C][C]3.70599[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]14.4479[/C][C]2.65205[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]11.9681[/C][C]3.63191[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]14.4667[/C][C]3.9333[/C][/ROW]
[ROW][C]238[/C][C]19.05[/C][C]13.7486[/C][C]5.30138[/C][/ROW]
[ROW][C]239[/C][C]18.55[/C][C]16.5225[/C][C]2.02747[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]17.6704[/C][C]1.4296[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]13.4127[/C][C]-0.312739[/C][/ROW]
[ROW][C]242[/C][C]12.85[/C][C]14.7776[/C][C]-1.92758[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]16.1367[/C][C]-6.63667[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]3.09695[/C][C]1.40305[/C][/ROW]
[ROW][C]245[/C][C]11.85[/C][C]14.1694[/C][C]-2.31942[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]15.1708[/C][C]-1.57077[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]10.6241[/C][C]1.07591[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]13.8184[/C][C]-1.41835[/C][/ROW]
[ROW][C]249[/C][C]13.35[/C][C]15.7325[/C][C]-2.38248[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]8.04631[/C][C]3.35369[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]9.56772[/C][C]5.33228[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]14.0134[/C][C]5.88665[/C][/ROW]
[ROW][C]253[/C][C]17.75[/C][C]18.6326[/C][C]-0.88258[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]12.0266[/C][C]-0.826647[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]12.8048[/C][C]1.79522[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]16.2979[/C][C]1.30208[/C][/ROW]
[ROW][C]257[/C][C]14.05[/C][C]13.0909[/C][C]0.959078[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]15.5865[/C][C]0.513473[/C][/ROW]
[ROW][C]259[/C][C]13.35[/C][C]13.5824[/C][C]-0.232356[/C][/ROW]
[ROW][C]260[/C][C]11.85[/C][C]14.1242[/C][C]-2.27419[/C][/ROW]
[ROW][C]261[/C][C]11.95[/C][C]11.7521[/C][C]0.197933[/C][/ROW]
[ROW][C]262[/C][C]14.75[/C][C]12.499[/C][C]2.25099[/C][/ROW]
[ROW][C]263[/C][C]15.15[/C][C]15.555[/C][C]-0.404954[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]12.0425[/C][C]1.15752[/C][/ROW]
[ROW][C]265[/C][C]16.85[/C][C]19.019[/C][C]-2.169[/C][/ROW]
[ROW][C]266[/C][C]7.85[/C][C]15.1939[/C][C]-7.34387[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]6.01585[/C][C]1.68415[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]16.0609[/C][C]-3.46089[/C][/ROW]
[ROW][C]269[/C][C]7.85[/C][C]7.63454[/C][C]0.21546[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.426[/C][C]0.524015[/C][/ROW]
[ROW][C]271[/C][C]12.35[/C][C]14.9548[/C][C]-2.60479[/C][/ROW]
[ROW][C]272[/C][C]9.95[/C][C]6.59631[/C][C]3.35369[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]13.1489[/C][C]1.7511[/C][/ROW]
[ROW][C]274[/C][C]16.65[/C][C]16.1097[/C][C]0.5403[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]13.1627[/C][C]0.237254[/C][/ROW]
[ROW][C]276[/C][C]13.95[/C][C]9.67441[/C][C]4.27559[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]10.9942[/C][C]4.70585[/C][/ROW]
[ROW][C]278[/C][C]16.85[/C][C]16.0966[/C][C]0.753427[/C][/ROW]
[ROW][C]279[/C][C]10.95[/C][C]7.24062[/C][C]3.70938[/C][/ROW]
[ROW][C]280[/C][C]15.35[/C][C]14.2041[/C][C]1.14586[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]11.0251[/C][C]1.17492[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]13.3877[/C][C]1.71231[/C][/ROW]
[ROW][C]283[/C][C]17.75[/C][C]15.123[/C][C]2.62697[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]13.9101[/C][C]1.28986[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]12.2613[/C][C]2.3387[/C][/ROW]
[ROW][C]286[/C][C]16.65[/C][C]19.2566[/C][C]-2.60662[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268645&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268645&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
112.911.72411.17591
27.411.2743-3.87431
312.211.35910.840879
412.812.12360.67645
57.412.5831-5.18307
66.711.3035-4.60348
712.615.3377-2.73774
814.812.53342.26659
913.312.04771.25228
1011.112.4409-1.34085
118.214.2174-6.01741
1211.412.8432-1.44318
136.414.4758-8.07579
1410.611.525-0.925024
151213.4478-1.44783
166.39.6933-3.3933
1711.311.24060.059386
1811.913.727-1.82701
199.312.0754-2.77537
209.612.1991-2.59907
211011.4477-1.44774
226.411.7271-5.32715
2313.813.00360.796407
2410.813.2393-2.43928
2513.812.04091.75909
2611.712.5539-0.853933
2710.914.9137-4.01374
2816.113.22882.87117
2913.410.99132.40868
309.910.9743-1.07429
3111.512.0964-0.596367
328.311.7636-3.46359
3311.713.3184-1.61844
346.111.5022-5.40224
35912.2862-3.28623
369.714.396-4.69595
3710.812.483-1.68298
3810.312.8305-2.5305
3910.411.6061-1.20607
4012.712.7598-0.0597616
419.312.1489-2.84894
4211.814.2612-2.46125
435.910.5332-4.63317
4411.413.9466-2.54664
451311.60611.39389
4610.812.4745-1.67453
4712.310.32271.97734
4811.313.3947-2.09473
4911.812.3794-0.579405
507.911.0269-3.12692
5112.79.838742.86126
5212.310.84611.45388
5311.611.9409-0.34087
546.710.9968-4.29679
5510.913.1505-2.25054
5612.112.6283-0.528347
5713.313.4901-0.19013
5810.113.3483-3.24834
595.711.6699-5.96994
6014.312.11672.18325
6189.47516-1.47516
6213.311.62981.67022
639.312.5351-3.23513
6412.511.66470.835261
657.610.653-3.053
6615.913.72382.17624
679.211.3063-2.10628
689.110.4967-1.39666
6911.114.0428-2.9428
701313.3151-0.315053
7114.512.92651.57352
7212.210.95321.2468
7312.313.4333-1.13332
7411.411.27220.127839
758.811.145-2.34501
7614.610.94773.65233
777.312.2606-4.96061
7812.612.8926-0.292618
79NANA-0.584463
801311.62151.37854
8112.614.0125-1.41255
8213.214.4913-1.29134
839.913.5234-3.62343
847.77.72581-0.0258115
8510.57.612642.88736
8613.414.2232-0.823241
8710.916.5748-5.67478
884.34.90228-0.602278
8910.39.909620.390378
9011.811.15610.643873
9111.210.63720.562799
9211.412.8358-1.43576
938.66.307592.29241
9413.210.83532.36475
9512.618.0219-5.42191
965.66.78531-1.18531
979.912.9912-3.09119
988.812.7823-3.98234
997.79.00707-1.30707
100913.9002-4.90019
1017.36.869240.430758
10211.49.178132.22187
10313.616.2895-2.68946
1047.98.0449-0.144904
10510.712.0007-1.30072
10610.312.1895-1.88952
1078.39.52097-1.22097
1089.67.015762.58424
10914.215.9897-1.78973
1108.55.579152.92085
11113.519.2036-5.70362
1124.98.61089-3.71089
1136.47.03436-0.634361
1149.68.724840.875162
11511.610.76770.832271
11611.116.3336-5.23355
1174.354.126080.223922
11812.79.37633.3237
11918.115.35382.74623
12017.8516.93880.911199
12116.613.59733.00275
12212.617.8694-5.26935
12317.113.50753.59246
12419.121.1591-2.05909
12516.113.36262.73741
12613.3512.61320.7368
12718.414.67923.72084
12814.718.9181-4.21814
12910.611.7413-1.14135
13012.611.49741.10264
13116.220.0526-3.85255
13213.610.8272.77297
13318.917.16171.73832
13414.111.41462.68541
13514.516.4603-1.96029
13616.1514.54841.60159
13714.7514.11320.636759
13814.814.60410.19588
13912.4514.5192-2.06925
14012.659.061423.58858
14117.3520.7422-3.39224
1428.67.800080.799923
14318.420.3862-1.98624
14416.115.19750.902453
14511.65.563936.03607
14617.7516.04831.70174
14715.2513.84791.40208
14817.6515.80541.84455
14915.613.8991.70102
15016.3513.41922.93085
15117.6516.96470.685267
15213.614.0535-0.45351
15311.710.7410.959019
15414.3517.695-3.34498
15514.7512.91661.83338
15618.2523.5227-5.2727
1579.97.751452.14855
1581613.45512.54488
15918.2518.7914-0.54144
16016.8514.73552.11453
16114.614.35560.244409
16213.8511.05382.79616
16318.9517.91911.03093
16415.618.0197-2.41975
16514.8515.7949-0.944898
16611.755.875065.87494
16718.4520.0212-1.57125
