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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, 05 Nov 2012 08:18:55 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/05/t13521215663p0ewxw83xne9mj.htm/, Retrieved Sun, 29 Jun 2025 20:14:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=186039, Retrieved Sun, 29 Jun 2025 20:14:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact240

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Decreasing Compet...] [2010-11-17 09:04:39] [b98453cac15ba1066b407e146608df68]
- R  D  [Multiple Regression] [Maand effect] [2012-11-05 13:06:01] [8fc56f6caf42131500698d1cf21d4abb]
-    D    [Multiple Regression] [maand en determin...] [2012-11-05 13:16:07] [8fc56f6caf42131500698d1cf21d4abb]
-   PD        [Multiple Regression] [t-effect] [2012-11-05 13:18:55] [4c917d823355d00d361b7013e9f37760] [Current]
-   PD          [Multiple Regression] [laatste model] [2012-11-05 13:28:26] [8fc56f6caf42131500698d1cf21d4abb]
-  M              [Multiple Regression] [MR multicollinari...] [2012-11-26 19:56:40] [8fc56f6caf42131500698d1cf21d4abb]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41	38	13	12	14	12	53	32	1
39	32	16	11	18	11	83	51	2
30	35	19	15	11	14	66	42	3
31	33	15	6	12	12	67	41	4
34	37	14	13	16	21	76	46	5
35	29	13	10	18	12	78	47	6
39	31	19	12	14	22	53	37	7
34	36	15	14	14	11	80	49	8
36	35	14	12	15	10	74	45	9
37	38	15	9	15	13	76	47	10
38	31	16	10	17	10	79	49	11
36	34	16	12	19	8	54	33	12
38	35	16	12	10	15	67	42	13
39	38	16	11	16	14	54	33	14
33	37	17	15	18	10	87	53	15
32	33	15	12	14	14	58	36	16
36	32	15	10	14	14	75	45	17
38	38	20	12	17	11	88	54	18
39	38	18	11	14	10	64	41	19
32	32	16	12	16	13	57	36	20
32	33	16	11	18	9.5	66	41	21
31	31	16	12	11	14	68	44	22
39	38	19	13	14	12	54	33	23
37	39	16	11	12	14	56	37	24
39	32	17	12	17	11	86	52	25
41	32	17	13	9	9	80	47	26
36	35	16	10	16	11	76	43	27
33	37	15	14	14	15	69	44	28
33	33	16	12	15	14	78	45	29
34	33	14	10	11	13	67	44	30
31	31	15	12	16	9	80	49	31
27	32	12	8	13	15	54	33	32
37	31	14	10	17	10	71	43	33
34	37	16	12	15	11	84	54	34
34	30	14	12	14	13	74	42	35
32	33	10	7	16	8	71	44	36
29	31	10	9	9	20	63	37	37
36	33	14	12	15	12	71	43	38
29	31	16	10	17	10	76	46	39
35	33	16	10	13	10	69	42	40
37	32	16	10	15	9	74	45	41
34	33	14	12	16	14	75	44	42
38	32	20	15	16	8	54	33	43
35	33	14	10	12	14	52	31	44
38	28	14	10	15	11	69	42	45
37	35	11	12	11	13	68	40	46
38	39	14	13	15	9	65	43	47
33	34	15	11	15	11	75	46	48
36	38	16	11	17	15	74	42	49
38	32	14	12	13	11	75	45	50
32	38	16	14	16	10	72	44	51
32	30	14	10	14	14	67	40	52
32	33	12	12	11	18	63	37	53
34	38	16	13	12	14	62	46	54
32	32	9	5	12	11	63	36	55
37	35	14	6	15	14.5	76	47	56
39	34	16	12	16	13	74	45	57
29	34	16	12	15	9	67	42	58
37	36	15	11	12	10	73	43	59
35	34	16	10	12	15	70	43	60
30	28	12	7	8	20	53	32	61
38	34	16	12	13	12	77	45	62
34	35	16	14	11	12	80	48	63
31	35	14	11	14	14	52	31	64
34	31	16	12	15	13	54	33	65
35	37	17	13	10	11	80	49	66
36	35	18	14	11	17	66	42	67
30	27	18	11	12	12	73	41	68
39	40	12	12	15	13	63	38	69
35	37	16	12	15	14	69	42	70
38	36	10	8	14	13	67	44	71
31	38	14	11	16	15	54	33	72
34	39	18	14	15	13	81	48	73
38	41	18	14	15	10	69	40	74
34	27	16	12	13	11	84	50	75
39	30	17	9	12	19	80	49	76
37	37	16	13	17	13	70	43	77
34	31	16	11	13	17	69	44	78
28	31	13	12	15	13	77	47	79
37	27	16	12	13	9	54	33	80
33	36	16	12	15	11	79	46	81
35	37	16	12	15	9	71	45	82
37	33	15	12	16	12	73	43	83
32	34	15	11	15	12	72	44	84
33	31	16	10	14	13	77	47	85
38	39	14	9	15	13	75	45	86
33	34	16	12	14	12	69	42	87
29	32	16	12	13	15	54	33	88
33	33	15	12	7	22	70	43	89
31	36	12	9	17	13	73	46	90
36	32	17	15	13	15	54	33	91
35	41	16	12	15	13	77	46	92
32	28	15	12	14	15	82	48	93
29	30	13	12	13	12.5	80	47	94
39	36	16	10	16	11	80	47	95
37	35	16	13	12	16	69	43	96
35	31	16	9	14	11	78	46	97
37	34	16	12	17	11	81	48	98
32	36	14	10	15	10	76	46	99
38	36	16	14	17	10	76	45	100
37	35	16	11	12	16	73	45	101
36	37	20	15	16	12	85	52	102
32	28	15	11	11	11	66	42	103
33	39	16	11	15	16	79	47	104
40	32	13	12	9	19	68	41	105
38	35	17	12	16	11	76	47	106
41	39	16	12	15	16	71	43	107
36	35	16	11	10	15	54	33	108
43	42	12	7	10	24	46	30	109
30	34	16	12	15	14	85	52	110
31	33	16	14	11	15	74	44	111
32	41	17	11	13	11	88	55	112
32	33	13	11	14	15	38	11	113
37	34	12	10	18	12	76	47	114
37	32	18	13	16	10	86	53	115
33	40	14	13	14	14	54	33	116
34	40	14	8	14	13	67	44	117
33	35	13	11	14	9	69	42	118
38	36	16	12	14	15	90	55	119
33	37	13	11	12	15	54	33	120
31	27	16	13	14	14	76	46	121
38	39	13	12	15	11	89	54	122
37	38	16	14	15	8	76	47	123
36	31	15	13	15	11	73	45	124
31	33	16	15	13	11	79	47	125
39	32	15	10	17	8	90	55	126
44	39	17	11	17	10	74	44	127
33	36	15	9	19	11	81	53	128
35	33	12	11	15	13	72	44	129
32	33	16	10	13	11	71	42	130
28	32	10	11	9	20	66	40	131
40	37	16	8	15	10	77	46	132
27	30	12	11	15	15	65	40	133
37	38	14	12	15	12	74	46	134
32	29	15	12	16	14	85	53	135
28	22	13	9	11	23	54	33	136
34	35	15	11	14	14	63	42	137
30	35	11	10	11	16	54	35	138
35	34	12	8	15	11	64	40	139
31	35	11	9	13	12	69	41	140
32	34	16	8	15	10	54	33	141
30	37	15	9	16	14	84	51	142
30	35	17	15	14	12	86	53	143
31	23	16	11	15	12	77	46	144
40	31	10	8	16	11	89	55	145
32	27	18	13	16	12	76	47	146
36	36	13	12	11	13	60	38	147
32	31	16	12	12	11	75	46	148
35	32	13	9	9	19	73	46	149
38	39	10	7	16	12	85	53	150
42	37	15	13	13	17	79	47	151
34	38	16	9	16	9	71	41	152
35	39	16	6	12	12	72	44	153
38	34	14	8	9	19	69	43	154
33	31	10	8	13	18	78	51	155
36	32	17	15	13	15	54	33	156
32	37	13	6	14	14	69	43	157
33	36	15	9	19	11	81	53	158
34	32	16	11	13	9	84	51	159
32	38	12	8	12	18	84	50	160
34	36	13	8	13	16	69	46	161
27	26	13	10	10	24	66	43	162
31	26	12	8	14	14	81	47	163
38	33	17	14	16	20	82	50	164
34	39	15	10	10	18	72	43	165
24	30	10	8	11	23	54	33	166
30	33	14	11	14	12	78	48	167
26	25	11	12	12	14	74	44	168
34	38	13	12	9	16	82	50	169
27	37	16	12	9	18	73	41	170
37	31	12	5	11	20	55	34	171
36	37	16	12	16	12	72	44	172
41	35	12	10	9	12	78	47	173
29	25	9	7	13	17	59	35	174
36	28	12	12	16	13	72	44	175
32	35	15	11	13	9	78	44	176
37	33	12	8	9	16	68	43	177
30	30	12	9	12	18	69	41	178
31	31	14	10	16	10	67	41	179
38	37	12	9	11	14	74	42	180
36	36	16	12	14	11	54	33	181
35	30	11	6	13	9	67	41	182
31	36	19	15	15	11	70	44	183
38	32	15	12	14	10	80	48	184
22	28	8	12	16	11	89	55	185
32	36	16	12	13	19	76	44	186
36	34	17	11	14	14	74	43	187
39	31	12	7	15	12	87	52	188
28	28	11	7	13	14	54	30	189
32	36	11	5	11	21	61	39	190
32	36	14	12	11	13	38	11	191
38	40	16	12	14	10	75	44	192
32	33	12	3	15	15	69	42	193
35	37	16	11	11	16	62	41	194
32	32	13	10	15	14	72	44	195
37	38	15	12	12	12	70	44	196
34	31	16	9	14	19	79	48	197
33	37	16	12	14	15	87	53	198
33	33	14	9	8	19	62	37	199
26	32	16	12	13	13	77	44	200
30	30	16	12	9	17	69	44	201
24	30	14	10	15	12	69	40	202
34	31	11	9	17	11	75	42	203
34	32	12	12	13	14	54	35	204
33	34	15	8	15	11	72	43	205
34	36	15	11	15	13	74	45	206
35	37	16	11	14	12	85	55	207
35	36	16	12	16	15	52	31	208
36	33	11	10	13	14	70	44	209
34	33	15	10	16	12	84	50	210
34	33	12	12	9	17	64	40	211
41	44	12	12	16	11	84	53	212
32	39	15	11	11	18	87	54	213
30	32	15	8	10	13	79	49	214
35	35	16	12	11	17	67	40	215
28	25	14	10	15	13	65	41	216
33	35	17	11	17	11	85	52	217
39	34	14	10	14	12	83	52	218
36	35	13	8	8	22	61	36	219
36	39	15	12	15	14	82	52	220
35	33	13	12	11	12	76	46	221
38	36	14	10	16	12	58	31	222
33	32	15	12	10	17	72	44	223
31	32	12	9	15	9	72	44	224
34	36	13	9	9	21	38	11	225
32	36	8	6	16	10	78	46	226
31	32	14	10	19	11	54	33	227
33	34	14	9	12	12	63	34	228
34	33	11	9	8	23	66	42	229
34	35	12	9	11	13	70	43	230
34	30	13	6	14	12	71	43	231
33	38	10	10	9	16	67	44	232
32	34	16	6	15	9	58	36	233
41	33	18	14	13	17	72	46	234
34	32	13	10	16	9	72	44	235
36	31	11	10	11	14	70	43	236
37	30	4	6	12	17	76	50	237
36	27	13	12	13	13	50	33	238
29	31	16	12	10	11	72	43	239
37	30	10	7	11	12	72	44	240
27	32	12	8	12	10	88	53	241
35	35	12	11	8	19	53	34	242
28	28	10	3	12	16	58	35	243
35	33	13	6	12	16	66	40	244
37	31	15	10	15	14	82	53	245
29	35	12	8	11	20	69	42	246
32	35	14	9	13	15	68	43	247
36	32	10	9	14	23	44	29	248
19	21	12	8	10	20	56	36	249
21	20	12	9	12	16	53	30	250
31	34	11	7	15	14	70	42	251
33	32	10	7	13	17	78	47	252
36	34	12	6	13	11	71	44	253
33	32	16	9	13	13	72	45	254
37	33	12	10	12	17	68	44	255
34	33	14	11	12	15	67	43	256
35	37	16	12	9	21	75	43	257
31	32	14	8	9	18	62	40	258
37	34	13	11	15	15	67	41	259
35	30	4	3	10	8	83	52	260
27	30	15	11	14	12	64	38	261
34	38	11	12	15	12	68	41	262
40	36	11	7	7	22	62	39	263
29	32	14	9	14	12	72	43	264

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 14 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186039&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186039&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186039&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 time14 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 5.33462704912005 + 0.0334318102550329Connected[t] + 0.0429100015092721Separate[t] + 0.557382329522837Software[t] + 0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] + 0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  5.33462704912005 +  0.0334318102550329Connected[t] +  0.0429100015092721Separate[t] +  0.557382329522837Software[t] +  0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] +  0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186039&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  5.33462704912005 +  0.0334318102550329Connected[t] +  0.0429100015092721Separate[t] +  0.557382329522837Software[t] +  0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] +  0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186039&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186039&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
Learning[t] = + 5.33462704912005 + 0.0334318102550329Connected[t] + 0.0429100015092721Separate[t] + 0.557382329522837Software[t] + 0.0707136347126803Happiness[t] -0.0289876371504571Depression[t] + 0.0235641874876029Belonging[t] -0.0252595092689673Belonging_Final[t] -0.0049379405910949t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.334627049120051.9627922.71790.0070210.00351
Connected0.03343181025503290.034590.96650.3347060.167353
Separate0.04291000150927210.0351321.22140.2230680.111534
Software0.5573823295228370.05386410.347900
Happiness0.07071363471268030.0579091.22110.223170.111585
Depression-0.02898763715045710.042089-0.68870.491620.24581
Belonging0.02356418748760290.0373860.63030.5290610.264531
Belonging_Final-0.02525950926896730.05566-0.45380.6503470.325173
t-0.00493794059109490.001684-2.93260.0036670.001834

\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) & 5.33462704912005 & 1.962792 & 2.7179 & 0.007021 & 0.00351 \tabularnewline
Connected & 0.0334318102550329 & 0.03459 & 0.9665 & 0.334706 & 0.167353 \tabularnewline
Separate & 0.0429100015092721 & 0.035132 & 1.2214 & 0.223068 & 0.111534 \tabularnewline
Software & 0.557382329522837 & 0.053864 & 10.3479 & 0 & 0 \tabularnewline
Happiness & 0.0707136347126803 & 0.057909 & 1.2211 & 0.22317 & 0.111585 \tabularnewline
Depression & -0.0289876371504571 & 0.042089 & -0.6887 & 0.49162 & 0.24581 \tabularnewline
Belonging & 0.0235641874876029 & 0.037386 & 0.6303 & 0.529061 & 0.264531 \tabularnewline
Belonging_Final & -0.0252595092689673 & 0.05566 & -0.4538 & 0.650347 & 0.325173 \tabularnewline
t & -0.0049379405910949 & 0.001684 & -2.9326 & 0.003667 & 0.001834 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186039&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]5.33462704912005[/C][C]1.962792[/C][C]2.7179[/C][C]0.007021[/C][C]0.00351[/C][/ROW]
[ROW][C]Connected[/C][C]0.0334318102550329[/C][C]0.03459[/C][C]0.9665[/C][C]0.334706[/C][C]0.167353[/C][/ROW]
[ROW][C]Separate[/C][C]0.0429100015092721[/C][C]0.035132[/C][C]1.2214[/C][C]0.223068[/C][C]0.111534[/C][/ROW]
[ROW][C]Software[/C][C]0.557382329522837[/C][C]0.053864[/C][C]10.3479[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0707136347126803[/C][C]0.057909[/C][C]1.2211[/C][C]0.22317[/C][C]0.111585[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0289876371504571[/C][C]0.042089[/C][C]-0.6887[/C][C]0.49162[/C][C]0.24581[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0235641874876029[/C][C]0.037386[/C][C]0.6303[/C][C]0.529061[/C][C]0.264531[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0252595092689673[/C][C]0.05566[/C][C]-0.4538[/C][C]0.650347[/C][C]0.325173[/C][/ROW]
[ROW][C]t[/C][C]-0.0049379405910949[/C][C]0.001684[/C][C]-2.9326[/C][C]0.003667[/C][C]0.001834[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186039&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186039&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)5.334627049120051.9627922.71790.0070210.00351
Connected0.03343181025503290.034590.96650.3347060.167353
Separate0.04291000150927210.0351321.22140.2230680.111534
Software0.5573823295228370.05386410.347900
Happiness0.07071363471268030.0579091.22110.223170.111585
Depression-0.02898763715045710.042089-0.68870.491620.24581
Belonging0.02356418748760290.0373860.63030.5290610.264531
Belonging_Final-0.02525950926896730.05566-0.45380.6503470.325173
t-0.00493794059109490.001684-2.93260.0036670.001834






Multiple Linear Regression - Regression Statistics
Multiple R0.667548376503906
R-squared0.445620834973
Adjusted R-squared0.428228547442742
F-TEST (value)25.6217495368402
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85709761762755
Sum Squared Residuals879.446948156467

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.667548376503906 \tabularnewline
R-squared & 0.445620834973 \tabularnewline
Adjusted R-squared & 0.428228547442742 \tabularnewline
F-TEST (value) & 25.6217495368402 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.85709761762755 \tabularnewline
Sum Squared Residuals & 879.446948156467 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186039&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.667548376503906[/C][/ROW]
[ROW][C]R-squared[/C][C]0.445620834973[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.428228547442742[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]25.6217495368402[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/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]1.85709761762755[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]879.446948156467[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186039&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186039&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 R0.667548376503906
R-squared0.445620834973
Adjusted R-squared0.428228547442742
F-TEST (value)25.6217495368402
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85709761762755
Sum Squared Residuals879.446948156467






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.1022982210197-3.10229822101972
21615.7544914458590.245508554141014
31917.05171257728311.94828742271692
41512.15545808399312.84454191600689
51416.4318778324043-2.43187783240426
61314.8691295709112-1.86912957091122
71915.28926302854883.71073697145122
81517.0984636628673-2.09846366286726
91416.0620688662447-2.06206886624467
101514.45679219685380.543207803146187
111614.99086211027731.00913788972271
121616.1770052175893-0.177005217589299
131615.52150358046840.478496419531648
141615.49561571664570.504384283354324
151718.0065120508452-1.0065120508452
161515.4716004383729-0.471600438372882
171514.61597068211550.384029317884485
182016.42822369964333.57177630035666
191815.4790150935912.52098490640904
201615.55578939358740.444210606412555
211615.36504326547830.634956734521665
221615.1441458781390.855854121861016
231916.48248691524712.51751308475295
241615.08551849078250.914481509217452
251716.17302056026780.826979439732198
261716.26950718772830.730492812271699
271614.99779466763471.00220533236535
281516.760323977679-1.76032397767898
291615.75550082198770.244499178012286
301414.181416577811-0.181416577811048
311515.7546834756412-0.754683475641216
321212.8348155240329-0.83481552403293
331414.8118391627312-0.81183916273115
341615.93689538828060.063104611719357
351415.5703707644626-1.57037076446263
361013.005541434452-3.005541434452
371013.0747086953106-3.07470869531064
381415.7548997678586-1.75489976785859
391614.55679944677541.44320055322457
401614.4915065565451.508493443455
411614.72297955116161.27702044883837
421415.7500199860774-1.75001998607735
432017.46497876118732.53502123881265
441414.1623540255355-0.162354025535507
451414.4650019090832-0.465001909083171
461115.5278918457463-4.52789184574632
471416.537742048153-2.53774204815302
481515.1382184624629-0.13821846246294
491615.50816652908580.491833470914169
501415.6508961989038-1.65089619890381
511617.0132875529785-1.01328755297849
521414.1613795638325-0.161379563832531
531215.0533666119315-3.05336661193155
541615.82298904132590.177010958674083
55911.3977910266151-2.39779102661507
561412.38528848084141.61471151915857
571615.86618387038930.133816129610749
581615.48299395653070.517006043469343
591515.1489452458437-0.148945245843684
601614.2183106039861.78168939601395
611211.5660773045620.433922695437972
621615.6956016526540.304398347346031
631616.5680978968282-0.568097896828235
641414.7144975746602-0.71449757466022
651615.29190801662040.70809198337962
661716.04816805197450.9518319480255
671816.2919300000091.708069999991
681814.47683483939223.52316516060783
691215.9112854601582-3.9112854601582
701615.65524972471850.344750275281548
711013.3387945042165-3.33879450421647
721414.9127730431715-0.912773043171451
731816.96778958614221.03221041385776
741817.18866762534170.811332374658303
751615.26495057660350.73504942339646
761713.51214273064913.48785726935087
771616.4136496754081-0.413649675408144
781614.48856285174151.51143714825848
791315.2105291692642-2.21052916926418
801615.12101761165840.878982388341565
811615.71272550544860.287274494551398
821615.71228247054590.287717529454097
831515.6839662612022-0.683966261202235
841514.87785960985320.12214039014684
851614.16258228323441.83741771676558
861414.1848053547452-0.184805354745237
871615.36297274922020.637027250779809
881614.8546837895331.14531621046697
891514.5236197302540.476380269745968
901213.871340301249-1.871340301249
911716.74603962811350.253960371886512
921615.83471813772690.165281862273136
931515.1102677566366-0.110267756636619
941315.0707409807562-2.07074098075619
951614.79843885258911.20156114741089
961615.76991352865640.230086471343579
971613.7196072581862.28039274181401
981615.81472437926420.185275620735792
991414.4339411801958-0.433941180195834
1001617.0258101979206-1.02581019792061
1011614.67419689806771.32580310193225
1022017.45593524075252.54406475924747
1031514.18184572147880.818154278521223
1041615.00030285183710.999697148162855
1051314.8675061755119-1.86750617551193
1061715.6882876034181.31171239658197
1071615.7228503788020.277149621197993
1081614.34915442036331.6508455796367
1091212.275456137583-0.275456137582957
1101615.28627495238360.713725047616351
1111616.0176513153709-0.0176513153709174
1121715.02670004943551.97329995056449
1131314.5664542163355-1.56645421633551
1141214.5701172401542-2.57011724015419
1151816.15213910925081.84786089074916
1161415.8505123074627-1.85051230746266
1171413.14956200204310.850437997956938
1181314.7823871743341-1.78238717433406
1191615.53744910989060.462550890109423
1201314.416850974949-1.41685097494897
1211615.39116746860730.608832531392733
1221315.839724797741-2.83972479774098
1231616.8306547434266-0.830654743426562
1241515.8273961971164-0.827396197116446
1251616.8053227042767-0.805322704276728
1261514.66496503511640.335034964883577
1271715.52779081374431.47220918625569
1281513.96166165804181.03833834195822
1291214.6840500753593-2.68405007535926
1301613.96493721040612.03506278959389
1311013.7296991647035-3.72969916470354
1321613.49015315268122.50984684731883
1331214.1462272767885-2.14622727678853
1341415.5237533235708-1.52375332357078
1351515.0605941760137-0.0605941760136943
1361312.10965546061520.890344539384808
1371514.43567480268040.564325197319618
1381113.4342499906017-2.43424999060171
1391212.975933493865-0.97593349386503
1401113.3597071648791-2.35970716487914
1411612.83592450907493.16407549092506
1421513.6572528259221.34274717407804
1431716.82394622076220.17605377923783
1441614.14344326643051.85655673356948
1451013.2656605799341-3.26566057993405
1461815.47529379854222.52470620145776
1471314.9006435559371-1.90064355593709
1481614.82750401395541.1724959860446
1491312.80245414075330.197545859246742
1501012.8872795704569-2.88727957045692
1511515.9276356858023-0.927635685802293
1521613.87570950364352.12429049635646
1531611.85293459562684.14706540437316
1541412.38801931991511.61198068008492
1551012.4090361127589-2.40903611275887
1561716.42507348969230.574926510307681
1571311.68508634140941.31491365859057
1581513.81352344030891.18647655969106
1591614.5400470100071.45995298999296
1601212.7472156095952-0.747215609595171
1611312.5995854202710.400414579728982
1621312.607333415850.392666584149958
1631212.4465137428269-0.44651374282687
1641716.23554956792630.764450432073746
1651513.69968323331091.30031676668912
1661011.6136876844136-1.61368768441355
1671414.32787037191-0.327870371910013
1681114.2106862511466-3.21068625114663
1691314.7978730780644-1.7978730780644
1701614.47328508591021.52671491408983
1711210.47964211738431.52035788261573
1721615.33387404762030.666125952379726
1731213.8661216503701-1.86612165037008
174911.3520658851189-2.35206588511894
1751214.9038825751131-2.90388257511308
1761514.55339984393330.446600156066671
1771212.2615035985194-0.261503598519359
1781212.6794441470007-0.67944414700072
1791413.77585760877590.224142391224061
1801213.3751911004819-1.37519110048189
1811614.9877821756981.01221782430197
1821111.4391784414346-0.439178441434581
1831916.65278026436492.34721973563512
1841515.1309558411913-0.130955841191348
185814.5671696852632-6.5671696852632
1861614.76730802257471.23269197742529
1871714.44667794522112.5533220547789
1881212.3914638757077-0.391463875707659
1891111.4687344908835-0.468734490883497
1901110.4193121438550.580687856145011
1911414.7132415544436-0.713241554443631
1921615.41794942817460.58205057182538
193129.73051899235562.2694810076444
1941614.0050431456041.99495685439604
1951313.6285705973993-0.62857059739933
1961514.96172237137240.0382776286276256
1971612.93352546056753.06647453943252
1981615.00292920950330.997070790496686
1991412.42901937854211.57098062145789
2001614.52343599712241.47656400287756
2011613.97908670717962.02091329282044
2021413.32905127711680.670948722883167
2031113.405240124026-2.405240124026
2041214.4275103508537-2.42751035085371
2051512.69590076643662.30409923356338
2061514.4209957098240.579004290176027
2071614.45728455310891.54271544689108
2081614.84989333386971.1501066661303
2091113.5475210272528-2.54752102725284
2101513.92417721380331.07582278619673
2111214.1753816464544-2.17538164645442
2121215.6883077893975-3.68830778939753
2131514.09950263901920.900497360980815
2141512.06719267626822.93280732373177
2151614.48700152925181.51299847074822
2161413.03059344594540.969406554054561
2171714.57212859276482.42787140723524
2181413.8792322664080.120767733591951
2191311.8737260813111.12627391868899
2201515.087549793977-0.0875497939769591
2211314.5770127002136-1.57701270021358
2221413.99464097369080.0053590263092174
2231514.19797364513460.802026354865392
2241213.039494366232-1.03949436623199
2251312.56673983965890.433260160341059
226811.6951354167233-3.69513541672332
2271413.66064136571310.339358634286859
2281412.91383981710811.08616018289194
2291112.166321626068-1.16632162606804
2301212.8182182048195-0.81821820481955
2311311.19127599688971.80872400311032
2321013.1366805948245-3.13668059482447
2331611.31433517494254.6856648250575
2341815.73040732682792.26959267317212
2351313.7135684147306-0.713568414730565
2361113.2122088681183-2.21220886811834
237410.9165827014858-6.91658270148581
2381314.0971838894582-1.09718388945817
2391614.14151468531941.8584853146806
2401011.5906760659384-1.59067606593836
2411212.1730026807329-0.173002680732853
2421213.3478370561178-1.34783705611779
243108.8118266754651.188173324535
2441310.989824356332.01017564367
2451513.51422890906581.4857710909342
2461211.81345163629220.186548363707805