16815.913.06022.83979
16917.111.73345.36662
17016.110.76775.33228
17119.919.68450.21546
17210.958.184922.76508
17318.4513.82774.62234
17415.115.6113-0.51132
1751517.5813-2.58127
17611.3510.41540.934616
17715.9510.9954.95496
17818.116.16191.93811
17914.615.0138-0.413811
18015.415.8138-0.413811
18115.411.1824.218
18217.617.943-0.342979
18313.3510.93492.41507
18419.116.59162.50839
18515.3519.9708-4.62078
1867.67.89542-0.29542
18713.413.26840.131589
18813.911.9561.94399
18919.117.50451.59551
19015.2514.2341.01602
19112.910.48242.41762
19216.110.96245.13763
19317.3516.38270.967295
19413.1510.82432.32573
19512.1512.02310.126943
19612.613.647-1.04701
19710.357.715942.63406
19815.416.5414-1.14142
1999.64.535635.06437
20018.216.58851.61152
20113.613.330.26999
20214.8517.0819-2.2319
20314.7514.7911-0.0410933
20414.110.7913.30896
20514.911.25773.64235
20616.2514.56791.68213
20719.2517.50681.74323
20813.613.18080.419238
20913.613.11610.483908
21015.6515.4070.243039
21112.759.209123.54088
21214.618.0089-3.40885
2139.858.159031.69097
21412.6513.1732-0.523237
21511.99.008942.89106
21619.217.0522.14795
21716.615.0921.508
21811.29.308881.89112
21915.2518.4478-3.19779
22011.914.948-3.04799
22113.214.0129-0.812937
22216.3517.2905-0.940506
22312.49.355933.04407
22415.8515.08170.768263
22514.3511.1863.164
22618.1518.2607-0.110703
22711.1511.3525-0.20253
22815.6514.26581.38416
22917.7522.4889-4.7389
2307.657.500270.149729
23112.358.196234.15377
23215.612.58263.01739
23319.315.82523.47475
23415.211.4943.70599
23517.114.44792.65205
23615.611.96813.63191
23718.414.46673.9333
23819.0513.74865.30138
23918.5516.52252.02747
24019.117.67041.4296
24113.113.4127-0.312739
24212.8514.7776-1.92758
2439.516.1367-6.63667
2444.53.096951.40305
24511.8514.1694-2.31942
24613.615.1708-1.57077
24711.710.62411.07591
24812.413.8184-1.41835
24913.3515.7325-2.38248
25011.48.046313.35369
25114.99.567725.33228
25219.914.01345.88665
25317.7518.6326-0.88258
25411.212.0266-0.826647
25514.612.80481.79522
25617.616.29791.30208
25714.0513.09090.959078
25816.115.58650.513473
25913.3513.5824-0.232356
26011.8514.1242-2.27419
26111.9511.75210.197933
26214.7512.4992.25099
26315.1515.555-0.404954
26413.212.04251.15752
26516.8519.019-2.169
2667.8515.1939-7.34387
2677.76.015851.68415
26812.616.0609-3.46089
2697.857.634540.21546
27010.9510.4260.524015
27112.3514.9548-2.60479
2729.956.596313.35369
27314.913.14891.7511
27416.6516.10970.5403
27513.413.16270.237254
27613.959.674414.27559
27715.710.99424.70585
27816.8516.09660.753427
27910.957.240623.70938
28015.3514.20411.14586
28112.211.02511.17492
28215.113.38771.71231
28317.7515.1232.62697
28415.213.91011.28986
28514.612.26132.3387
28616.6519.2566-2.60662
2878.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9427760.1144490.0572244
100.9007750.1984490.0992247
110.9134330.1731340.0865672
120.8632640.2734710.136736
130.8919840.2160310.108016
140.8405660.3188680.159434
150.7772880.4454240.222712
160.7364660.5270680.263534
170.7338770.5322460.266123
180.6706370.6587260.329363
190.5981550.8036890.401845
200.5277690.9444620.472231
210.4522740.9045480.547726
220.4952090.9904170.504791
230.4448310.8896610.555169
240.3814490.7628990.618551
250.3289780.6579550.671022
260.2742940.5485880.725706
270.2341760.4683530.765824
280.1935630.3871260.806437
290.2573870.5147740.742613
300.2191490.4382980.780851
310.2013390.4026780.798661
320.1723110.3446220.827689
330.1686960.3373920.831304
340.2268080.4536160.773192
350.1936740.3873490.806326
360.2184920.4369840.781508
370.1861860.3723710.813814
380.1548810.3097620.845119
390.1304560.2609120.869544
400.137050.27410.86295
410.159050.31810.84095
420.1430380.2860750.856962
430.1940680.3881360.805932
440.1680690.3361390.831931
450.1537620.3075240.846238
460.1345860.2691720.865414
470.1428260.2856530.857174
480.1226270.2452540.877373
490.1060080.2120160.893992
500.1288080.2576150.871192
510.1401430.2802870.859857
520.1430850.286170.856915
530.1259760.2519520.874024
540.1302710.2605430.869729
550.1207640.2415280.879236
560.1194890.2389790.880511
570.1175570.2351130.882443
580.1034310.2068620.896569
590.1631480.3262960.836852
600.1980270.3960540.801973
610.1713340.3426680.828666
620.1816380.3632750.818362
630.1877120.3754250.812288
640.1775640.3551280.822436
650.1798440.3596870.820156
660.2249670.4499330.775033
670.2191040.4382080.780896
680.1924830.3849670.807517
690.1918190.3836380.808181
700.1789840.3579680.821016
710.1838180.3676360.816182
720.1715630.3431260.828437
730.155980.3119590.84402
740.1393290.2786580.860671
750.1251930.2503850.874807
760.1326320.2652650.867368
770.2206960.4413910.779304
780.2096920.4193830.790308
790.1987940.3975890.801206
800.1908990.3817970.809101
810.1894770.3789530.810523
820.1666440.3332870.833356
830.1962740.3925480.803726
840.1728110.3456210.827189
850.1914460.3828930.808554
860.1699320.3398630.830068
870.2900840.5801680.709916
880.2709770.5419540.729023
890.2464730.4929470.753527
900.2199270.4398530.780073
910.1966190.3932380.803381
920.1861960.3723920.813804
930.1956060.3912120.804394
940.2047980.4095960.795202
950.3010950.6021910.698905
960.3034820.6069650.696518
970.2975720.5951440.702428
980.3200460.6400920.679954
990.3143050.6286090.685695
1000.398970.7979410.60103
1010.383170.766340.61683
1020.4295090.8590180.570491
1030.4872570.9745150.512743
1040.4594230.9188460.540577
1050.4429810.8859630.557019
1060.4453190.8906370.554681
1070.4634840.9269680.536516
1080.4958490.9916990.504151
1090.5219370.9561270.478063
1100.5398640.9202720.460136
1110.736220.527560.26378
1120.7734550.453090.226545
1130.7815310.4369380.218469
1140.7780040.4439930.221996
1150.7684210.4631570.231579
1160.8184950.363010.181505
1170.8111020.3777970.188898
1180.8893780.2212440.110622
1190.9229460.1541080.0770541
1200.9153030.1693940.0846971
1210.945460.109080.0545399
1220.9421210.1157570.0578786
1230.953860.09227910.0461396
1240.9621570.07568670.0378434
1250.9676780.06464460.0323223
1260.9689360.06212860.0310643
1270.9808910.03821710.0191085
1280.9838730.03225380.0161269
1290.9809760.03804710.0190236
1300.9803970.03920560.0196028
1310.9788410.0423170.0211585
1320.9775190.04496150.0224807
1330.976180.04764020.0238201
1340.9776430.0447140.022357
1350.9764580.0470850.0235425
1360.978530.04294080.0214704
1370.9747580.05048340.0252417
1380.9697270.06054520.0302726
1390.9648870.07022580.0351129
1400.9751540.04969280.0248464
1410.9753050.04939050.0246953
1420.9728280.0543450.0271725
1430.9677370.06452620.0322631
1440.9642860.07142720.0357136
1450.9831170.03376690.0168834
1460.9825250.03494940.0174747
1470.9824650.03506960.0175348
1480.9813080.03738470.0186923
1490.9786230.0427540.021377
1500.9792920.04141650.0207083
1510.9757710.04845820.0242291
1520.9741690.0516630.0258315
1530.9698040.0603910.0301955
1540.9658670.06826650.0341332
1550.9643240.07135220.0356761
1560.9875130.02497490.0124875
1570.9862160.02756860.0137843
1580.9865770.02684570.0134229
1590.9836190.0327620.016381
1600.9842310.0315380.015769
1610.9809020.03819510.0190976
1620.9802340.03953270.0197664
1630.976860.04627910.0231395
1640.9751020.04979520.0248976
1650.9707480.05850340.0292517
1660.9806870.03862670.0193133
1670.977540.04491940.0224597
1680.9785710.04285730.0214287
1690.9959310.008137010.0040685
1700.9968630.006273510.00313676
1710.995930.008140460.00407023
1720.9958870.00822670.00411335
1730.9973330.005334190.00266709
1740.9965530.00689470.00344735
1750.9967010.006597180.00329859
1760.9960330.007933150.00396657