2471412.70373321441011.29626678558989
2481012.3306976778834-2.33069767788343
2491210.63808867440111.36191132559894
2501211.55272899351180.447271006488222
2511111.7356777720557-0.735677772055743
2521011.5456092216354-1.54560922163543
2531211.25415942360160.745840576398441
2541612.67558244171313.32441755828694
2551213.1490026491782-1.14900264917825
2561413.66082220342720.339177796572829
2571614.22078518151111.77921481848893
2581411.49444767618162.50555232381843
2591314.0518737366042-1.05187373660423
26049.29789121761609-5.29789121761609
2611513.55737498891741.44262501108259
2621114.7763139185647-3.77631391856475
2631111.1527836332774-0.152783633277424
2641412.6426960851831.35730391481695

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.1022982210197 & -3.10229822101972 \tabularnewline
2 & 16 & 15.754491445859 & 0.245508554141014 \tabularnewline
3 & 19 & 17.0517125772831 & 1.94828742271692 \tabularnewline
4 & 15 & 12.1554580839931 & 2.84454191600689 \tabularnewline
5 & 14 & 16.4318778324043 & -2.43187783240426 \tabularnewline
6 & 13 & 14.8691295709112 & -1.86912957091122 \tabularnewline
7 & 19 & 15.2892630285488 & 3.71073697145122 \tabularnewline
8 & 15 & 17.0984636628673 & -2.09846366286726 \tabularnewline
9 & 14 & 16.0620688662447 & -2.06206886624467 \tabularnewline
10 & 15 & 14.4567921968538 & 0.543207803146187 \tabularnewline
11 & 16 & 14.9908621102773 & 1.00913788972271 \tabularnewline
12 & 16 & 16.1770052175893 & -0.177005217589299 \tabularnewline
13 & 16 & 15.5215035804684 & 0.478496419531648 \tabularnewline
14 & 16 & 15.4956157166457 & 0.504384283354324 \tabularnewline
15 & 17 & 18.0065120508452 & -1.0065120508452 \tabularnewline
16 & 15 & 15.4716004383729 & -0.471600438372882 \tabularnewline
17 & 15 & 14.6159706821155 & 0.384029317884485 \tabularnewline
18 & 20 & 16.4282236996433 & 3.57177630035666 \tabularnewline
19 & 18 & 15.479015093591 & 2.52098490640904 \tabularnewline
20 & 16 & 15.5557893935874 & 0.444210606412555 \tabularnewline
21 & 16 & 15.3650432654783 & 0.634956734521665 \tabularnewline
22 & 16 & 15.144145878139 & 0.855854121861016 \tabularnewline
23 & 19 & 16.4824869152471 & 2.51751308475295 \tabularnewline
24 & 16 & 15.0855184907825 & 0.914481509217452 \tabularnewline
25 & 17 & 16.1730205602678 & 0.826979439732198 \tabularnewline
26 & 17 & 16.2695071877283 & 0.730492812271699 \tabularnewline
27 & 16 & 14.9977946676347 & 1.00220533236535 \tabularnewline
28 & 15 & 16.760323977679 & -1.76032397767898 \tabularnewline
29 & 16 & 15.7555008219877 & 0.244499178012286 \tabularnewline
30 & 14 & 14.181416577811 & -0.181416577811048 \tabularnewline
31 & 15 & 15.7546834756412 & -0.754683475641216 \tabularnewline
32 & 12 & 12.8348155240329 & -0.83481552403293 \tabularnewline
33 & 14 & 14.8118391627312 & -0.81183916273115 \tabularnewline
34 & 16 & 15.9368953882806 & 0.063104611719357 \tabularnewline
35 & 14 & 15.5703707644626 & -1.57037076446263 \tabularnewline
36 & 10 & 13.005541434452 & -3.005541434452 \tabularnewline
37 & 10 & 13.0747086953106 & -3.07470869531064 \tabularnewline
38 & 14 & 15.7548997678586 & -1.75489976785859 \tabularnewline
39 & 16 & 14.5567994467754 & 1.44320055322457 \tabularnewline
40 & 16 & 14.491506556545 & 1.508493443455 \tabularnewline
41 & 16 & 14.7229795511616 & 1.27702044883837 \tabularnewline
42 & 14 & 15.7500199860774 & -1.75001998607735 \tabularnewline
43 & 20 & 17.4649787611873 & 2.53502123881265 \tabularnewline
44 & 14 & 14.1623540255355 & -0.162354025535507 \tabularnewline
45 & 14 & 14.4650019090832 & -0.465001909083171 \tabularnewline
46 & 11 & 15.5278918457463 & -4.52789184574632 \tabularnewline
47 & 14 & 16.537742048153 & -2.53774204815302 \tabularnewline
48 & 15 & 15.1382184624629 & -0.13821846246294 \tabularnewline
49 & 16 & 15.5081665290858 & 0.491833470914169 \tabularnewline
50 & 14 & 15.6508961989038 & -1.65089619890381 \tabularnewline
51 & 16 & 17.0132875529785 & -1.01328755297849 \tabularnewline
52 & 14 & 14.1613795638325 & -0.161379563832531 \tabularnewline
53 & 12 & 15.0533666119315 & -3.05336661193155 \tabularnewline
54 & 16 & 15.8229890413259 & 0.177010958674083 \tabularnewline
55 & 9 & 11.3977910266151 & -2.39779102661507 \tabularnewline
56 & 14 & 12.3852884808414 & 1.61471151915857 \tabularnewline
57 & 16 & 15.8661838703893 & 0.133816129610749 \tabularnewline
58 & 16 & 15.4829939565307 & 0.517006043469343 \tabularnewline
59 & 15 & 15.1489452458437 & -0.148945245843684 \tabularnewline
60 & 16 & 14.218310603986 & 1.78168939601395 \tabularnewline
61 & 12 & 11.566077304562 & 0.433922695437972 \tabularnewline
62 & 16 & 15.695601652654 & 0.304398347346031 \tabularnewline
63 & 16 & 16.5680978968282 & -0.568097896828235 \tabularnewline
64 & 14 & 14.7144975746602 & -0.71449757466022 \tabularnewline
65 & 16 & 15.2919080166204 & 0.70809198337962 \tabularnewline
66 & 17 & 16.0481680519745 & 0.9518319480255 \tabularnewline
67 & 18 & 16.291930000009 & 1.708069999991 \tabularnewline
68 & 18 & 14.4768348393922 & 3.52316516060783 \tabularnewline
69 & 12 & 15.9112854601582 & -3.9112854601582 \tabularnewline
70 & 16 & 15.6552497247185 & 0.344750275281548 \tabularnewline
71 & 10 & 13.3387945042165 & -3.33879450421647 \tabularnewline
72 & 14 & 14.9127730431715 & -0.912773043171451 \tabularnewline
73 & 18 & 16.9677895861422 & 1.03221041385776 \tabularnewline
74 & 18 & 17.1886676253417 & 0.811332374658303 \tabularnewline
75 & 16 & 15.2649505766035 & 0.73504942339646 \tabularnewline
76 & 17 & 13.5121427306491 & 3.48785726935087 \tabularnewline
77 & 16 & 16.4136496754081 & -0.413649675408144 \tabularnewline
78 & 16 & 14.4885628517415 & 1.51143714825848 \tabularnewline
79 & 13 & 15.2105291692642 & -2.21052916926418 \tabularnewline
80 & 16 & 15.1210176116584 & 0.878982388341565 \tabularnewline
81 & 16 & 15.7127255054486 & 0.287274494551398 \tabularnewline
82 & 16 & 15.7122824705459 & 0.287717529454097 \tabularnewline
83 & 15 & 15.6839662612022 & -0.683966261202235 \tabularnewline
84 & 15 & 14.8778596098532 & 0.12214039014684 \tabularnewline
85 & 16 & 14.1625822832344 & 1.83741771676558 \tabularnewline
86 & 14 & 14.1848053547452 & -0.184805354745237 \tabularnewline
87 & 16 & 15.3629727492202 & 0.637027250779809 \tabularnewline
88 & 16 & 14.854683789533 & 1.14531621046697 \tabularnewline
89 & 15 & 14.523619730254 & 0.476380269745968 \tabularnewline
90 & 12 & 13.871340301249 & -1.871340301249 \tabularnewline
91 & 17 & 16.7460396281135 & 0.253960371886512 \tabularnewline
92 & 16 & 15.8347181377269 & 0.165281862273136 \tabularnewline
93 & 15 & 15.1102677566366 & -0.110267756636619 \tabularnewline
94 & 13 & 15.0707409807562 & -2.07074098075619 \tabularnewline
95 & 16 & 14.7984388525891 & 1.20156114741089 \tabularnewline
96 & 16 & 15.7699135286564 & 0.230086471343579 \tabularnewline
97 & 16 & 13.719607258186 & 2.28039274181401 \tabularnewline
98 & 16 & 15.8147243792642 & 0.185275620735792 \tabularnewline
99 & 14 & 14.4339411801958 & -0.433941180195834 \tabularnewline
100 & 16 & 17.0258101979206 & -1.02581019792061 \tabularnewline
101 & 16 & 14.6741968980677 & 1.32580310193225 \tabularnewline
102 & 20 & 17.4559352407525 & 2.54406475924747 \tabularnewline
103 & 15 & 14.1818457214788 & 0.818154278521223 \tabularnewline
104 & 16 & 15.0003028518371 & 0.999697148162855 \tabularnewline
105 & 13 & 14.8675061755119 & -1.86750617551193 \tabularnewline
106 & 17 & 15.688287603418 & 1.31171239658197 \tabularnewline
107 & 16 & 15.722850378802 & 0.277149621197993 \tabularnewline
108 & 16 & 14.3491544203633 & 1.6508455796367 \tabularnewline
109 & 12 & 12.275456137583 & -0.275456137582957 \tabularnewline
110 & 16 & 15.2862749523836 & 0.713725047616351 \tabularnewline
111 & 16 & 16.0176513153709 & -0.0176513153709174 \tabularnewline
112 & 17 & 15.0267000494355 & 1.97329995056449 \tabularnewline
113 & 13 & 14.5664542163355 & -1.56645421633551 \tabularnewline
114 & 12 & 14.5701172401542 & -2.57011724015419 \tabularnewline
115 & 18 & 16.1521391092508 & 1.84786089074916 \tabularnewline
116 & 14 & 15.8505123074627 & -1.85051230746266 \tabularnewline
117 & 14 & 13.1495620020431 & 0.850437997956938 \tabularnewline
118 & 13 & 14.7823871743341 & -1.78238717433406 \tabularnewline
119 & 16 & 15.5374491098906 & 0.462550890109423 \tabularnewline
120 & 13 & 14.416850974949 & -1.41685097494897 \tabularnewline
121 & 16 & 15.3911674686073 & 0.608832531392733 \tabularnewline
122 & 13 & 15.839724797741 & -2.83972479774098 \tabularnewline
123 & 16 & 16.8306547434266 & -0.830654743426562 \tabularnewline
124 & 15 & 15.8273961971164 & -0.827396197116446 \tabularnewline
125 & 16 & 16.8053227042767 & -0.805322704276728 \tabularnewline
126 & 15 & 14.6649650351164 & 0.335034964883577 \tabularnewline
127 & 17 & 15.5277908137443 & 1.47220918625569 \tabularnewline
128 & 15 & 13.9616616580418 & 1.03833834195822 \tabularnewline
129 & 12 & 14.6840500753593 & -2.68405007535926 \tabularnewline
130 & 16 & 13.9649372104061 & 2.03506278959389 \tabularnewline
131 & 10 & 13.7296991647035 & -3.72969916470354 \tabularnewline
132 & 16 & 13.4901531526812 & 2.50984684731883 \tabularnewline
133 & 12 & 14.1462272767885 & -2.14622727678853 \tabularnewline
134 & 14 & 15.5237533235708 & -1.52375332357078 \tabularnewline
135 & 15 & 15.0605941760137 & -0.0605941760136943 \tabularnewline
136 & 13 & 12.1096554606152 & 0.890344539384808 \tabularnewline
137 & 15 & 14.4356748026804 & 0.564325197319618 \tabularnewline
138 & 11 & 13.4342499906017 & -2.43424999060171 \tabularnewline
139 & 12 & 12.975933493865 & -0.97593349386503 \tabularnewline
140 & 11 & 13.3597071648791 & -2.35970716487914 \tabularnewline
141 & 16 & 12.8359245090749 & 3.16407549092506 \tabularnewline
142 & 15 & 13.657252825922 & 1.34274717407804 \tabularnewline
143 & 17 & 16.8239462207622 & 0.17605377923783 \tabularnewline
144 & 16 & 14.1434432664305 & 1.85655673356948 \tabularnewline
145 & 10 & 13.2656605799341 & -3.26566057993405 \tabularnewline
146 & 18 & 15.4752937985422 & 2.52470620145776 \tabularnewline
147 & 13 & 14.9006435559371 & -1.90064355593709 \tabularnewline
148 & 16 & 14.8275040139554 & 1.1724959860446 \tabularnewline
149 & 13 & 12.8024541407533 & 0.197545859246742 \tabularnewline
150 & 10 & 12.8872795704569 & -2.88727957045692 \tabularnewline
151 & 15 & 15.9276356858023 & -0.927635685802293 \tabularnewline
152 & 16 & 13.8757095036435 & 2.12429049635646 \tabularnewline
153 & 16 & 11.8529345956268 & 4.14706540437316 \tabularnewline
154 & 14 & 12.3880193199151 & 1.61198068008492 \tabularnewline
155 & 10 & 12.4090361127589 & -2.40903611275887 \tabularnewline
156 & 17 & 16.4250734896923 & 0.574926510307681 \tabularnewline
157 & 13 & 11.6850863414094 & 1.31491365859057 \tabularnewline
158 & 15 & 13.8135234403089 & 1.18647655969106 \tabularnewline
159 & 16 & 14.540047010007 & 1.45995298999296 \tabularnewline
160 & 12 & 12.7472156095952 & -0.747215609595171 \tabularnewline
161 & 13 & 12.599585420271 & 0.400414579728982 \tabularnewline
162 & 13 & 12.60733341585 & 0.392666584149958 \tabularnewline
163 & 12 & 12.4465137428269 & -0.44651374282687 \tabularnewline
164 & 17 & 16.2355495679263 & 0.764450432073746 \tabularnewline
165 & 15 & 13.6996832333109 & 1.30031676668912 \tabularnewline
166 & 10 & 11.6136876844136 & -1.61368768441355 \tabularnewline
167 & 14 & 14.32787037191 & -0.327870371910013 \tabularnewline
168 & 11 & 14.2106862511466 & -3.21068625114663 \tabularnewline
169 & 13 & 14.7978730780644 & -1.7978730780644 \tabularnewline
170 & 16 & 14.4732850859102 & 1.52671491408983 \tabularnewline
171 & 12 & 10.4796421173843 & 1.52035788261573 \tabularnewline
172 & 16 & 15.3338740476203 & 0.666125952379726 \tabularnewline
173 & 12 & 13.8661216503701 & -1.86612165037008 \tabularnewline
174 & 9 & 11.3520658851189 & -2.35206588511894 \tabularnewline
175 & 12 & 14.9038825751131 & -2.90388257511308 \tabularnewline
176 & 15 & 14.5533998439333 & 0.446600156066671 \tabularnewline
177 & 12 & 12.2615035985194 & -0.261503598519359 \tabularnewline
178 & 12 & 12.6794441470007 & -0.67944414700072 \tabularnewline