1770.997320.005360910.00268045
1780.9970370.005925310.00296266
1790.996160.007680670.00384033
1800.9950730.009854960.00492748
1810.9959120.008175590.00408779
1820.995380.009240480.00462024
1830.9953440.009312850.00465643
1840.9947760.01044850.00522427
1850.9959450.008109810.00405491
1860.9955680.008863810.00443191
1870.9945970.01080510.00540257
1880.9937240.01255120.00627558
1890.992160.01568040.00784021
1900.9918550.01629010.00814506
1910.9904160.01916780.00958389
1920.9949060.01018870.00509434
1930.9937350.01253070.00626533
1940.9924930.01501490.00750747
1950.9903940.01921260.00960628
1960.9880750.02385020.0119251
1970.9859720.02805530.0140276
1980.9841760.03164870.0158244
1990.9901840.0196320.00981599
2000.988190.02361980.0118099
2010.986750.02649940.0132497
2020.9865440.0269120.013456
2030.9827580.0344850.0172425
2040.9838290.03234170.0161709
2050.9833480.03330460.0166523
2060.9806230.03875360.0193768
2070.9793010.04139790.0206989
2080.976910.04618090.0230905
2090.9716660.05666840.0283342
2100.9660820.06783690.0339184
2110.974760.05048040.0252402
2120.9719770.05604680.0280234
2130.9705850.05882980.0294149
2140.9631270.07374630.0368732
2150.9591470.08170640.0408532
2160.9525030.09499430.0474972
2170.9428970.1142050.0571027
2180.933440.1331190.0665596
2190.9447150.1105690.0552846
2200.9364760.1270470.0635236
2210.9324720.1350560.0675281
2220.9207310.1585380.0792688
2230.9176380.1647250.0823623
2240.9044460.1911080.0955542
2250.8924320.2151360.107568
2260.8705810.2588380.129419
2270.8459080.3081850.154092
2280.8311160.3377670.168884
2290.8498230.3003540.150177
2300.8245080.3509840.175492
2310.8239290.3521420.176071
2320.8076740.3846530.192326
2330.8694930.2610130.130507
2340.8848620.2302760.115138
2350.8877110.2245780.112289
2360.8722150.2555710.127785
2370.8858080.2283850.114192
2380.9102370.1795260.089763
2390.8898620.2202750.110138
2400.8705620.2588750.129438
2410.864560.270880.13544
2420.8602950.279410.139705
2430.9444130.1111740.0555868
2440.9400720.1198560.059928
2450.939990.120020.0600101
2460.9243260.1513490.0756745
2470.9033790.1932430.0966214
2480.8883250.223350.111675
2490.8648350.270330.135165
2500.8532770.2934460.146723
2510.8388030.3223940.161197
2520.9055940.1888130.0944065
2530.8791090.2417830.120891
2540.8503290.2993420.149671
2550.8201140.3597720.179886
2560.7803220.4393560.219678
2570.7336610.5326780.266339
2580.6783530.6432950.321647
2590.6282980.7434030.371702
2600.6261830.7476340.373817
2610.5608420.8783170.439158
2620.4961230.9922460.503877
2630.5506680.8986640.449332
2640.4820910.9641830.517909
2650.4804740.9609480.519526
2660.9027320.1945350.0972677
2670.8637410.2725170.136259
2680.9959630.008074660.00403733
2690.9969680.006063570.00303179
2700.9973360.005328490.00266425
2710.999820.0003592110.000179605
2720.9994090.001182220.000591112
2730.9980360.003927030.00196351
2740.9959350.008130730.00406537
2750.9945070.01098580.00549291
2760.982650.03469980.0173499
2770.9714340.05713290.0285664
2780.8881690.2236630.111831

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.942776 & 0.114449 & 0.0572244 \tabularnewline
10 & 0.900775 & 0.198449 & 0.0992247 \tabularnewline
11 & 0.913433 & 0.173134 & 0.0865672 \tabularnewline
12 & 0.863264 & 0.273471 & 0.136736 \tabularnewline
13 & 0.891984 & 0.216031 & 0.108016 \tabularnewline
14 & 0.840566 & 0.318868 & 0.159434 \tabularnewline
15 & 0.777288 & 0.445424 & 0.222712 \tabularnewline
16 & 0.736466 & 0.527068 & 0.263534 \tabularnewline
17 & 0.733877 & 0.532246 & 0.266123 \tabularnewline
18 & 0.670637 & 0.658726 & 0.329363 \tabularnewline
19 & 0.598155 & 0.803689 & 0.401845 \tabularnewline
20 & 0.527769 & 0.944462 & 0.472231 \tabularnewline
21 & 0.452274 & 0.904548 & 0.547726 \tabularnewline
22 & 0.495209 & 0.990417 & 0.504791 \tabularnewline
23 & 0.444831 & 0.889661 & 0.555169 \tabularnewline
24 & 0.381449 & 0.762899 & 0.618551 \tabularnewline
25 & 0.328978 & 0.657955 & 0.671022 \tabularnewline
26 & 0.274294 & 0.548588 & 0.725706 \tabularnewline
27 & 0.234176 & 0.468353 & 0.765824 \tabularnewline
28 & 0.193563 & 0.387126 & 0.806437 \tabularnewline
29 & 0.257387 & 0.514774 & 0.742613 \tabularnewline
30 & 0.219149 & 0.438298 & 0.780851 \tabularnewline
31 & 0.201339 & 0.402678 & 0.798661 \tabularnewline
32 & 0.172311 & 0.344622 & 0.827689 \tabularnewline
33 & 0.168696 & 0.337392 & 0.831304 \tabularnewline
34 & 0.226808 & 0.453616 & 0.773192 \tabularnewline
35 & 0.193674 & 0.387349 & 0.806326 \tabularnewline
36 & 0.218492 & 0.436984 & 0.781508 \tabularnewline
37 & 0.186186 & 0.372371 & 0.813814 \tabularnewline
38 & 0.154881 & 0.309762 & 0.845119 \tabularnewline
39 & 0.130456 & 0.260912 & 0.869544 \tabularnewline
40 & 0.13705 & 0.2741 & 0.86295 \tabularnewline
41 & 0.15905 & 0.3181 & 0.84095 \tabularnewline
42 & 0.143038 & 0.286075 & 0.856962 \tabularnewline
43 & 0.194068 & 0.388136 & 0.805932 \tabularnewline
44 & 0.168069 & 0.336139 & 0.831931 \tabularnewline
45 & 0.153762 & 0.307524 & 0.846238 \tabularnewline
46 & 0.134586 & 0.269172 & 0.865414 \tabularnewline
47 & 0.142826 & 0.285653 & 0.857174 \tabularnewline
48 & 0.122627 & 0.245254 & 0.877373 \tabularnewline
49 & 0.106008 & 0.212016 & 0.893992 \tabularnewline
50 & 0.128808 & 0.257615 & 0.871192 \tabularnewline
51 & 0.140143 & 0.280287 & 0.859857 \tabularnewline
52 & 0.143085 & 0.28617 & 0.856915 \tabularnewline
53 & 0.125976 & 0.251952 & 0.874024 \tabularnewline
54 & 0.130271 & 0.260543 & 0.869729 \tabularnewline
55 & 0.120764 & 0.241528 & 0.879236 \tabularnewline
56 & 0.119489 & 0.238979 & 0.880511 \tabularnewline
57 & 0.117557 & 0.235113 & 0.882443 \tabularnewline
58 & 0.103431 & 0.206862 & 0.896569 \tabularnewline
59 & 0.163148 & 0.326296 & 0.836852 \tabularnewline
60 & 0.198027 & 0.396054 & 0.801973 \tabularnewline
61 & 0.171334 & 0.342668 & 0.828666 \tabularnewline
62 & 0.181638 & 0.363275 & 0.818362 \tabularnewline
63 & 0.187712 & 0.375425 & 0.812288 \tabularnewline
64 & 0.177564 & 0.355128 & 0.822436 \tabularnewline
65 & 0.179844 & 0.359687 & 0.820156 \tabularnewline
66 & 0.224967 & 0.449933 & 0.775033 \tabularnewline
67 & 0.219104 & 0.438208 & 0.780896 \tabularnewline
68 & 0.192483 & 0.384967 & 0.807517 \tabularnewline
69 & 0.191819 & 0.383638 & 0.808181 \tabularnewline
70 & 0.178984 & 0.357968 & 0.821016 \tabularnewline
71 & 0.183818 & 0.367636 & 0.816182 \tabularnewline
72 & 0.171563 & 0.343126 & 0.828437 \tabularnewline
73 & 0.15598 & 0.311959 & 0.84402 \tabularnewline
74 & 0.139329 & 0.278658 & 0.860671 \tabularnewline
75 & 0.125193 & 0.250385 & 0.874807 \tabularnewline
76 & 0.132632 & 0.265265 & 0.867368 \tabularnewline
77 & 0.220696 & 0.441391 & 0.779304 \tabularnewline
78 & 0.209692 & 0.419383 & 0.790308 \tabularnewline
79 & 0.198794 & 0.397589 & 0.801206 \tabularnewline
80 & 0.190899 & 0.381797 & 0.809101 \tabularnewline
81 & 0.189477 & 0.378953 & 0.810523 \tabularnewline
82 & 0.166644 & 0.333287 & 0.833356 \tabularnewline
83 & 0.196274 & 0.392548 & 0.803726 \tabularnewline
84 & 0.172811 & 0.345621 & 0.827189 \tabularnewline
85 & 0.191446 & 0.382893 & 0.808554 \tabularnewline
86 & 0.169932 & 0.339863 & 0.830068 \tabularnewline
87 & 0.290084 & 0.580168 & 0.709916 \tabularnewline
88 & 0.270977 & 0.541954 & 0.729023 \tabularnewline
89 & 0.246473 & 0.492947 & 0.753527 \tabularnewline
90 & 0.219927 & 0.439853 & 0.780073 \tabularnewline
91 & 0.196619 & 0.393238 & 0.803381 \tabularnewline
92 & 0.186196 & 0.372392 & 0.813804 \tabularnewline
93 & 0.195606 & 0.391212 & 0.804394 \tabularnewline