179 & 14 & 13.7758576087759 & 0.224142391224061 \tabularnewline
180 & 12 & 13.3751911004819 & -1.37519110048189 \tabularnewline
181 & 16 & 14.987782175698 & 1.01221782430197 \tabularnewline
182 & 11 & 11.4391784414346 & -0.439178441434581 \tabularnewline
183 & 19 & 16.6527802643649 & 2.34721973563512 \tabularnewline
184 & 15 & 15.1309558411913 & -0.130955841191348 \tabularnewline
185 & 8 & 14.5671696852632 & -6.5671696852632 \tabularnewline
186 & 16 & 14.7673080225747 & 1.23269197742529 \tabularnewline
187 & 17 & 14.4466779452211 & 2.5533220547789 \tabularnewline
188 & 12 & 12.3914638757077 & -0.391463875707659 \tabularnewline
189 & 11 & 11.4687344908835 & -0.468734490883497 \tabularnewline
190 & 11 & 10.419312143855 & 0.580687856145011 \tabularnewline
191 & 14 & 14.7132415544436 & -0.713241554443631 \tabularnewline
192 & 16 & 15.4179494281746 & 0.58205057182538 \tabularnewline
193 & 12 & 9.7305189923556 & 2.2694810076444 \tabularnewline
194 & 16 & 14.005043145604 & 1.99495685439604 \tabularnewline
195 & 13 & 13.6285705973993 & -0.62857059739933 \tabularnewline
196 & 15 & 14.9617223713724 & 0.0382776286276256 \tabularnewline
197 & 16 & 12.9335254605675 & 3.06647453943252 \tabularnewline
198 & 16 & 15.0029292095033 & 0.997070790496686 \tabularnewline
199 & 14 & 12.4290193785421 & 1.57098062145789 \tabularnewline
200 & 16 & 14.5234359971224 & 1.47656400287756 \tabularnewline
201 & 16 & 13.9790867071796 & 2.02091329282044 \tabularnewline
202 & 14 & 13.3290512771168 & 0.670948722883167 \tabularnewline
203 & 11 & 13.405240124026 & -2.405240124026 \tabularnewline
204 & 12 & 14.4275103508537 & -2.42751035085371 \tabularnewline
205 & 15 & 12.6959007664366 & 2.30409923356338 \tabularnewline
206 & 15 & 14.420995709824 & 0.579004290176027 \tabularnewline
207 & 16 & 14.4572845531089 & 1.54271544689108 \tabularnewline
208 & 16 & 14.8498933338697 & 1.1501066661303 \tabularnewline
209 & 11 & 13.5475210272528 & -2.54752102725284 \tabularnewline
210 & 15 & 13.9241772138033 & 1.07582278619673 \tabularnewline
211 & 12 & 14.1753816464544 & -2.17538164645442 \tabularnewline
212 & 12 & 15.6883077893975 & -3.68830778939753 \tabularnewline
213 & 15 & 14.0995026390192 & 0.900497360980815 \tabularnewline
214 & 15 & 12.0671926762682 & 2.93280732373177 \tabularnewline
215 & 16 & 14.4870015292518 & 1.51299847074822 \tabularnewline
216 & 14 & 13.0305934459454 & 0.969406554054561 \tabularnewline
217 & 17 & 14.5721285927648 & 2.42787140723524 \tabularnewline
218 & 14 & 13.879232266408 & 0.120767733591951 \tabularnewline
219 & 13 & 11.873726081311 & 1.12627391868899 \tabularnewline
220 & 15 & 15.087549793977 & -0.0875497939769591 \tabularnewline
221 & 13 & 14.5770127002136 & -1.57701270021358 \tabularnewline
222 & 14 & 13.9946409736908 & 0.0053590263092174 \tabularnewline
223 & 15 & 14.1979736451346 & 0.802026354865392 \tabularnewline
224 & 12 & 13.039494366232 & -1.03949436623199 \tabularnewline
225 & 13 & 12.5667398396589 & 0.433260160341059 \tabularnewline
226 & 8 & 11.6951354167233 & -3.69513541672332 \tabularnewline
227 & 14 & 13.6606413657131 & 0.339358634286859 \tabularnewline
228 & 14 & 12.9138398171081 & 1.08616018289194 \tabularnewline
229 & 11 & 12.166321626068 & -1.16632162606804 \tabularnewline
230 & 12 & 12.8182182048195 & -0.81821820481955 \tabularnewline
231 & 13 & 11.1912759968897 & 1.80872400311032 \tabularnewline
232 & 10 & 13.1366805948245 & -3.13668059482447 \tabularnewline
233 & 16 & 11.3143351749425 & 4.6856648250575 \tabularnewline
234 & 18 & 15.7304073268279 & 2.26959267317212 \tabularnewline
235 & 13 & 13.7135684147306 & -0.713568414730565 \tabularnewline
236 & 11 & 13.2122088681183 & -2.21220886811834 \tabularnewline
237 & 4 & 10.9165827014858 & -6.91658270148581 \tabularnewline
238 & 13 & 14.0971838894582 & -1.09718388945817 \tabularnewline
239 & 16 & 14.1415146853194 & 1.8584853146806 \tabularnewline
240 & 10 & 11.5906760659384 & -1.59067606593836 \tabularnewline
241 & 12 & 12.1730026807329 & -0.173002680732853 \tabularnewline
242 & 12 & 13.3478370561178 & -1.34783705611779 \tabularnewline
243 & 10 & 8.811826675465 & 1.188173324535 \tabularnewline
244 & 13 & 10.98982435633 & 2.01017564367 \tabularnewline
245 & 15 & 13.5142289090658 & 1.4857710909342 \tabularnewline
246 & 12 & 11.8134516362922 & 0.186548363707805 \tabularnewline
247 & 14 & 12.7037332144101 & 1.29626678558989 \tabularnewline
248 & 10 & 12.3306976778834 & -2.33069767788343 \tabularnewline
249 & 12 & 10.6380886744011 & 1.36191132559894 \tabularnewline
250 & 12 & 11.5527289935118 & 0.447271006488222 \tabularnewline
251 & 11 & 11.7356777720557 & -0.735677772055743 \tabularnewline
252 & 10 & 11.5456092216354 & -1.54560922163543 \tabularnewline
253 & 12 & 11.2541594236016 & 0.745840576398441 \tabularnewline
254 & 16 & 12.6755824417131 & 3.32441755828694 \tabularnewline
255 & 12 & 13.1490026491782 & -1.14900264917825 \tabularnewline
256 & 14 & 13.6608222034272 & 0.339177796572829 \tabularnewline
257 & 16 & 14.2207851815111 & 1.77921481848893 \tabularnewline
258 & 14 & 11.4944476761816 & 2.50555232381843 \tabularnewline
259 & 13 & 14.0518737366042 & -1.05187373660423 \tabularnewline
260 & 4 & 9.29789121761609 & -5.29789121761609 \tabularnewline
261 & 15 & 13.5573749889174 & 1.44262501108259 \tabularnewline
262 & 11 & 14.7763139185647 & -3.77631391856475 \tabularnewline
263 & 11 & 11.1527836332774 & -0.152783633277424 \tabularnewline
264 & 14 & 12.642696085183 & 1.35730391481695 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186039&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]13[/C][C]16.1022982210197[/C][C]-3.10229822101972[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.754491445859[/C][C]0.245508554141014[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.0517125772831[/C][C]1.94828742271692[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.1554580839931[/C][C]2.84454191600689[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4318778324043[/C][C]-2.43187783240426[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.8691295709112[/C][C]-1.86912957091122[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.2892630285488[/C][C]3.71073697145122[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0984636628673[/C][C]-2.09846366286726[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0620688662447[/C][C]-2.06206886624467[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4567921968538[/C][C]0.543207803146187[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.9908621102773[/C][C]1.00913788972271[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1770052175893[/C][C]-0.177005217589299[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5215035804684[/C][C]0.478496419531648[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.4956157166457[/C][C]0.504384283354324[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.0065120508452[/C][C]-1.0065120508452[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4716004383729[/C][C]-0.471600438372882[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.6159706821155[/C][C]0.384029317884485[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4282236996433[/C][C]3.57177630035666[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.479015093591[/C][C]2.52098490640904[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.5557893935874[/C][C]0.444210606412555[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3650432654783[/C][C]0.634956734521665[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.144145878139[/C][C]0.855854121861016[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4824869152471[/C][C]2.51751308475295[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.0855184907825[/C][C]0.914481509217452[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1730205602678[/C][C]0.826979439732198[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.2695071877283[/C][C]0.730492812271699[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9977946676347[/C][C]1.00220533236535[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.760323977679[/C][C]-1.76032397767898[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7555008219877[/C][C]0.244499178012286[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.181416577811[/C][C]-0.181416577811048[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7546834756412[/C][C]-0.754683475641216[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.8348155240329[/C][C]-0.83481552403293[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.8118391627312[/C][C]-0.81183916273115[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9368953882806[/C][C]0.063104611719357[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.5703707644626[/C][C]-1.57037076446263[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]13.005541434452[/C][C]-3.005541434452[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0747086953106[/C][C]-3.07470869531064[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.7548997678586[/C][C]-1.75489976785859[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5567994467754[/C][C]1.44320055322457[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.491506556545[/C][C]1.508493443455[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.7229795511616[/C][C]1.27702044883837[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.7500199860774[/C][C]-1.75001998607735[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4649787611873[/C][C]2.53502123881265[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1623540255355[/C][C]-0.162354025535507[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4650019090832[/C][C]-0.465001909083171[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.5278918457463[/C][C]-4.52789184574632[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.537742048153[/C][C]-2.53774204815302[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1382184624629[/C][C]-0.13821846246294[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.5081665290858[/C][C]0.491833470914169[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.6508961989038[/C][C]-1.65089619890381[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.0132875529785[/C][C]-1.01328755297849[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1613795638325[/C][C]-0.161379563832531[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.0533666119315[/C][C]-3.05336661193155[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.8229890413259[/C][C]0.177010958674083[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3977910266151[/C][C]-2.39779102661507[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.3852884808414[/C][C]1.61471151915857[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.8661838703893[/C][C]0.133816129610749[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.4829939565307[/C][C]0.517006043469343[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.1489452458437[/C][C]-0.148945245843684[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.218310603986[/C][C]1.78168939601395[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.566077304562[/C][C]0.433922695437972[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.695601652654[/C][C]0.304398347346031[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5680978968282[/C][C]-0.568097896828235[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.7144975746602[/C][C]-0.71449757466022[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2919080166204[/C][C]0.70809198337962[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.0481680519745[/C][C]0.9518319480255[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.291930000009[/C][C]1.708069999991[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.4768348393922[/C][C]3.52316516060783[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.9112854601582[/C][C]-3.9112854601582[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.6552497247185[/C][C]0.344750275281548[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.3387945042165[/C][C]-3.33879450421647[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.9127730431715[/C][C]-0.912773043171451[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.9677895861422[/C][C]1.03221041385776[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.1886676253417[/C][C]0.811332374658303[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.2649505766035[/C][C]0.73504942339646[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5121427306491[/C][C]3.48785726935087[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4136496754081[/C][C]-0.413649675408144[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.4885628517415[/C][C]1.51143714825848[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.2105291692642[/C][C]-2.21052916926418[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1210176116584[/C][C]0.878982388341565[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.7127255054486[/C][C]0.287274494551398[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7122824705459[/C][C]0.287717529454097[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6839662612022[/C][C]-0.683966261202235[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.8778596098532[/C][C]0.12214039014684[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.1625822832344[/C][C]1.83741771676558[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.1848053547452[/C][C]-0.184805354745237[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.3629727492202[/C][C]0.637027250779809[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.854683789533[/C][C]1.14531621046697[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.523619730254[/C][C]0.476380269745968[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.871340301249[/C][C]-1.871340301249[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.7460396281135[/C][C]0.253960371886512[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.8347181377269[/C][C]0.165281862273136[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.1102677566366[/C][C]-0.110267756636619[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0707409807562[/C][C]-2.07074098075619[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.7984388525891[/C][C]1.20156114741089[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7699135286564[/C][C]0.230086471343579[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.719607258186[/C][C]2.28039274181401[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8147243792642[/C][C]0.185275620735792[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4339411801958[/C][C]-0.433941180195834[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0258101979206[/C][C]-1.02581019792061[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6741968980677[/C][C]1.32580310193225[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4559352407525[/C][C]2.54406475924747[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.1818457214788[/C][C]0.818154278521223[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.0003028518371[/C][C]0.999697148162855[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8675061755119[/C][C]-1.86750617551193[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.688287603418[/C][C]1.31171239658197[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.722850378802[/C][C]0.277149621197993[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.3491544203633[/C][C]1.6508455796367[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.275456137583[/C][C]-0.275456137582957[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2862749523836[/C][C]0.713725047616351[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.0176513153709[/C][C]-0.0176513153709174[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0267000494355[/C][C]1.97329995056449[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5664542163355[/C][C]-1.56645421633551[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5701172401542[/C][C]-2.57011724015419[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1521391092508[/C][C]1.84786089074916[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8505123074627[/C][C]-1.85051230746266[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.1495620020431[/C][C]0.850437997956938[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7823871743341[/C][C]-1.78238717433406[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5374491098906[/C][C]0.462550890109423[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.416850974949[/C][C]-1.41685097494897[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.3911674686073[/C][C]0.608832531392733[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.839724797741[/C][C]-2.83972479774098[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.8306547434266[/C][C]-0.830654743426562[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8273961971164[/C][C]-0.827396197116446[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.8053227042767[/C][C]-0.805322704276728[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6649650351164[/C][C]0.335034964883577[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.5277908137443[/C][C]1.47220918625569[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9616616580418[/C][C]1.03833834195822[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.6840500753593[/C][C]-2.68405007535926[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9649372104061[/C][C]2.03506278959389[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.7296991647035[/C][C]-3.72969916470354[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4901531526812[/C][C]2.50984684731883[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1462272767885[/C][C]-2.14622727678853[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.5237533235708[/C][C]-1.52375332357078[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.0605941760137[/C][C]-0.0605941760136943[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1096554606152[/C][C]0.890344539384808[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.4356748026804[/C][C]0.564325197319618[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4342499906017[/C][C]-2.43424999060171[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.975933493865[/C][C]-0.97593349386503[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.3597071648791[/C][C]-2.35970716487914[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8359245090749[/C][C]3.16407549092506[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.657252825922[/C][C]1.34274717407804[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.8239462207622[/C][C]0.17605377923783[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.1434432664305[/C][C]1.85655673356948[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.2656605799341[/C][C]-3.26566057993405[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.4752937985422[/C][C]2.52470620145776[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.9006435559371[/C][C]-1.90064355593709[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.8275040139554[/C][C]1.1724959860446[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.8024541407533[/C][C]0.197545859246742[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8872795704569[/C][C]-2.88727957045692[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.9276356858023[/C][C]-0.927635685802293[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8757095036435[/C][C]2.12429049635646[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8529345956268[/C][C]4.14706540437316[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.3880193199151[/C][C]1.61198068008492[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.4090361127589[/C][C]-2.40903611275887[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.4250734896923[/C][C]0.574926510307681[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.6850863414094[/C][C]1.31491365859057[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.8135234403089[/C][C]1.18647655969106[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.540047010007[/C][C]1.45995298999296[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.7472156095952[/C][C]-0.747215609595171[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.599585420271[/C][C]0.400414579728982[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.60733341585[/C][C]0.392666584149958[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.4465137428269[/C][C]-0.44651374282687[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2355495679263[/C][C]0.764450432073746[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6996832333109[/C][C]1.30031676668912[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.6136876844136[/C][C]-1.61368768441355[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.32787037191[/C][C]-0.327870371910013[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2106862511466[/C][C]-3.21068625114663[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.7978730780644[/C][C]-1.7978730780644[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4732850859102[/C][C]1.52671491408983[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.4796421173843[/C][C]1.52035788261573[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.3338740476203[/C][C]0.666125952379726[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.8661216503701[/C][C]-1.86612165037008[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3520658851189[/C][C]-2.35206588511894[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.9038825751131[/C][C]-2.90388257511308[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.5533998439333[/C][C]0.446600156066671[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2615035985194[/C][C]-0.261503598519359[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6794441470007[/C][C]-0.67944414700072[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.7758576087759[/C][C]0.224142391224061[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.3751911004819[/C][C]-1.37519110048189[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]14.987782175698[/C][C]1.01221782430197[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.4391784414346[/C][C]-0.439178441434581[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.6527802643649[/C][C]2.34721973563512[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.1309558411913[/C][C]-0.130955841191348[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.5671696852632[/C][C]-6.5671696852632[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.7673080225747[/C][C]1.23269197742529[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.4466779452211[/C][C]2.5533220547789[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.3914638757077[/C][C]-0.391463875707659[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4687344908835[/C][C]-0.468734490883497[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.419312143855[/C][C]0.580687856145011[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.7132415544436[/C][C]-0.713241554443631[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4179494281746[/C][C]0.58205057182538[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.7305189923556[/C][C]2.2694810076444[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.005043145604[/C][C]1.99495685439604[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6285705973993[/C][C]-0.62857059739933[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.9617223713724[/C][C]0.0382776286276256[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.9335254605675[/C][C]3.06647453943252[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.0029292095033[/C][C]0.997070790496686[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4290193785421[/C][C]1.57098062145789[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.5234359971224[/C][C]1.47656400287756[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.9790867071796[/C][C]2.02091329282044[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.3290