94 & 0.204798 & 0.409596 & 0.795202 \tabularnewline
95 & 0.301095 & 0.602191 & 0.698905 \tabularnewline
96 & 0.303482 & 0.606965 & 0.696518 \tabularnewline
97 & 0.297572 & 0.595144 & 0.702428 \tabularnewline
98 & 0.320046 & 0.640092 & 0.679954 \tabularnewline
99 & 0.314305 & 0.628609 & 0.685695 \tabularnewline
100 & 0.39897 & 0.797941 & 0.60103 \tabularnewline
101 & 0.38317 & 0.76634 & 0.61683 \tabularnewline
102 & 0.429509 & 0.859018 & 0.570491 \tabularnewline
103 & 0.487257 & 0.974515 & 0.512743 \tabularnewline
104 & 0.459423 & 0.918846 & 0.540577 \tabularnewline
105 & 0.442981 & 0.885963 & 0.557019 \tabularnewline
106 & 0.445319 & 0.890637 & 0.554681 \tabularnewline
107 & 0.463484 & 0.926968 & 0.536516 \tabularnewline
108 & 0.495849 & 0.991699 & 0.504151 \tabularnewline
109 & 0.521937 & 0.956127 & 0.478063 \tabularnewline
110 & 0.539864 & 0.920272 & 0.460136 \tabularnewline
111 & 0.73622 & 0.52756 & 0.26378 \tabularnewline
112 & 0.773455 & 0.45309 & 0.226545 \tabularnewline
113 & 0.781531 & 0.436938 & 0.218469 \tabularnewline
114 & 0.778004 & 0.443993 & 0.221996 \tabularnewline
115 & 0.768421 & 0.463157 & 0.231579 \tabularnewline
116 & 0.818495 & 0.36301 & 0.181505 \tabularnewline
117 & 0.811102 & 0.377797 & 0.188898 \tabularnewline
118 & 0.889378 & 0.221244 & 0.110622 \tabularnewline
119 & 0.922946 & 0.154108 & 0.0770541 \tabularnewline
120 & 0.915303 & 0.169394 & 0.0846971 \tabularnewline
121 & 0.94546 & 0.10908 & 0.0545399 \tabularnewline
122 & 0.942121 & 0.115757 & 0.0578786 \tabularnewline
123 & 0.95386 & 0.0922791 & 0.0461396 \tabularnewline
124 & 0.962157 & 0.0756867 & 0.0378434 \tabularnewline
125 & 0.967678 & 0.0646446 & 0.0323223 \tabularnewline
126 & 0.968936 & 0.0621286 & 0.0310643 \tabularnewline
127 & 0.980891 & 0.0382171 & 0.0191085 \tabularnewline
128 & 0.983873 & 0.0322538 & 0.0161269 \tabularnewline
129 & 0.980976 & 0.0380471 & 0.0190236 \tabularnewline
130 & 0.980397 & 0.0392056 & 0.0196028 \tabularnewline
131 & 0.978841 & 0.042317 & 0.0211585 \tabularnewline
132 & 0.977519 & 0.0449615 & 0.0224807 \tabularnewline
133 & 0.97618 & 0.0476402 & 0.0238201 \tabularnewline
134 & 0.977643 & 0.044714 & 0.022357 \tabularnewline
135 & 0.976458 & 0.047085 & 0.0235425 \tabularnewline
136 & 0.97853 & 0.0429408 & 0.0214704 \tabularnewline
137 & 0.974758 & 0.0504834 & 0.0252417 \tabularnewline
138 & 0.969727 & 0.0605452 & 0.0302726 \tabularnewline
139 & 0.964887 & 0.0702258 & 0.0351129 \tabularnewline
140 & 0.975154 & 0.0496928 & 0.0248464 \tabularnewline
141 & 0.975305 & 0.0493905 & 0.0246953 \tabularnewline
142 & 0.972828 & 0.054345 & 0.0271725 \tabularnewline
143 & 0.967737 & 0.0645262 & 0.0322631 \tabularnewline
144 & 0.964286 & 0.0714272 & 0.0357136 \tabularnewline
145 & 0.983117 & 0.0337669 & 0.0168834 \tabularnewline
146 & 0.982525 & 0.0349494 & 0.0174747 \tabularnewline
147 & 0.982465 & 0.0350696 & 0.0175348 \tabularnewline
148 & 0.981308 & 0.0373847 & 0.0186923 \tabularnewline
149 & 0.978623 & 0.042754 & 0.021377 \tabularnewline
150 & 0.979292 & 0.0414165 & 0.0207083 \tabularnewline
151 & 0.975771 & 0.0484582 & 0.0242291 \tabularnewline
152 & 0.974169 & 0.051663 & 0.0258315 \tabularnewline
153 & 0.969804 & 0.060391 & 0.0301955 \tabularnewline
154 & 0.965867 & 0.0682665 & 0.0341332 \tabularnewline
155 & 0.964324 & 0.0713522 & 0.0356761 \tabularnewline
156 & 0.987513 & 0.0249749 & 0.0124875 \tabularnewline
157 & 0.986216 & 0.0275686 & 0.0137843 \tabularnewline
158 & 0.986577 & 0.0268457 & 0.0134229 \tabularnewline
159 & 0.983619 & 0.032762 & 0.016381 \tabularnewline
160 & 0.984231 & 0.031538 & 0.015769 \tabularnewline
161 & 0.980902 & 0.0381951 & 0.0190976 \tabularnewline
162 & 0.980234 & 0.0395327 & 0.0197664 \tabularnewline
163 & 0.97686 & 0.0462791 & 0.0231395 \tabularnewline
164 & 0.975102 & 0.0497952 & 0.0248976 \tabularnewline
165 & 0.970748 & 0.0585034 & 0.0292517 \tabularnewline
166 & 0.980687 & 0.0386267 & 0.0193133 \tabularnewline
167 & 0.97754 & 0.0449194 & 0.0224597 \tabularnewline
168 & 0.978571 & 0.0428573 & 0.0214287 \tabularnewline
169 & 0.995931 & 0.00813701 & 0.0040685 \tabularnewline
170 & 0.996863 & 0.00627351 & 0.00313676 \tabularnewline
171 & 0.99593 & 0.00814046 & 0.00407023 \tabularnewline
172 & 0.995887 & 0.0082267 & 0.00411335 \tabularnewline
173 & 0.997333 & 0.00533419 & 0.00266709 \tabularnewline
174 & 0.996553 & 0.0068947 & 0.00344735 \tabularnewline
175 & 0.996701 & 0.00659718 & 0.00329859 \tabularnewline
176 & 0.996033 & 0.00793315 & 0.00396657 \tabularnewline
177 & 0.99732 & 0.00536091 & 0.00268045 \tabularnewline
178 & 0.997037 & 0.00592531 & 0.00296266 \tabularnewline
179 & 0.99616 & 0.00768067 & 0.00384033 \tabularnewline
180 & 0.995073 & 0.00985496 & 0.00492748 \tabularnewline
181 & 0.995912 & 0.00817559 & 0.00408779 \tabularnewline
182 & 0.99538 & 0.00924048 & 0.00462024 \tabularnewline
183 & 0.995344 & 0.00931285 & 0.00465643 \tabularnewline
184 & 0.994776 & 0.0104485 & 0.00522427 \tabularnewline
185 & 0.995945 & 0.00810981 & 0.00405491 \tabularnewline
186 & 0.995568 & 0.00886381 & 0.00443191 \tabularnewline
187 & 0.994597 & 0.0108051 & 0.00540257 \tabularnewline
188 & 0.993724 & 0.0125512 & 0.00627558 \tabularnewline
189 & 0.99216 & 0.0156804 & 0.00784021 \tabularnewline
190 & 0.991855 & 0.0162901 & 0.00814506 \tabularnewline
191 & 0.990416 & 0.0191678 & 0.00958389 \tabularnewline
192 & 0.994906 & 0.0101887 & 0.00509434 \tabularnewline
193 & 0.993735 & 0.0125307 & 0.00626533 \tabularnewline
194 & 0.992493 & 0.0150149 & 0.00750747 \tabularnewline
195 & 0.990394 & 0.0192126 & 0.00960628 \tabularnewline
196 & 0.988075 & 0.0238502 & 0.0119251 \tabularnewline
197 & 0.985972 & 0.0280553 & 0.0140276 \tabularnewline
198 & 0.984176 & 0.0316487 & 0.0158244 \tabularnewline
199 & 0.990184 & 0.019632 & 0.00981599 \tabularnewline
200 & 0.98819 & 0.0236198 & 0.0118099 \tabularnewline
201 & 0.98675 & 0.0264994 & 0.0132497 \tabularnewline
202 & 0.986544 & 0.026912 & 0.013456 \tabularnewline
203 & 0.982758 & 0.034485 & 0.0172425 \tabularnewline
204 & 0.983829 & 0.0323417 & 0.0161709 \tabularnewline
205 & 0.983348 & 0.0333046 & 0.0166523 \tabularnewline
206 & 0.980623 & 0.0387536 & 0.0193768 \tabularnewline
207 & 0.979301 & 0.0413979 & 0.0206989 \tabularnewline
208 & 0.97691 & 0.0461809 & 0.0230905 \tabularnewline
209 & 0.971666 & 0.0566684 & 0.0283342 \tabularnewline
210 & 0.966082 & 0.0678369 & 0.0339184 \tabularnewline
211 & 0.97476 & 0.0504804 & 0.0252402 \tabularnewline
212 & 0.971977 & 0.0560468 & 0.0280234 \tabularnewline
213 & 0.970585 & 0.0588298 & 0.0294149 \tabularnewline
214 & 0.963127 & 0.0737463 & 0.0368732 \tabularnewline
215 & 0.959147 & 0.0817064 & 0.0408532 \tabularnewline
216 & 0.952503 & 0.0949943 & 0.0474972 \tabularnewline
217 & 0.942897 & 0.114205 & 0.0571027 \tabularnewline
218 & 0.93344 & 0.133119 & 0.0665596 \tabularnewline
219 & 0.944715 & 0.110569 & 0.0552846 \tabularnewline
220 & 0.936476 & 0.127047 & 0.0635236 \tabularnewline
221 & 0.932472 & 0.135056 & 0.0675281 \tabularnewline
222 & 0.920731 & 0.158538 & 0.0792688 \tabularnewline
223 & 0.917638 & 0.164725 & 0.0823623 \tabularnewline
224 & 0.904446 & 0.191108 & 0.0955542 \tabularnewline
225 & 0.892432 & 0.215136 & 0.107568 \tabularnewline
226 & 0.870581 & 0.258838 & 0.129419 \tabularnewline
227 & 0.845908 & 0.308185 & 0.154092 \tabularnewline
228 & 0.831116 & 0.337767 & 0.168884 \tabularnewline
229 & 0.849823 & 0.300354 & 0.150177 \tabularnewline
230 & 0.824508 & 0.350984 & 0.175492 \tabularnewline