512771168[/C][C]0.670948722883167[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.405240124026[/C][C]-2.405240124026[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4275103508537[/C][C]-2.42751035085371[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6959007664366[/C][C]2.30409923356338[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.420995709824[/C][C]0.579004290176027[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4572845531089[/C][C]1.54271544689108[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.8498933338697[/C][C]1.1501066661303[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5475210272528[/C][C]-2.54752102725284[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.9241772138033[/C][C]1.07582278619673[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1753816464544[/C][C]-2.17538164645442[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.6883077893975[/C][C]-3.68830778939753[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.0995026390192[/C][C]0.900497360980815[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0671926762682[/C][C]2.93280732373177[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4870015292518[/C][C]1.51299847074822[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0305934459454[/C][C]0.969406554054561[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5721285927648[/C][C]2.42787140723524[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.879232266408[/C][C]0.120767733591951[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.873726081311[/C][C]1.12627391868899[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.087549793977[/C][C]-0.0875497939769591[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5770127002136[/C][C]-1.57701270021358[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.9946409736908[/C][C]0.0053590263092174[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.1979736451346[/C][C]0.802026354865392[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.039494366232[/C][C]-1.03949436623199[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.5667398396589[/C][C]0.433260160341059[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.6951354167233[/C][C]-3.69513541672332[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6606413657131[/C][C]0.339358634286859[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.9138398171081[/C][C]1.08616018289194[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.166321626068[/C][C]-1.16632162606804[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8182182048195[/C][C]-0.81821820481955[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.1912759968897[/C][C]1.80872400311032[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.1366805948245[/C][C]-3.13668059482447[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3143351749425[/C][C]4.6856648250575[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.7304073268279[/C][C]2.26959267317212[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.7135684147306[/C][C]-0.713568414730565[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.2122088681183[/C][C]-2.21220886811834[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9165827014858[/C][C]-6.91658270148581[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.0971838894582[/C][C]-1.09718388945817[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.1415146853194[/C][C]1.8584853146806[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5906760659384[/C][C]-1.59067606593836[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1730026807329[/C][C]-0.173002680732853[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3478370561178[/C][C]-1.34783705611779[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.811826675465[/C][C]1.188173324535[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.98982435633[/C][C]2.01017564367[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.5142289090658[/C][C]1.4857710909342[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.8134516362922[/C][C]0.186548363707805[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.7037332144101[/C][C]1.29626678558989[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.3306976778834[/C][C]-2.33069767788343[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.6380886744011[/C][C]1.36191132559894[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5527289935118[/C][C]0.447271006488222[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.7356777720557[/C][C]-0.735677772055743[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.5456092216354[/C][C]-1.54560922163543[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2541594236016[/C][C]0.745840576398441[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.6755824417131[/C][C]3.32441755828694[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.1490026491782[/C][C]-1.14900264917825[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.6608222034272[/C][C]0.339177796572829[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.2207851815111[/C][C]1.77921481848893[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.4944476761816[/C][C]2.50555232381843[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.0518737366042[/C][C]-1.05187373660423[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.29789121761609[/C][C]-5.29789121761609[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.5573749889174[/C][C]1.44262501108259[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.7763139185647[/C][C]-3.77631391856475[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1527836332774[/C][C]-0.152783633277424[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.642696085183[/C][C]1.35730391481695[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186039&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186039&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
11316.1022982210197-3.10229822101972
21615.7544914458590.245508554141014
31917.05171257728311.94828742271692
41512.15545808399312.84454191600689
51416.4318778324043-2.43187783240426
61314.8691295709112-1.86912957091122
71915.28926302854883.71073697145122
81517.0984636628673-2.09846366286726
91416.0620688662447-2.06206886624467
101514.45679219685380.543207803146187
111614.99086211027731.00913788972271
121616.1770052175893-0.177005217589299
131615.52150358046840.478496419531648
141615.49561571664570.504384283354324
151718.0065120508452-1.0065120508452
161515.4716004383729-0.471600438372882
171514.61597068211550.384029317884485
182016.42822369964333.57177630035666
191815.4790150935912.52098490640904
201615.55578939358740.444210606412555
211615.36504326547830.634956734521665
221615.1441458781390.855854121861016
231916.48248691524712.51751308475295
241615.08551849078250.914481509217452
251716.17302056026780.826979439732198
261716.26950718772830.730492812271699
271614.99779466763471.00220533236535
281516.760323977679-1.76032397767898
291615.75550082198770.244499178012286
301414.181416577811-0.181416577811048
311515.7546834756412-0.754683475641216
321212.8348155240329-0.83481552403293
331414.8118391627312-0.81183916273115
341615.93689538828060.063104611719357
351415.5703707644626-1.57037076446263
361013.005541434452-3.005541434452
371013.0747086953106-3.07470869531064
381415.7548997678586-1.75489976785859
391614.55679944677541.44320055322457
401614.4915065565451.508493443455
411614.72297955116161.27702044883837
421415.7500199860774-1.75001998607735
432017.46497876118732.53502123881265
441414.1623540255355-0.162354025535507
451414.4650019090832-0.465001909083171
461115.5278918457463-4.52789184574632
471416.537742048153-2.53774204815302
481515.1382184624629-0.13821846246294
491615.50816652908580.491833470914169
501415.6508961989038-1.65089619890381
511617.0132875529785-1.01328755297849
521414.1613795638325-0.161379563832531
531215.0533666119315-3.05336661193155
541615.82298904132590.177010958674083
55911.3977910266151-2.39779102661507
561412.38528848084141.61471151915857
571615.86618387038930.133816129610749
581615.48299395653070.517006043469343
591515.1489452458437-0.148945245843684
601614.2183106039861.78168939601395
611211.5660773045620.433922695437972
621615.6956016526540.304398347346031
631616.5680978968282-0.568097896828235
641414.7144975746602-0.71449757466022
651615.29190801662040.70809198337962
661716.04816805197450.9518319480255
671816.2919300000091.708069999991
681814.47683483939223.52316516060783
691215.9112854601582-3.9112854601582
701615.65524972471850.344750275281548
711013.3387945042165-3.33879450421647
721414.9127730431715-0.912773043171451
731816.96778958614221.03221041385776
741817.18866762534170.811332374658303
751615.26495057660350.73504942339646
761713.51214273064913.48785726935087
771616.4136496754081-0.413649675408144
781614.48856285174151.51143714825848
791315.2105291692642-2.21052916926418
801615.12101761165840.878982388341565
811615.71272550544860.287274494551398
821615.71228247054590.287717529454097
831515.6839662612022-0.683966261202235
841514.87785960985320.12214039014684
851614.16258228323441.83741771676558
861414.1848053547452-0.184805354745237
871615.36297274922020.637027250779809
881614.8546837895331.14531621046697
891514.5236197302540.476380269745968
901213.871340301249-1.871340301249
911716.74603962811350.253960371886512
921615.83471813772690.165281862273136
931515.1102677566366-0.110267756636619
941315.0707409807562-2.07074098075619
951614.79843885258911.20156114741089
961615.76991352865640.230086471343579
971613.7196072581862.28039274181401
981615.81472437926420.185275620735792
991414.4339411801958-0.433941180195834
1001617.0258101979206-1.02581019792061
1011614.67419689806771.32580310193225
1022017.45593524075252.54406475924747
1031514.18184572147880.818154278521223
1041615.00030285183710.999697148162855
1051314.8675061755119-1.86750617551193
1061715.6882876034181.31171239658197
1071615.7228503788020.277149621197993
1081614.34915442036331.6508455796367
1091212.275456137583-0.275456137582957
1101615.28627495238360.713725047616351
1111616.0176513153709-0.0176513153709174
1121715.02670004943551.97329995056449
1131314.5664542163355-1.56645421633551
1141214.5701172401542-2.57011724015419
1151816.15213910925081.84786089074916
1161415.8505123074627-1.85051230746266
1171413.14956200204310.850437997956938
1181314.7823871743341-1.78238717433406
1191615.53744910989060.462550890109423
1201314.416850974949-1.41685097494897
1211615.39116746860730.608832531392733
1221315.839724797741-2.83972479774098
1231616.8306547434266-0.830654743426562
1241515.8273961971164-0.827396197116446
1251616.8053227042767-0.805322704276728
1261514.66496503511640.335034964883577
1271715.52779081374431.47220918625569
1281513.96166165804181.03833834195822
1291214.6840500753593-2.68405007535926
1301613.96493721040612.03506278959389
1311013.7296991647035-3.72969916470354
1321613.49015315268122.50984684731883
1331214.1462272767885-2.14622727678853
1341415.5237533235708-1.52375332357078
1351515.0605941760137-0.0605941760136943
1361312.10965546061520.890344539384808
1371514.43567480268040.564325197319618
1381113.4342499906017-2.43424999060171
1391212.975933493865-0.97593349386503
1401113.3597071648791-2.35970716487914
1411612.83592450907493.16407549092506
1421513.6572528259221.34274717407804
1431716.82394622076220.17605377923783
1441614.14344326643051.85655673356948
1451013.2656605799341-3.26566057993405
1461815.47529379854222.52470620145776
1471314.9006435559371-1.90064355593709
1481614.82750401395541.1724959860446
1491312.80245414075330.197545859246742
1501012.8872795704569-2.88727957045692
1511515.9276356858023-0.927635685802293
1521613.87570950364352.12429049635646
1531611.85293459562684.14706540437316
1541412.38801931991511.61198068008492
1551012.4090361127589-2.40903611275887
1561716.42507348969230.574926510307681
1571311.68508634140941.31491365859057
1581513.81352344030891.18647655969106
1591614.5400470100071.45995298999296
1601212.7472156095952-0.747215609595171
1611312.5995854202710.400414579728982
1621312.607333415850.392666584149958
1631212.4465137428269-0.44651374282687
1641716.23554956792630.764450432073746
1651513.69968323331091.30031676668912
1661011.6136876844136-1.61368768441355
1671414.32787037191-0.327870371910013
1681114.2106862511466-3.21068625114663
1691314.7978730780644-1.7978730780644
1701614.47328508591021.52671491408983
1711210.47964211738431.52035788261573
1721615.33387404762030.666125952379726
1731213.8661216503701-1.86612165037008
174911.3520658851189-2.35206588511894
1751214.9038825751131-2.90388257511308
1761514.55339984393330.446600156066671
1771212.2615035985194-0.261503598519359
1781212.6794441470007-0.67944414700072
1791413.77585760877590.224142391224061
1801213.3751911004819-1.37519110048189
1811614.9877821756981.01221782430197
1821111.4391784414346-0.439178441434581
1831916.65278026436492.34721973563512
1841515.1309558411913-0.130955841191348
185814.5671696852632-6.5671696852632
1861614.76730802257471.23269197742529
1871714.44667794522112.5533220547789
1881212.3914638757077-0.391463875707659
1891111.4687344908835-0.468734490883497
1901110.4193121438550.580687856145011
1911414.7132415544436-0.713241554443631
1921615.41794942817460.58205057182538
193129.73051899235562.2694810076444
1941614.0050431456041.99495685439604
1951313.6285705973993-0.62857059739933
1961514.96172237137240.0382776286276256
1971612.93352546056753.06647453943252
1981615.00292920950330.997070790496686
1991412.42901937854211.57098062145789
2001614.52343599712241.47656400287756
2011613.97908670717962.02091329282044
2021413.32905127711680.670948722883167
2031113.405240124026-2.405240124026
2041214.4275103508537-2.42751035085371
2051512.69590076643662.30409923356338
2061514.4209957098240.579004290176027
2071614.45728455310891.54271544689108
2081614.84989333386971.1501066661303
2091113.5475210272528-2.54752102725284
2101513.92417721380331.07582278619673
2111214.1753816464544-2.17538164645442
2121215.6883077893975-3.68830778939753
2131514.09950263901920.900497360980815
2141512.06719267626822.93280732373177
2151614.48700152925181.51299847074822
2161413.03059344594540.969406554054561
2171714.57212859276482.42787140723524
2181413.8792322664080.120767733591951
2191311.8737260813111.12627391868899
2201515.087549793977-0.0875497939769591
2211314.5770127002136-1.57701270021358
2221413.99464097369080.0053590263092174
2231514.19797364513460.802026354865392
2241213.039494366232-1.03949436623199
2251312.56673983965890.433260160341059
226811.6951354167233-3.69513541672332
2271413.66064136571310.339358634286859
2281412.91383981710811.08616018289194
2291112.166321626068-1.16632162606804
2301212.8182182048195-0.81821820481955
2311311.19127599688971.80872400311032
2321013.1366805948245-3.13668059482447
2331611.31433517494254.6856648250575
2341815.73040732682792.26959267317212
2351313.7135684147306-0.713568414730565
2361113.2122088681183-2.21220886811834
237410.9165827014858-6.91658270148581
2381314.0971838894582-1.09718388945817
2391614.14151468531941.8584853146806
2401011.5906760659384-1.59067606593836
2411212.1730026807329-0.173002680732853
2421213.3478370561178-1.34783705611779
243108.8118266754651.188173324535
2441310.989824356332.01017564367
2451513.51422890906581.4857710909342
2461211.81345163629220.186548363707805
2471412.70373321441011.29626678558989
2481012.3306976778834-2.33069767788343
2491210.63808867440111.36191132559894
2501211.55272899351180.447271006488222
2511111.7356777720557-0.735677772055743
2521011.5456092216354-1.54560922163543
2531211.25415942360160.745840576398441
2541612.67558244171313.32441755828694
2551213.1490026491782-1.14900264917825
2561413.66082220342720.339177796572829
2571614.22078518151111.77921481848893
2581411.49444767618162.50555232381843
2591314.0518737366042-1.05187373660423
26049.29789121761609-5.29789121761609
2611513.55737498891741.44262501108259
2621114.7763139185647-3.77631391856475
2631111.1527836332774-0.152783633277424
2641412.6426960851831.35730391481695






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.09490693367178270.1898138673435650.905093066328217
130.1688210524404690.3376421048809370.831178947559531
140.178863827940670.3577276558813410.82113617205933
150.1021082218164460.2042164436328930.897891778183554
160.07842819714433640.1568563942886730.921571802855664
170.08702376605979080.1740475321195820.912976233940209
180.2132234398370970.4264468796741940.786776560162903
190.1758104644518980.3516209289037950.824189535548102
200.1394060419652330.2788120839304660.860593958034767
210.1076168728677320.2152337457354630.892383127132269
220.1314003163079110.2628006326158210.868599683692089
230.229848580090410.459697160180820.77015141990959
240.345400678188320.6908013563766390.65459932181168
250.2821587565081750.5643175130163490.717841243491825
260.2373233122401470.4746466244802940.762676687759853
270.2278962457384570.4557924914769140.772103754261543
280.3384850522129770.6769701044259540.661514947787023
290.2893254811346310.5786509622692620.710674518865369
300.3978828599366230.7957657198732450.602117140063377
310.3568902574880350.713780514976070.643109742511965
320.329416582090550.65883316418110.67058341790945
330.3141214600600360.6282429201200720.685878539939964
340.2782628951098780.5565257902197550.721737104890122
350.2368206844126130.4736413688252260.763179315587387
360.3669047636406810.7338095272813620.633095236359319
370.3956217287057510.7912434574115020.604378271294249
380.37157667251540.7431533450308010.6284233274846
390.416207602576150.83241520515230.58379239742385
400.3965466505621470.7930933011242930.603453349437853
410.3577995707434310.7155991414868630.642200429256569
420.319486473803070.6389729476061410.68051352619693
430.3384091031573870.6768182063147750.661590896842613
440.291402618208390.5828052364167810.70859738179161
450.264493101647080.528986203294160.73550689835292
460.4416124751845530.8832249503691070.558387524815447
470.5322670026109670.9354659947780670.467732997389033
480.4892016963859960.9784033927719920.510798303614004
490.5136426551357230.9727146897285540.486357344864277
500.4866219481787860.9732438963575720.513378051821214
510.4415572589751860.8831145179503720.558442741024814
520.4004250108969730.8008500217939450.599574989103027
530.3998641474306660.7997282948613320.600135852569334
540.3580805641964730.7161611283929460.641919435803527
550.3460959966995090.6921919933990180.653904003300491
560.3433011269468690.6866022538937380.656698873053131
570.3042398889216210.6084797778432420.695760111078379
580.2857200862422750.571440172484550.714279913757725
590.255885142827490.5117702856549790.74411485717251
600.2763078016978720.5526156033957430.723692198302128
610.2529929042034120.5059858084068250.747007095796588
620.228275085332220.4565501706644410.77172491466778
630.199677701775130.3993554035502610.80032229822487
640.1720118990507720.3440237981015430.827988100949228
650.1517815382386840.3035630764773680.848218461761316
660.1430713872026180.2861427744052370.856928612797382
670.1390475535876250.2780951071752490.860952446412375
680.2692032311029030.5384064622058060.730796768897097
690.3644951757875050.7289903515750090.635504824212495
700.3340009024832860.6680018049665710.665999097516714
710.4431017811684230.8862035623368450.556898218831578
720.4083901990131820.8167803980263650.591609800986818
730.4088932175450150.8177864350900310.591106782454984
740.3971357235217690.7942714470435380.602864276478231
750.3600340565442360.7200681130884710.639965943455764
760.4257931817071380.8515863634142770.574206818292862
770.3880424411457730.7760848822915470.611957558854227
780.3620947587099960.7241895174199930.637905241290004
790.3767932495497760.7535864990995520.623206750450224
800.3431168503060020.6862337006120050.656883149693998
810.3145228214193750.629045642838750.685477178580625
820.2808624843347370.5617249686694740.719137515665263
830.2532822022560530.5065644045121060.746717797743947
840.223423532033940.446847064067880.77657646796606
850.2172941130128580.4345882260257150.782705886987142
860.1898215960811270.3796431921622530.810178403918873
870.1674870500495880.3349741000991770.832512949950412
880.1551269114241020.3102538228482030.844873088575898
890.1336367401632070.2672734803264140.866363259836793
900.1322699266580860.2645398533161710.867730073341914
910.1131565212513720.2263130425027450.886843478748628
920.09888473584626070.1977694716925210.901115264153739
930.0841070314242160.1682140628484320.915892968575784
940.087387903163340.174775806326680.91261209683666
950.07905597610140650.1581119522028130.920944023898594
960.06615681562295230.1323136312459050.933843184377048
970.07087573047600050.1417514609520010.929124269524
980.05887246776282060.1177449355256410.941127532237179
990.04884884085961710.09769768171923420.951151159140383
1000.04292117224369980.08584234448739970.9570788277563
1010.03757442967993540.07514885935987080.962425570320065
1020.04346502184713560.08693004369427120.956534978152864
1030.03663580215437720.07327160430875440.963364197845623
1040.03285284634801090.06570569269602180.967147153651989
1050.03913920191121280.07827840382242550.960860798088787
1060.03405157097239640.06810314194479280.965948429027604
1070.02765164508836610.05530329017673220.972348354911634
1080.02678027064873750.05356054129747490.973219729351263
1090.02175499515892960.04350999031785920.97824500484107
1100.01772690060187320.03545380120374640.982273099398127
1110.01405453909611810.02810907819223610.985945460903882
1120.01419518124251680.02839036248503350.985804818757483
1130.01288849216904410.02577698433808820.987111507830956
1140.01886063958014740.03772127916029490.981139360419853
1150.0177299769212730.03545995384254610.982270023078727
1160.01723449623989080.03446899247978170.982765503760109
1170.01416276390975150.0283255278195030.985837236090249
1180.01425322643443670.02850645286887330.985746773565563
1190.01148841265526150.0229768253105230.988511587344739
1200.01028505431584560.02057010863169110.989714945684154
1210.008261909746838570.01652381949367710.991738090253161
1220.01251857842882640.02503715685765290.987481421571174
1230.01044720142890080.02089440285780160.989552798571099
1240.008973745364233480.0179474907284670.991026254635767
1250.007295191777116460.01459038355423290.992704808222884
1260.005773670024639530.01154734004927910.99422632997536
1270.005258363128513180.01051672625702640.994741636871487
1280.004250609199450490.008501218398900980.995749390800549
1290.006006641470327730.01201328294065550.993993358529672
1300.006603665812144640.01320733162428930.993396334187855
1310.01373860168122820.02747720336245640.986261398318772
1320.01641982605893550.03283965211787090.983580173941065
1330.01760203972465740.03520407944931480.982397960275343
1340.01669508230170530.03339016460341050.983304917698295
1350.01334414796471280.02668829592942560.986655852035287
1360.01122251727385520.02244503454771040.988777482726145
1370.008916657321749270.01783331464349850.991083342678251
1380.01115054210354870.02230108420709740.988849457896451
1390.009557227639701090.01911445527940220.990442772360299
1400.01131238699459740.02262477398919490.988687613005403
1410.01795907823722150.0359181564744430.982040921762778
1420.0165488861252270.0330977722504540.983451113874773
1430.01330585372132480.02661170744264960.986694146278675
1440.01369886080338960.02739772160677930.98630113919661
1450.02457946585901780.04915893171803560.975420534140982
1460.02983593984356710.05967187968713430.970164060156433
1470.03131752201670240.06263504403340470.968682477983298
1480.02771179376523080.05542358753046160.972288206234769
1490.02255240723186070.04510481446372140.977447592768139
1500.03149661579808850.06299323159617710.968503384201912
1510.0265998969757280.0531997939514560.973400103024272
1520.02894597497460320.05789194994920640.971054025025397
1530.05853760298865580.1170752059773120.941462397011344
1540.05640498581459260.1128099716291850.943595014185407
1550.06460824369310670.1292164873862130.935391756306893
1560.05493705281748810.1098741056349760.945062947182512