231 & 0.823929 & 0.352142 & 0.176071 \tabularnewline
232 & 0.807674 & 0.384653 & 0.192326 \tabularnewline
233 & 0.869493 & 0.261013 & 0.130507 \tabularnewline
234 & 0.884862 & 0.230276 & 0.115138 \tabularnewline
235 & 0.887711 & 0.224578 & 0.112289 \tabularnewline
236 & 0.872215 & 0.255571 & 0.127785 \tabularnewline
237 & 0.885808 & 0.228385 & 0.114192 \tabularnewline
238 & 0.910237 & 0.179526 & 0.089763 \tabularnewline
239 & 0.889862 & 0.220275 & 0.110138 \tabularnewline
240 & 0.870562 & 0.258875 & 0.129438 \tabularnewline
241 & 0.86456 & 0.27088 & 0.13544 \tabularnewline
242 & 0.860295 & 0.27941 & 0.139705 \tabularnewline
243 & 0.944413 & 0.111174 & 0.0555868 \tabularnewline
244 & 0.940072 & 0.119856 & 0.059928 \tabularnewline
245 & 0.93999 & 0.12002 & 0.0600101 \tabularnewline
246 & 0.924326 & 0.151349 & 0.0756745 \tabularnewline
247 & 0.903379 & 0.193243 & 0.0966214 \tabularnewline
248 & 0.888325 & 0.22335 & 0.111675 \tabularnewline
249 & 0.864835 & 0.27033 & 0.135165 \tabularnewline
250 & 0.853277 & 0.293446 & 0.146723 \tabularnewline
251 & 0.838803 & 0.322394 & 0.161197 \tabularnewline
252 & 0.905594 & 0.188813 & 0.0944065 \tabularnewline
253 & 0.879109 & 0.241783 & 0.120891 \tabularnewline
254 & 0.850329 & 0.299342 & 0.149671 \tabularnewline
255 & 0.820114 & 0.359772 & 0.179886 \tabularnewline
256 & 0.780322 & 0.439356 & 0.219678 \tabularnewline
257 & 0.733661 & 0.532678 & 0.266339 \tabularnewline
258 & 0.678353 & 0.643295 & 0.321647 \tabularnewline
259 & 0.628298 & 0.743403 & 0.371702 \tabularnewline
260 & 0.626183 & 0.747634 & 0.373817 \tabularnewline
261 & 0.560842 & 0.878317 & 0.439158 \tabularnewline
262 & 0.496123 & 0.992246 & 0.503877 \tabularnewline
263 & 0.550668 & 0.898664 & 0.449332 \tabularnewline
264 & 0.482091 & 0.964183 & 0.517909 \tabularnewline
265 & 0.480474 & 0.960948 & 0.519526 \tabularnewline
266 & 0.902732 & 0.194535 & 0.0972677 \tabularnewline
267 & 0.863741 & 0.272517 & 0.136259 \tabularnewline
268 & 0.995963 & 0.00807466 & 0.00403733 \tabularnewline
269 & 0.996968 & 0.00606357 & 0.00303179 \tabularnewline
270 & 0.997336 & 0.00532849 & 0.00266425 \tabularnewline
271 & 0.99982 & 0.000359211 & 0.000179605 \tabularnewline
272 & 0.999409 & 0.00118222 & 0.000591112 \tabularnewline
273 & 0.998036 & 0.00392703 & 0.00196351 \tabularnewline
274 & 0.995935 & 0.00813073 & 0.00406537 \tabularnewline
275 & 0.994507 & 0.0109858 & 0.00549291 \tabularnewline
276 & 0.98265 & 0.0346998 & 0.0173499 \tabularnewline
277 & 0.971434 & 0.0571329 & 0.0285664 \tabularnewline
278 & 0.888169 & 0.223663 & 0.111831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268645&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]0.942776[/C][C]0.114449[/C][C]0.0572244[/C][/ROW]
[ROW][C]10[/C][C]0.900775[/C][C]0.198449[/C][C]0.0992247[/C][/ROW]
[ROW][C]11[/C][C]0.913433[/C][C]0.173134[/C][C]0.0865672[/C][/ROW]
[ROW][C]12[/C][C]0.863264[/C][C]0.273471[/C][C]0.136736[/C][/ROW]
[ROW][C]13[/C][C]0.891984[/C][C]0.216031[/C][C]0.108016[/C][/ROW]
[ROW][C]14[/C][C]0.840566[/C][C]0.318868[/C][C]0.159434[/C][/ROW]
[ROW][C]15[/C][C]0.777288[/C][C]0.445424[/C][C]0.222712[/C][/ROW]
[ROW][C]16[/C][C]0.736466[/C][C]0.527068[/C][C]0.263534[/C][/ROW]
[ROW][C]17[/C][C]0.733877[/C][C]0.532246[/C][C]0.266123[/C][/ROW]
[ROW][C]18[/C][C]0.670637[/C][C]0.658726[/C][C]0.329363[/C][/ROW]
[ROW][C]19[/C][C]0.598155[/C][C]0.803689[/C][C]0.401845[/C][/ROW]
[ROW][C]20[/C][C]0.527769[/C][C]0.944462[/C][C]0.472231[/C][/ROW]
[ROW][C]21[/C][C]0.452274[/C][C]0.904548[/C][C]0.547726[/C][/ROW]
[ROW][C]22[/C][C]0.495209[/C][C]0.990417[/C][C]0.504791[/C][/ROW]
[ROW][C]23[/C][C]0.444831[/C][C]0.889661[/C][C]0.555169[/C][/ROW]
[ROW][C]24[/C][C]0.381449[/C][C]0.762899[/C][C]0.618551[/C][/ROW]
[ROW][C]25[/C][C]0.328978[/C][C]0.657955[/C][C]0.671022[/C][/ROW]
[ROW][C]26[/C][C]0.274294[/C][C]0.548588[/C][C]0.725706[/C][/ROW]
[ROW][C]27[/C][C]0.234176[/C][C]0.468353[/C][C]0.765824[/C][/ROW]
[ROW][C]28[/C][C]0.193563[/C][C]0.387126[/C][C]0.806437[/C][/ROW]
[ROW][C]29[/C][C]0.257387[/C][C]0.514774[/C][C]0.742613[/C][/ROW]
[ROW][C]30[/C][C]0.219149[/C][C]0.438298[/C][C]0.780851[/C][/ROW]
[ROW][C]31[/C][C]0.201339[/C][C]0.402678[/C][C]0.798661[/C][/ROW]
[ROW][C]32[/C][C]0.172311[/C][C]0.344622[/C][C]0.827689[/C][/ROW]
[ROW][C]33[/C][C]0.168696[/C][C]0.337392[/C][C]0.831304[/C][/ROW]
[ROW][C]34[/C][C]0.226808[/C][C]0.453616[/C][C]0.773192[/C][/ROW]
[ROW][C]35[/C][C]0.193674[/C][C]0.387349[/C][C]0.806326[/C][/ROW]
[ROW][C]36[/C][C]0.218492[/C][C]0.436984[/C][C]0.781508[/C][/ROW]
[ROW][C]37[/C][C]0.186186[/C][C]0.372371[/C][C]0.813814[/C][/ROW]
[ROW][C]38[/C][C]0.154881[/C][C]0.309762[/C][C]0.845119[/C][/ROW]
[ROW][C]39[/C][C]0.130456[/C][C]0.260912[/C][C]0.869544[/C][/ROW]
[ROW][C]40[/C][C]0.13705[/C][C]0.2741[/C][C]0.86295[/C][/ROW]
[ROW][C]41[/C][C]0.15905[/C][C]0.3181[/C][C]0.84095[/C][/ROW]
[ROW][C]42[/C][C]0.143038[/C][C]0.286075[/C][C]0.856962[/C][/ROW]
[ROW][C]43[/C][C]0.194068[/C][C]0.388136[/C][C]0.805932[/C][/ROW]
[ROW][C]44[/C][C]0.168069[/C][C]0.336139[/C][C]0.831931[/C][/ROW]
[ROW][C]45[/C][C]0.153762[/C][C]0.307524[/C][C]0.846238[/C][/ROW]
[ROW][C]46[/C][C]0.134586[/C][C]0.269172[/C][C]0.865414[/C][/ROW]
[ROW][C]47[/C][C]0.142826[/C][C]0.285653[/C][C]0.857174[/C][/ROW]
[ROW][C]48[/C][C]0.122627[/C][C]0.245254[/C][C]0.877373[/C][/ROW]
[ROW][C]49[/C][C]0.106008[/C][C]0.212016[/C][C]0.893992[/C][/ROW]
[ROW][C]50[/C][C]0.128808[/C][C]0.257615[/C][C]0.871192[/C][/ROW]
[ROW][C]51[/C][C]0.140143[/C][C]0.280287[/C][C]0.859857[/C][/ROW]
[ROW][C]52[/C][C]0.143085[/C][C]0.28617[/C][C]0.856915[/C][/ROW]
[ROW][C]53[/C][C]0.125976[/C][C]0.251952[/C][C]0.874024[/C][/ROW]
[ROW][C]54[/C][C]0.130271[/C][C]0.260543[/C][C]0.869729[/C][/ROW]
[ROW][C]55[/C][C]0.120764[/C][C]0.241528[/C][C]0.879236[/C][/ROW]
[ROW][C]56[/C][C]0.119489[/C][C]0.238979[/C][C]0.880511[/C][/ROW]
[ROW][C]57[/C][C]0.117557[/C][C]0.235113[/C][C]0.882443[/C][/ROW]
[ROW][C]58[/C][C]0.103431[/C][C]0.206862[/C][C]0.896569[/C][/ROW]
[ROW][C]59[/C][C]0.163148[/C][C]0.326296[/C][C]0.836852[/C][/ROW]
[ROW][C]60[/C][C]0.198027[/C][C]0.396054[/C][C]0.801973[/C][/ROW]
[ROW][C]61[/C][C]0.171334[/C][C]0.342668[/C][C]0.828666[/C][/ROW]
[ROW][C]62[/C][C]0.181638[/C][C]0.363275[/C][C]0.818362[/C][/ROW]
[ROW][C]63[/C][C]0.187712[/C][C]0.375425[/C][C]0.812288[/C][/ROW]
[ROW][C]64[/C][C]0.177564[/C][C]0.355128[/C][C]0.822436[/C][/ROW]
[ROW][C]65[/C][C]0.179844[/C][C]0.359687[/C][C]0.820156[/C][/ROW]
[ROW][C]66[/C][C]0.224967[/C][C]0.449933[/C][C]0.775033[/C][/ROW]
[ROW][C]67[/C][C]0.219104[/C][C]0.438208[/C][C]0.780896[/C][/ROW]
[ROW][C]68[/C][C]0.192483[/C][C]0.384967[/C][C]0.807517[/C][/ROW]
[ROW][C]69[/C][C]0.191819[/C][C]0.383638[/C][C]0.808181[/C][/ROW]
[ROW][C]70[/C][C]0.178984[/C][C]0.357968[/C][C]0.821016[/C][/ROW]
[ROW][C]71[/C][C]0.183818[/C][C]0.367636[/C][C]0.816182[/C][/ROW]
[ROW][C]72[/C][C]0.171563[/C][C]0.343126[/C][C]0.828437[/C][/ROW]
[ROW][C]73[/C][C]0.15598[/C][C]0.311959[/C][C]0.84402[/C][/ROW]
[ROW][C]74[/C][C]0.139329[/C][C]0.278658[/C][C]0.860671[/C][/ROW]
[ROW][C]75[/C][C]0.125193[/C][C]0.250385[/C][C]0.874807[/C][/ROW]
[ROW][C]76[/C][C]0.132632[/C][C]0.265265[/C][C]0.867368[/C][/ROW]
[ROW][C]77[/C][C]0.220696[/C][C]0.441391[/C][C]0.779304[/C][/ROW]
[ROW][C]78[/C][C]0.209692[/C][C]0.419383[/C][C]0.790308[/C][/ROW]
[ROW][C]79[/C][C]0.198794[/C][C]0.397589[/C][C]0.801206[/C][/ROW]
[ROW][C]80[/C][C]0.190899[/C][C]0.381797[/C][C]0.809101[/C][/ROW]
[ROW][C]81[/C][C]0.189477[/C][C]0.378953[/C][C]0.810523[/C][/ROW]
[ROW][C]82[/C][C]0.166644[/C][C]0.333287[/C][C]0.833356[/C][/ROW]
[ROW][C]83[/C][C]0.196274[/C][C]0.392548[/C][C]0.803726[/C][/ROW]
[ROW][C]84[/C][C]0.172811[/C][C]0.345621[/C][C]0.827189[/C][/ROW]
[ROW][C]85[/C][C]0.191446[/C][C]0.382893[/C][C]0.808554[/C][/ROW]
[ROW][C]86[/C][C]0.169932[/C][C]0.339863[/C][C]0.830068[/C][/ROW]
[ROW][C]87[/C][C]0.290084[/C][C]0.580168[/C][C]0.709916[/C][/ROW]
[ROW][C]88[/C][C]0.270977[/C][C]0.541954[/C][C]0.729023[/C][/ROW]
[ROW][C]89[/C][C]0.246473[/C][C]0.492947[/C][C]0.753527[/C][/ROW]
[ROW][C]90[/C][C]0.219927[/C][C]0.439853[/C][C]0.780073[/C][/ROW]
[ROW][C]91[/C][C]0.196619[/C][C]0.393238[/C][C]0.803381[/C][/ROW]
[ROW][C]92[/C][C]0.186196[/C][C]0.372392[/C][C]0.813804[/C][/ROW]
[ROW][C]93[/C][C]0.195606[/C][C]0.391212[/C][C]0.804394[/C][/ROW]
[ROW][C]94[/C][C]0.204798[/C][C]0.409596[/C][C]0.795202[/C][/ROW]
[ROW][C]95[/C][C]0.301095[/C][C]0.602191[/C][C]0.698905[/C][/ROW]
[ROW][C]96[/C][C]0.303482[/C][C]0.606965[/C][C]0.696518[/C][/ROW]
[ROW][C]97[/C][C]0.297572[/C][C]0.595144[/C][C]0.702428[/C][/ROW]
[ROW][C]98[/C][C]0.320046[/C][C]0.640092[/C][C]0.679954[/C][/ROW]
[ROW][C]99[/C][C]0.314305[/C][C]0.628609[/C][C]0.685695[/C][/ROW]
[ROW][C]100[/C][C]0.39897[/C][C]0.797941[/C][C]0.60103[/C][/ROW]
[ROW][C]101[/C][C]0.38317[/C][C]0.76634[/C][C]0.61683[/C][/ROW]
[ROW][C]102[/C][C]0.429509[/C][C]0.859018[/C][C]0.570491[/C][/ROW]
[ROW][C]103[/C][C]0.487257[/C][C]0.974515[/C][C]0.512743[/C][/ROW]
[ROW][C]104[/C][C]0.459423[/C][C]0.918846[/C][C]0.540577[/C][/ROW]
[ROW][C]105[/C][C]0.442981[/C][C]0.885963[/C][C]0.557019[/C][/ROW]
[ROW][C]106[/C][C]0.445319[/C][C]0.890637[/C][C]0.554681[/C][/ROW]
[ROW][C]107[/C][C]0.463484[/C][C]0.926968[/C][C]0.536516[/C][/ROW]
[ROW][C]108[/C][C]0.495849[/C][C]0.991699[/C][C]0.504151[/C][/ROW]
[ROW][C]109[/C][C]0.521937[/C][C]0.956127[/C][C]0.478063[/C][/ROW]
[ROW][C]110[/C][C]0.539864[/C][C]0.920272[/C][C]0.460136[/C][/ROW]
[ROW][C]111[/C][C]0.73622[/C][C]0.52756[/C][C]0.26378[/C][/ROW]
[ROW][C]112[/C][C]0.773455[/C][C]0.45309[/C][C]0.226545[/C][/ROW]
[ROW][C]113[/C][C]0.781531[/C][C]0.436938[/C][C]0.218469[/C][/ROW]
[ROW][C]114[/C][C]0.778004[/C][C]0.443993[/C][C]0.221996[/C][/ROW]
[ROW][C]115[/C][C]0.768421[/C][C]0.463157[/C][C]0.231579[/C][/ROW]
[ROW][C]116[/C][C]0.818495[/C][C]0.36301[/C][C]0.181505[/C][/ROW]
[ROW][C]117[/C][C]0.811102[/C][C]0.377797[/C][C]0.188898[/C][/ROW]
[ROW][C]118[/C][C]0.889378[/C][C]0.221244[/C][C]0.110622[/C][/ROW]
[ROW][C]119[/C][C]0.922946[/C][C]0.154108[/C][C]0.0770541[/C][/ROW]
[ROW][C]120[/C][C]0.915303[/C][C]0.169394[/C][C]0.0846971[/C][/ROW]
[ROW][C]121[/C][C]0.94546[/C][C]0.10908[/C][C]0.0545399[/C][/ROW]
[ROW][C]122[/C][C]0.942121[/C][C]0.115757[/C][C]0.0578786[/C][/ROW]
[ROW][C]123[/C][C]0.95386[/C][C]0.0922791[/C][C]0.0461396[/C][/ROW]
[ROW][C]124[/C][C]0.962157[/C][C]0.0756867[/C][C]0.0378434[/C][/ROW]
[ROW][C]125[/C][C]0.967678[/C][C]0.0646446[/C][C]0.0323223[/C][/ROW]
[ROW][C]126[/C][C]0.968936[/C][C]0.0621286[/C][C]0.0310643[/C][/ROW]
[ROW][C]127[/C][C]0.980891[/C][C]0.0382171[/C][C]0.0191085[/C][/ROW]
[ROW][C]128[/C][C]0.983873[/C][C]0.0322538[/C][C]0.0161269[/C][/ROW]
[ROW][C]129[/C][C]0.980976[/C][C]0.0380471[/C][C]0.0190236[/C][/ROW]
[ROW][C]130[/C][C]0.980397[/C][C]0.0392056[/C][C]0.0196028[/C][/ROW]
[ROW][C]131[/C][C]0.978841[/C][C]0.042317[/C][C]0.0211585[/C][/ROW]
[ROW][C]132[/C][C]0.977519[/C][C]0.0449615[/C][C]0.0224807[/C][/ROW]
[ROW][C]133[/C][C]0.97618[/C][C]0.0476402[/C][C]0.0238201[/C][/ROW]
[ROW][C]134[/C][C]0.977643[/C][C]0.044714[/C][C]0.022357[/C][/ROW]
[ROW][C]135[/C][C]0.976458[/C][C]0.047085[/C][C]0.0235425[/C][/ROW]
[ROW][C]136[/C][C]0.97853[/C][C]0.0429408[/C][C]0.0214704[/C][/ROW]
[ROW][C]137[/C][C]0.974758[/C][C]0.0504834[/C][C]0.0252417[/C][/ROW]
[ROW][C]138[/C][C]0.969727[/C][C]0.0605452[/C][C]0.0302726[/C][/ROW]
[ROW][C]139[/C][C]0.964887[/C][C]0.0702258[/C][C]0.0351129[/C][/ROW]
[ROW][C]140[/C][C]0.975154[/C][C]0.0496928[/C][C]0.0248464[/C][/ROW]
[ROW][C]141[/C][C]0.975305[/C][C]0.0493905[/C][C]0.0246953[/C][/ROW]
[ROW][C]142[/C][C]0.972828[/C][C]0.054345[/C][C]0.0271725[/C][/ROW]
[ROW][C]143[/C][C]0.967737[/C][C]0.0645262[/C][C]0.0322631[/C][/ROW]
[ROW][C]144[/C][C]0.964286[/C][C]0.0714272[/C][C]0.0357136[/C][/ROW]
[ROW][C]145[/C][C]0.983117[/C][C]0.0337669[/C][C]0.0168834[/C][/ROW]
[ROW][C]146[/C][C]0.982525[/C][C]0.0349494[/C][C]0.0174747[/C][/ROW]
[ROW][C]147[/C][C]0.982465[/C][C]0.0350696[/C][C]0.0175348[/C][/ROW]
[ROW][C]148[/C][C]0.981308[/C][C]0.0373847[/C][C]0.0186923[/C][/ROW]
[ROW][C]149[/C][C]0.978623[/C][C]0.042754[/C][C]0.021377[/C][/ROW]
[ROW][C]150[/C][C]0.979292[/C][C]0.0414165[/C][C]0.0207083[/C][/ROW]
[ROW][C]151[/C][C]0.975771[/C][C]0.0484582[/C][C]0.0242291[/C][/ROW]
[ROW][C]152[/C][C]0.974169[/C][C]0.051663[/C][C]0.0258315[/C][/ROW]
[ROW][C]153[/C][C]0.969804[/C][C]0.060391[/C][C]0.0301955[/C][/ROW]
[ROW][C]154[/C][C]0.965867[/C][C]0.0682665[/C][C]0.0341332[/C][/ROW]
[ROW][C]155[/C][C]0.964324[/C][C]0.0713522[/C][C]0.0356761[/C][/ROW]
[ROW][C]156[/C][C]0.987513[/C][C]0.0249749[/C][C]0.0124875[/C][/ROW]
[ROW][C]157[/C][C]0.986216[/C][C]0.0275686[/C][C]0.0137843[/C][/ROW]
[ROW][C]158[/C][C]0.986577[/C][C]0.0268457[/C][C]0.0134229[/C][/ROW]
[ROW][C]159[/C][C]0.983619[/C][C]0.032762[/C][C]0.016381[/C][/ROW]
[ROW][C]160[/C][C]0.984231[/C][C]0.031538[/C][C]0.015769[/C][/ROW]
[ROW][C]161[/C][C]0.980902[/C][C]0.0381951[/C][C]0.0190976[/C][/ROW]
[ROW][C]162[/C][C]0.980234[/C][C]0.0395327[/C][C]0.0197664[/C][/ROW]
[ROW][C]163[/C][C]0.97686[/C][C]0.0462791[/C][C]0.0231395[/C][/ROW]
[ROW][C]164[/C][C]0.975102[/C][C]0.0497952[/C][C]0.0248976[/C][/ROW]
[ROW][C]165[/C][C]0.970748[/C][C]0.0585034[/C][C]0.0292517[/C][/ROW]
[ROW][C]166[/C][C]0.980687[/C][C]0.0386267[/C][C]0.0193133[/C][/ROW]
[ROW][C]167[/C][C]0.97754[/C][C]0.0449194[/C][C]0.0224597[/C][/ROW]
[ROW][C]168[/C][C]0.978571[/C][C]0.0428573[/C][C]0.0214287[/C][/ROW]
[ROW][C]169[/C][C]0.995931[/C][C]0.00813701[/C][C]0.0040685[/C][/ROW]
[ROW][C]170[/C][C]0.996863[/C][C]0.00627351[/C][C]0.00313676[/C][/ROW]
[ROW][C]171[/C][C]0.99593[/C][C]0.00814046[/C][C]0.00407023[/C][/ROW]
[ROW][C]172[/C][C]0.995887[/C][C]0.0082267[/C][C]0.00411335[/C][/ROW]
[ROW][C]173[/C][C]0.997333[/C][C]0.00533419[/C][C]0.00266709[/C][/ROW]
[ROW][C]174[/C][C]0.996553[/C][C]0.0068947[/C][C]0.00344735[/C][/ROW]
[ROW][C]175[/C][C]0.996701[/C][C]0.00659718[/C][C]0.00329859[/C][/ROW]
[ROW][C]176[/C][C]0.996033[/C][C]0.00793315[/C][C]0.00396657[/C][/ROW]
[ROW][C]177[/C][C]0.99732[/C][C]0.00536091[/C][C]0.00268045[/C][/ROW]
[ROW][C]178[/C][C]0.997037[/C][C]0.00592531[/C][C]0.00296266[/C][/ROW]
[ROW][C]179[/C][C]0.99616[/C][C]0.00768067[/C][C]0.00384033[/C][/ROW]
[ROW][C]180[/C][C]0.995073[/C][C]0.00985496[/C][C]0.00492748[/C][/ROW]
[ROW][C]181[/C][C]0.995912[/C][C]0.00817559[/C][C]0.00408779[/C][/ROW]
[ROW][C]182[/C][C]0.99538[/C][C]0.00924048[/C][C]0.00462024[/C][/ROW]
[ROW][C]183[/C][C]0.995344[/C][C]0.00931285[/C][C]0.00465643[/C][/ROW]
[ROW][C]184[/C][C]0.994776[/C][C]0.0104485[/C][C]0.00522427[/C][/ROW]
[ROW][C]185[/C][C]0.995945[/C][C]0.00810981[/C][C]0.00405491[/C][/ROW]
[ROW][C]186[/C][C]0.995568[/C][C]0.00886381[/C][C]0.00443191[/C][/ROW]
[ROW][C]187[/C][C]0.994597[/C][C]0.0108051[/C][C]0.00540257[/C][/ROW]
[ROW][C]188[/C][C]0.993724[/C][C]0.0125512[/C][C]0.00627558[/C][/ROW]
[ROW][C]189[/C][C]0.99216[/C][C]0.0156804[/C][C]0.00784021[/C][/ROW]
[ROW][C]190[/C][C]0.991855[/C][C]0.0162901[/C][C]0.00814506[/C][/ROW]
[ROW][C]191[/C][C]0.990416[/C][C]0.0191678[/C][C]0.00958389[/C][/ROW]
[ROW][C]192[/C][C]0.994906[/C][C]0.0101887[/C][C]0.00509434[/C][/ROW]
[ROW][C]193[/C][C]0.993735[/C][C]0.0125307[/C][C]0.00626533[/C][/ROW]
[ROW][C]194[/C][C]0.992493[/C][C]0.0150149[/C][C]0.00750747[/C][/ROW]
[ROW][C]195[/C][C]0.990394[/C][C]0.0192126[/C][C]0.00960628[/C][/ROW]
[ROW][C]196[/C][C]0.988075[/C][C]0.0238502[/C][C]0.0119251[/C][/ROW]
[ROW][C]197[/C][C]0.985972[/C][C]0.0280553[/C][C]0.0140276[/C][/ROW]
[ROW][C]198[/C][C]0.984176[/C][C]0.0316487[/C][C]0.0158244[/C][/ROW]
[ROW][C]199[/C][C]0.990184[/C][C]0.019632[/C][C]0.00981599[/C][/ROW]
[ROW][C]200[/C][C]0.98819[/C][C]0.0236198[/C][C]0.0118099[/C][/ROW]
[ROW][C]201[/C][C]0.98675[/C][C]0.0264994[/C][C]0.0132497[/C][/ROW]
[ROW][C]202[/C][C]0.986544[/C][C]0.026912[/C][C]0.013456[/C][/ROW]
[ROW][C]203[/C][C]0.982758[/C][C]0.034485[/C][C]0.0172425[/C][/ROW]
[ROW][C]204[/C][C]0.983829[/C][C]0.0323417[/C][C]0.0161709[/C][/ROW]
[ROW][C]205[/C][C]0.983348[/C][C]0.0333046[/C][C]0.0166523[/C][/ROW]
[ROW][C]206[/C][C]0.980623[/C][C]0.0387536[/C][C]0.0193768[/C][/ROW]
[ROW][C]207[/C][C]0.979301[/C][C]0.0413979[/C][C]0.0206989[/C][/ROW]
[ROW][C]208[/C][C]0.97691[/C][C]0.0461809[/C][C]0.0230905[/C][/ROW]
[ROW][C]209[/C][C]0.971666[/C][C]0.0566684[/C][C]0.0283342[/C][/ROW]
[ROW][C]210[/C][C]0.966082[/C][C]0.0678369[/C][C]0.0339184[/C][/ROW]
[ROW][C]211[/C][C]0.97476[/C][C]0.0504804[/C][C]0.0252402[/C][/ROW]
[ROW][C]212[/C][C]0.971977[/C][C]0.0560468[/C][C]0.0280234[/C][/ROW]
[ROW][C]213[/C][C]0.970585[/C][C]0.0588298[/C][C]0.0294149[/C][/ROW]
[ROW][C]214[/C][C]0.963127[/C][C]0.0737463[/C][C]0.0368732[/C][/ROW]
[ROW][C]215[/C][C]0.959147[/C][C]0.0817064[/C][C]0.0408532[/C][/ROW]
[ROW][C]216[/C][C]0.952503[/C][C]0.0949943[/C][C]0.0474972[/C][/ROW]
[ROW][C]217[/C][C]0.942897[/C][C]0.114205[/C][C]0.0571027[/C][/ROW]
[ROW][C]218[/C][C]0.93344[/C][C]0.133119[/C][C]0.0665596[/C][/ROW]
[ROW][C]219[/C][C]0.944715[/C][C]0.110569[/C][C]0.0552846[/C][/ROW]
[ROW][C]220[/C][C]0.936476[/C][C]0.127047[/C][C]0.0635236[/C][/ROW]
[ROW][C]221[/C][C]0.932472[/C][C]0.135056[/C][C]0.0675281[/C][/ROW]
[ROW][C]222[/C][C]0.920731[/C][C]0.158538[/C][C]0.0792688[/C][/ROW]
[ROW][C]223[/C][C]0.917638[/C][C]0.164725[/C][C]0.0823623[/C][/ROW]
[ROW][C]224[/C][C]0.904446[/C][C]0.191108[/C][C]0.0955542[/C][/ROW]
[ROW][C]225[/C][C]0.892432[/C][C]0.215136[/C][C]0.107568[/C][/ROW]
[ROW][C]226[/C][C]0.870581[/C][C]0.258838[/C][C]0.129419[/C][/ROW]
[ROW][C]227[/C][C]0.845908[/C][C]0.308185[/C][C]0.154092[/C][/ROW]
[ROW][C]228[/C][C]0.831116[/C][C]0.337767[/C][C]0.168884[/C][/ROW]
[ROW][C]229[/C][C]0.849823[/C][C]0.300354[/C][C]0.150177[/C][/ROW]
[ROW][C]230[/C][C]0.824508[/C][C]0.350984[/C][C]0.175492[/C][/ROW]
[ROW][C]231[/C][C]0.823929[/C][C]0.352142[/C][C]0.176071[/C][/ROW]
[ROW][C]232[/C][C]0.807674[/C][C]0.384653[/C][C]0.192326[/C][/ROW]
[ROW][C]233[/C][C]0.869493[/C][C]0.261013[/C][C]0.130507[/C][/ROW]
[ROW][C]234[/C][C]0.884862[/C][C]0.230276[/C][C]0.115138[/C][/ROW]
[ROW][C]235[/C][C]0.887711[/C][C]0.224578[/C][C]0.112289[/C][/ROW]
[ROW][C]236[/C][C]0.872215[/C][C]0.255571[/C][C]0.127785[/C][/ROW]
[ROW][C]237[/C][C]0.885808[/C][C]0.228385[/C][C]0.114192[/C][/ROW]
[ROW][C]238[/C][C]0.910237[/C][C]0.179526[/C][C]0.089763[/C][/ROW]
[ROW][C]239[/C][C]0.889862[/C][C]0.220275[/C][C]0.110138[/C][/ROW]
[ROW][C]240[/C][C]0.870562[/C][C]0.258875[/C][C]0.129438[/C][/ROW]
[ROW][C]241[/C][C]0.86456[/C][C]0.27088[/C][C]0.13544[/C][/ROW]
[ROW][C]242[/C][C]0.860295[/C][C]0.27941[/C][C]0.139705[/C][/ROW]
[ROW][C]243[/C][C]0.944413[/C][C]0.111174[/C][C]0.0555868[/C][/ROW]
[ROW][C]244[/C][C]0.940072[/C][C]0.119856[/C][C]0.059928[/C][/ROW]
[ROW][C]245[/C][C]0.93999[/C][C]0.12002[/C][C]0.0600101[/C][/ROW]
[ROW][C]246[/C][C]0.924326[/C][C]0.151349[/C][C]0.0756745[/C][/ROW]
[ROW][C]247[/C][C]0.903379[/C][C]0.193243[/C][C]0.0966214[/C][/ROW]
[ROW][C]248[/C][C]0.888325[/C][C]0.22335[/C][C]0.111675[/C][/ROW]
[ROW][C]249[/C][C]0.864835[/C][C]0.27033[/C][C]0.135165[/C][/ROW]
[ROW][C]250[/C][C]0.853277[/C][C]0.293446[/C][C]0.146723[/C][/ROW]
[ROW][C]251[/C][C]0.838803[/C][C]0.322394[/C][C]0.161197[/C][/ROW]
[ROW][C]252[/C][C]0.905594[/C][C]0.188813[/C][C]0.0944065[/C][/ROW]
[ROW][C]253[/C][C]0.879109[/C][C]0.241783[/C][C]0.120891[/C][/ROW]
[ROW][C]254[/C][C]0.850329[/C][C]0.299342[/C][C]0.149671[/C][/ROW]
[ROW][C]255[/C][C]0.820114[/C][C]0.359772[/C][C]0.179886[/C][/ROW]
[ROW][C]256[/C][C]0.780322[/C][C]0.439356[/C][C]0.219678[/C][/ROW]
[ROW][C]257[/C][C]0.733661[/C][C]0.532678[/C][C]0.266339[/C][/ROW]
[ROW][C]258[/C][C]0.678353[/C][C]0.643295[/C][C]0.321647[/C][/ROW]
[ROW][C]259[/C][C]0.628298[/C][C]0.743403[/C][C]0.371702[/C][/ROW]
[ROW][C]260[/C][C]0.626183[/C][C]0.747634[/C][C]0.373817[/C][/ROW]
[ROW][C]261[/C][C]0.560842[/C][C]0.878317[/C][C]0.439158[/C][/ROW]
[ROW][C]262[/C][C]0.496123[/C][C]0.992246[/C][C]0.503877[/C][/ROW]
[ROW][C]263[/C][C]0.550668[/C][C]0.898664[/C][C]0.449332[/C][/ROW]
[ROW][C]264[/C][C]0.482091[/C][C]0.964183[/C][C]0.517909[/C][/ROW]
[ROW][C]265[/C][C]0.480474[/C][C]0.960948[/C][C]0.519526[/C][/ROW]
[ROW][C]266[/C][C]0.902732[/C][C]0.194535[/C][C]0.0972677[/C][/ROW]
[ROW][C]267[/C][C]0.863741[/C][C]0.272517[/C][C]0.136259[/C][/ROW]
[ROW][C]268[/C][C]0.995963[/C][C]0.00807466[/C][C]0.00403733[/C][/ROW]
[ROW][C]269[/C][C]0.996968[/C][C]0.00606357[/C][C]0.00303179[/C][/ROW]
[ROW][C]270[/C][C]0.997336[/C][C]0.00532849[/C][C]0.00266425[/C][/ROW]
[ROW][C]271[/C][C]0.99982[/C][C]0.000359211[/C][C]0.000179605[/C][/ROW]
[ROW][C]272[/C][C]0.999409[/C][C]0.00118222[/C][C]0.000591112[/C][/ROW]
[ROW][C]273[/C][C]0.998036[/C][C]0.00392703[/C][C]0.00196351[/C][/ROW]
[ROW][C]274[/C][C]0.995935[/C][C]0.00813073[/C][C]0.00406537[/C][/ROW]
[ROW][C]275[/C][C]0.994507[/C][C]0.0109858[/C][C]0.00549291[/C][/ROW]
[ROW][C]276[/C][C]0.98265[/C][C]0.0346998[/C][C]0.0173499[/C][/ROW]
[ROW][C]277[/C][C]0.971434[/C][C]0.0571329[/C][C]0.0285664[/C][/ROW]
[ROW][C]278[/C][C]0.888169[/C][C]0.223663[/C][C]0.111831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268645&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268645&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
90.9427760.1144490.0572244
100.9007750.1984490.0992247
110.9134330.1731340.0865672
120.8632640.2734710.136736
130.8919840.2160310.108016
140.8405660.3188680.159434
150.7772880.4454240.222712
160.7364660.5270680.263534
170.7338770.5322460.266123
180.6706370.6587260.329363
190.5981550.8036890.401845
200.5277690.9444620.472231
210.4522740.9045480.547726
220.4952090.9904170.504791
230.4448310.8896610.555169
240.3814490.7628990.618551
250.3289780.6579550.671022
260.2742940.5485880.725706
270.2341760.4683530.765824
280.1935630.3871260.806437
290.2573870.5147740.742613
300.2191490.4382980.780851
310.2013390.4026780.798661
320.1723110.3446220.827689
330.1686960.3373920.831304
340.2268080.4536160.773192
350.1936740.3873490.806326
360.2184920.4369840.781508
370.1861860.3723710.813814
380.1548810.3097620.845119
390.1304560.2609120.869544
400.137050.27410.86295
410.159050.31810.84095
420.1430380.2860750.856962
430.1940680.3881360.805932
440.1680690.3361390.831931
450.1537620.3075240.846238
460.1345860.2691720.865414
470.1428260.2856530.857174
480.1226270.2452540.877373
490.1060080.2120160.893992
500.1288080.2576150.871192
510.1401430.2802870.859857
520.1430850.286170.856915
530.1259760.2519520.874024
540.1302710.2605430.869729
550.1207640.2415280.879236
560.1194890.2389790.880511
570.1175570.2351130.882443
580.1034310.2068620.896569
590.1631480.3262960.836852
600.1980270.3960540.801973
610.1713340.3426680.828666
620.1816380.3632750.818362
630.1877120.3754250.812288
640.1775640.3551280.822436
650.1798440.3596870.820156
660.2249670.4499330.775033
670.2191040.4382080.780896
680.1924830.3849670.807517
690.1918190.3836380.808181
700.1789840.3579680.821016
710.1838180.3676360.816182
720.1715630.3431260.828437
730.155980.3119590.84402
740.1393290.2786580.860671
750.1251930.2503850.874807
760.1326320.2652650.867368
770.2206960.4413910.779304
780.2096920.4193830.790308
790.1987940.3975890.801206
800.1908990.3817970.809101
810.1894770.3789530.810523
820.1666440.3332870.833356
830.1962740.3925480.803726
840.1728110.3456210.827189
850.1914460.3828930.808554
860.1699320.3398630.830068
870.2900840.5801680.709916
880.2709770.5419540.729023
890.2464730.4929470.753527
900.2199270.4398530.780073
910.1966190.3932380.803381
920.1861960.3723920.813804
930.1956060.3912120.804394
940.2047980.4095960.795202
950.3010950.6021910.698905
960.3034820.6069650.696518
970.2975720.5951440.702428
980.3200460.6400920.679954
990.3143050.6286090.685695
1000.398970.7979410.60103
1010.383170.766340.61683
1020.4295090.8590180.570491
1030.4872570.9745150.512743
1040.4594230.9188460.540577
1050.4429810.8859630.557019
1060.4453190.8906370.554681
1070.4634840.9269680.536516
1080.4958490.9916990.504151
1090.5219370.9561270.478063
1100.5398640.9202720.460136
1110.736220.527560.26378
1120.7734550.453090.226545
1130.7815310.4369380.218469
1140.7780040.4439930.221996
1150.7684210.4631570.231579
1160.8184950.363010.181505
1170.8111020.3777970.188898
1180.8893780.2212440.110622
1190.9229460.1541080.0770541
1200.9153030.1693940.0846971
1210.945460.109080.0545399
1220.9421210.1157570.0578786
1230.953860.09227910.0461396
1240.9621570.07568670.0378434
1250.9676780.06464460.0323223
1260.9689360.06212860.0310643
1270.9808910.03821710.0191085
1280.9838730.03225380.0161269
1290.9809760.03804710.0190236
1300.9803970.03920560.0196028
1310.9788410.0423170.0211585
1320.9775190.04496150.0224807
1330.976180.04764020.0238201
1340.9776430.0447140.022357
1350.9764580.0470850.0235425
1360.978530.04294080.0214704
1370.9747580.05048340.0252417
1380.9697270.06054520.0302726
1390.9648870.07022580.0351129
1400.9751540.04969280.0248464
1410.9753050.04939050.0246953
1420.9728280.0543450.0271725
1430.9677370.06452620.0322631
1440.9642860.07142720.0357136
1450.9831170.03376690.0168834
1460.9825250.03494940.0174747
1470.9824650.03506960.0175348
1480.9813080.03738470.0186923
1490.9786230.0427540.021377
1500.9792920.04141650.0207083
1510.9757710.04845820.0242291
1520.9741690.0516630.0258315
1530.9698040.0603910.0301955
1540.9658670.06826650.0341332
1550.9643240.07135220.0356761
1560.9875130.02497490.0124875
1570.9862160.02756860.0137843
1580.9865770.02684570.0134229
1590.9836190.0327620.016381
1600.9842310.0315380.015769
1610.9809020.03819510.0190976
1620.9802340.03953270.0197664
1630.976860.04627910.0231395
1640.9751020.04979520.0248976
1650.9707480.05850340.0292517
1660.9806870.03862670.0193133
1670.977540.04491940.0224597
1680.9785710.04285730.0214287
1690.9959310.008137010.0040685
1700.9968630.006273510.00313676
1710.995930.008140460.00407023
1720.9958870.00822670.00411335
1730.9973330.005334190.00266709
1740.9965530.00689470.00344735
1750.9967010.006597180.00329859
1760.9960330.007933150.00396657
1770.997320.005360910.00268045
1780.9970370.005925310.00296266
1790.996160.007680670.00384033
1800.9950730.009854960.00492748
1810.9959120.008175590.00408779
1820.995380.009240480.00462024
1830.9953440.009312850.00465643
1840.9947760.01044850.00522427
1850.9959450.008109810.00405491
1860.9955680.008863810.00443191
1870.9945970.01080510.00540257
1880.9937240.01255120.00627558
1890.992160.01568040.00784021
1900.9918550.01629010.00814506
1910.9904160.01916780.00958389
1920.9949060.01018870.00509434
1930.9937350.01253070.00626533
1940.9924930.01501490.00750747
1950.9903940.01921260.00960628
1960.9880750.02385020.0119251
1970.9859720.02805530.0140276
1980.9841760.03164870.0158244
1990.9901840.0196320.00981599
2000.988190.02361980.0118099
2010.986750.02649940.0132497
2020.9865440.0269120.013456
2030.9827580.0344850.0172425
2040.9838290.03234170.0161709
2050.9833480.03330460.0166523
2060.9806230.03875360.0193768
2070.9793010.04139790.0206989
2080.976910.04618090.0230905
2090.9716660.05666840.0283342
2100.9660820.06783690.0339184
2110.974760.05048040.0252402
2120.9719770.05604680.0280234
2130.9705850.05882980.0294149
2140.9631270.07374630.0368732
2150.9591470.08170640.0408532
2160.9525030.09499430.0474972
2170.9428970.1142050.0571027
2180.933440.1331190.0665596
2190.9447150.1105690.0552846
2200.9364760.1270470.0635236
2210.9324720.1350560.0675281
2220.9207310.1585380.0792688
2230.9176380.1647250.0823623
2240.9044460.1911080.0955542
2250.8924320.2151360.107568
2260.8705810.2588380.129419
2270.8459080.3081850.154092
2280.8311160.3377670.168884
2290.8498230.3003540.150177
2300.8245080.3509840.175492
2310.8239290.3521420.176071
2320.8076740.3846530.192326
2330.8694930.2610130.130507
2340.8848620.2302760.115138
2350.8877110.2245780.112289
2360.8722150.2555710.127785
2370.8858080.2283850.114192
2380.9102370.1795260.089763
2390.8898620.2202750.110138
2400.8705620.2588750.129438
2410.864560.270880.13544
2420.8602950.279410.139705
2430.9444130.1111740.0555868
2440.9400720.1198560.059928
2450.939990.120020.0600101
2460.9243260.1513490.0756745
2470.9033790.1932430.0966214
2480.8883250.223350.111675
2490.8648350.270330.135165
2500.8532770.2934460.146723
2510.8388030.3223940.161197
2520.9055940.1888130.0944065
2530.8791090.2417830.120891
2540.8503290.2993420.149671
2550.8201140.3597720.179886
2560.7803220.4393560.219678
2570.7336610.5326780.266339
2580.6783530.6432950.321647
2590.6282980.7434030.371702
2600.6261830.7476340.373817
2610.5608420.8783170.439158
2620.4961230.9922460.503877
2630.5506680.8986640.449332
2640.4820910.9641830.517909
2650.4804740.9609480.519526
2660.9027320.1945350.0972677
2670.8637410.2725170.136259
2680.9959630.008074660.00403733
2690.9969680.006063570.00303179
2700.9973360.005328490.00266425
2710.999820.0003592110.000179605
2720.9994090.001182220.000591112
2730.9980360.003927030.00196351
2740.9959350.008130730.00406537
2750.9945070.01098580.00549291
2760.982650.03469980.0173499
2770.9714340.05713290.0285664
2780.8881690.2236630.111831






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level240.0888889NOK
5% type I error level800.296296NOK
10% type I error level1040.385185NOK

\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 & 24 & 0.0888889 & NOK \tabularnewline
5% type I error level & 80 & 0.296296 & NOK \tabularnewline
10% type I error level & 104 & 0.385185 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268645&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]24[/C][C]0.0888889[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]80[/C][C]0.296296[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]104[/C][C]0.385185[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268645&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268645&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 level240.0888889NOK
5% type I error level800.296296NOK
10% type I error level1040.385185NOK


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):
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')
}