1570.04901887120467130.09803774240934270.950981128795329
1580.04268954235422440.08537908470844880.957310457645776
1590.04132954873613580.08265909747227170.958670451263864
1600.0354669898625970.0709339797251940.964533010137403
1610.0289564655703490.05791293114069790.971043534429651
1620.02363570823402070.04727141646804140.976364291765979
1630.01930963884510070.03861927769020140.980690361154899
1640.01632910977000030.03265821954000060.98367089023
1650.01445008337874660.02890016675749320.985549916621253
1660.01494861176131710.02989722352263430.985051388238683
1670.01188421738242430.02376843476484850.988115782617576
1680.01751327832294780.03502655664589560.982486721677052
1690.01763400818190620.03526801636381250.982365991818094
1700.01673538826347340.03347077652694680.983264611736527
1710.01545666162761660.03091332325523320.984543338372383
1720.01247237287750020.02494474575500040.9875276271225
1730.0120882121093150.024176424218630.987911787890685
1740.01377482855148940.02754965710297880.986225171448511
1750.0179335058427580.0358670116855160.982066494157242
1760.0143782154817520.0287564309635040.985621784518248
1770.01135238021117960.02270476042235910.98864761978882
1780.009545562620591690.01909112524118340.990454437379408
1790.007389758045191480.0147795160903830.992610241954809
1800.006509052142836590.01301810428567320.993490947857163
1810.00531052029528310.01062104059056620.994689479704717
1820.004086686884734920.008173373769469840.995913313115265
1830.004424692917154670.008849385834309340.995575307082845
1840.003352022920341060.006704045840682130.996647977079659
1850.09163270237506730.1832654047501350.908367297624933
1860.08192793360271330.1638558672054270.918072066397287
1870.09042000229711070.1808400045942210.909579997702889
1880.07590051292008580.1518010258401720.924099487079914
1890.06774692269210660.1354938453842130.932253077307893
1900.0565897118898440.1131794237796880.943410288110156
1910.052365079923280.104730159846560.94763492007672
1920.04325736088569910.08651472177139820.956742639114301
1930.04437521881991710.08875043763983430.955624781180083
1940.04485920517831940.08971841035663870.955140794821681
1950.03879136012260830.07758272024521650.961208639877392
1960.03121425287124310.06242850574248620.968785747128757
1970.03941489334589140.07882978669178270.960585106654109
1980.03218361130267320.06436722260534650.967816388697327
1990.02896427162907880.05792854325815750.971035728370921
2000.02485692046963590.04971384093927180.975143079530364
2010.02324626684405330.04649253368810650.976753733155947
2020.01965012261955380.03930024523910760.980349877380446
2030.02580615996018440.05161231992036870.974193840039816
2040.03005587198241490.06011174396482980.969944128017585
2050.03147735367449860.06295470734899710.968522646325501
2060.02467345405028220.04934690810056440.975326545949718
2070.02361957126079230.04723914252158450.976380428739208
2080.01930971781874440.03861943563748870.980690282181256
2090.02153171270348120.04306342540696230.978468287296519
2100.01715999382600610.03431998765201220.982840006173994
2110.01972006081024880.03944012162049760.980279939189751
2120.03198601436106650.06397202872213290.968013985638933
2130.02490099880834780.04980199761669570.975099001191652
2140.03219963344204030.06439926688408060.96780036655796
2150.02732320563832830.05464641127665650.972676794361672
2160.02113757479784180.04227514959568370.978862425202158
2170.02322055161677570.04644110323355140.976779448383224
2180.01957973264799160.03915946529598310.980420267352008
2190.01819143350512490.03638286701024980.981808566494875
2200.01391046527472530.02782093054945060.986089534725275
2210.01158463563075670.02316927126151330.988415364369243
2220.008318636450755210.01663727290151040.991681363549245
2230.006380203789997460.01276040757999490.993619796210003
2240.004809065882655540.009618131765311080.995190934117344
2250.004093750450760220.008187500901520440.99590624954924
2260.009466810057665290.01893362011533060.990533189942335
2270.007417951092789390.01483590218557880.992582048907211
2280.005488961457264570.01097792291452910.994511038542735
2290.003925896582777710.007851793165555420.996074103417222
2300.002890463416874660.005780926833749330.997109536583125
2310.002606181890285140.005212363780570270.997393818109715
2320.006137343094016580.01227468618803320.993862656905983
2330.02476496745693710.04952993491387430.975235032543063
2340.03774775795470850.0754955159094170.962252242045291
2350.02723109893689870.05446219787379750.972768901063101
2360.02282544908181220.04565089816362450.977174550918188
2370.197370721984520.394741443969040.80262927801548
2380.1556675216785840.3113350433571670.844332478321416
2390.1296071410199340.2592142820398670.870392858980066
2400.1005441980234880.2010883960469760.899455801976512
2410.08840818112546270.1768163622509250.911591818874537
2420.1379384942689970.2758769885379940.862061505731003
2430.1129598284016440.2259196568032870.887040171598356
2440.1182937307244960.2365874614489910.881706269275504
2450.09681983447441890.1936396689488380.903180165525581
2460.0821740101718720.1643480203437440.917825989828128
2470.05305608321626040.1061121664325210.94694391678374
2480.04520287298809690.09040574597619380.954797127011903
2490.0404519036819730.0809038073639460.959548096318027
2500.1154964621938520.2309929243877030.884503537806148
2510.09470384115353980.189407682307080.90529615884646
2520.4314389998356860.8628779996713710.568561000164314

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.0949069336717827 & 0.189813867343565 & 0.905093066328217 \tabularnewline
13 & 0.168821052440469 & 0.337642104880937 & 0.831178947559531 \tabularnewline
14 & 0.17886382794067 & 0.357727655881341 & 0.82113617205933 \tabularnewline
15 & 0.102108221816446 & 0.204216443632893 & 0.897891778183554 \tabularnewline
16 & 0.0784281971443364 & 0.156856394288673 & 0.921571802855664 \tabularnewline
17 & 0.0870237660597908 & 0.174047532119582 & 0.912976233940209 \tabularnewline
18 & 0.213223439837097 & 0.426446879674194 & 0.786776560162903 \tabularnewline
19 & 0.175810464451898 & 0.351620928903795 & 0.824189535548102 \tabularnewline
20 & 0.139406041965233 & 0.278812083930466 & 0.860593958034767 \tabularnewline
21 & 0.107616872867732 & 0.215233745735463 & 0.892383127132269 \tabularnewline
22 & 0.131400316307911 & 0.262800632615821 & 0.868599683692089 \tabularnewline
23 & 0.22984858009041 & 0.45969716018082 & 0.77015141990959 \tabularnewline
24 & 0.34540067818832 & 0.690801356376639 & 0.65459932181168 \tabularnewline
25 & 0.282158756508175 & 0.564317513016349 & 0.717841243491825 \tabularnewline
26 & 0.237323312240147 & 0.474646624480294 & 0.762676687759853 \tabularnewline
27 & 0.227896245738457 & 0.455792491476914 & 0.772103754261543 \tabularnewline
28 & 0.338485052212977 & 0.676970104425954 & 0.661514947787023 \tabularnewline
29 & 0.289325481134631 & 0.578650962269262 & 0.710674518865369 \tabularnewline
30 & 0.397882859936623 & 0.795765719873245 & 0.602117140063377 \tabularnewline
31 & 0.356890257488035 & 0.71378051497607 & 0.643109742511965 \tabularnewline
32 & 0.32941658209055 & 0.6588331641811 & 0.67058341790945 \tabularnewline
33 & 0.314121460060036 & 0.628242920120072 & 0.685878539939964 \tabularnewline
34 & 0.278262895109878 & 0.556525790219755 & 0.721737104890122 \tabularnewline
35 & 0.236820684412613 & 0.473641368825226 & 0.763179315587387 \tabularnewline
36 & 0.366904763640681 & 0.733809527281362 & 0.633095236359319 \tabularnewline
37 & 0.395621728705751 & 0.791243457411502 & 0.604378271294249 \tabularnewline
38 & 0.3715766725154 & 0.743153345030801 & 0.6284233274846 \tabularnewline
39 & 0.41620760257615 & 0.8324152051523 & 0.58379239742385 \tabularnewline
40 & 0.396546650562147 & 0.793093301124293 & 0.603453349437853 \tabularnewline
41 & 0.357799570743431 & 0.715599141486863 & 0.642200429256569 \tabularnewline
42 & 0.31948647380307 & 0.638972947606141 & 0.68051352619693 \tabularnewline
43 & 0.338409103157387 & 0.676818206314775 & 0.661590896842613 \tabularnewline
44 & 0.29140261820839 & 0.582805236416781 & 0.70859738179161 \tabularnewline
45 & 0.26449310164708 & 0.52898620329416 & 0.73550689835292 \tabularnewline
46 & 0.441612475184553 & 0.883224950369107 & 0.558387524815447 \tabularnewline
47 & 0.532267002610967 & 0.935465994778067 & 0.467732997389033 \tabularnewline
48 & 0.489201696385996 & 0.978403392771992 & 0.510798303614004 \tabularnewline
49 & 0.513642655135723 & 0.972714689728554 & 0.486357344864277 \tabularnewline
50 & 0.486621948178786 & 0.973243896357572 & 0.513378051821214 \tabularnewline
51 & 0.441557258975186 & 0.883114517950372 & 0.558442741024814 \tabularnewline
52 & 0.400425010896973 & 0.800850021793945 & 0.599574989103027 \tabularnewline
53 & 0.399864147430666 & 0.799728294861332 & 0.600135852569334 \tabularnewline
54 & 0.358080564196473 & 0.716161128392946 & 0.641919435803527 \tabularnewline
55 & 0.346095996699509 & 0.692191993399018 & 0.653904003300491 \tabularnewline
56 & 0.343301126946869 & 0.686602253893738 & 0.656698873053131 \tabularnewline
57 & 0.304239888921621 & 0.608479777843242 & 0.695760111078379 \tabularnewline
58 & 0.285720086242275 & 0.57144017248455 & 0.714279913757725 \tabularnewline
59 & 0.25588514282749 & 0.511770285654979 & 0.74411485717251 \tabularnewline
60 & 0.276307801697872 & 0.552615603395743 & 0.723692198302128 \tabularnewline
61 & 0.252992904203412 & 0.505985808406825 & 0.747007095796588 \tabularnewline
62 & 0.22827508533222 & 0.456550170664441 & 0.77172491466778 \tabularnewline
63 & 0.19967770177513 & 0.399355403550261 & 0.80032229822487 \tabularnewline
64 & 0.172011899050772 & 0.344023798101543 & 0.827988100949228 \tabularnewline
65 & 0.151781538238684 & 0.303563076477368 & 0.848218461761316 \tabularnewline
66 & 0.143071387202618 & 0.286142774405237 & 0.856928612797382 \tabularnewline
67 & 0.139047553587625 & 0.278095107175249 & 0.860952446412375 \tabularnewline
68 & 0.269203231102903 & 0.538406462205806 & 0.730796768897097 \tabularnewline
69 & 0.364495175787505 & 0.728990351575009 & 0.635504824212495 \tabularnewline
70 & 0.334000902483286 & 0.668001804966571 & 0.665999097516714 \tabularnewline
71 & 0.443101781168423 & 0.886203562336845 & 0.556898218831578 \tabularnewline
72 & 0.408390199013182 & 0.816780398026365 & 0.591609800986818 \tabularnewline
73 & 0.408893217545015 & 0.817786435090031 & 0.591106782454984 \tabularnewline
74 & 0.397135723521769 & 0.794271447043538 & 0.602864276478231 \tabularnewline
75 & 0.360034056544236 & 0.720068113088471 & 0.639965943455764 \tabularnewline
76 & 0.425793181707138 & 0.851586363414277 & 0.574206818292862 \tabularnewline
77 & 0.388042441145773 & 0.776084882291547 & 0.611957558854227 \tabularnewline
78 & 0.362094758709996 & 0.724189517419993 & 0.637905241290004 \tabularnewline
79 & 0.376793249549776 & 0.753586499099552 & 0.623206750450224 \tabularnewline
80 & 0.343116850306002 & 0.686233700612005 & 0.656883149693998 \tabularnewline
81 & 0.314522821419375 & 0.62904564283875 & 0.685477178580625 \tabularnewline
82 & 0.280862484334737 & 0.561724968669474 & 0.719137515665263 \tabularnewline
83 & 0.253282202256053 & 0.506564404512106 & 0.746717797743947 \tabularnewline
84 & 0.22342353203394 & 0.44684706406788 & 0.77657646796606 \tabularnewline
85 & 0.217294113012858 & 0.434588226025715 & 0.782705886987142 \tabularnewline
86 & 0.189821596081127 & 0.379643192162253 & 0.810178403918873 \tabularnewline
87 & 0.167487050049588 & 0.334974100099177 & 0.832512949950412 \tabularnewline
88 & 0.155126911424102 & 0.310253822848203 & 0.844873088575898 \tabularnewline
89 & 0.133636740163207 & 0.267273480326414 & 0.866363259836793 \tabularnewline
90 & 0.132269926658086 & 0.264539853316171 & 0.867730073341914 \tabularnewline
91 & 0.113156521251372 & 0.226313042502745 & 0.886843478748628 \tabularnewline
92 & 0.0988847358462607 & 0.197769471692521 & 0.901115264153739 \tabularnewline
93 & 0.084107031424216 & 0.168214062848432 & 0.915892968575784 \tabularnewline
94 & 0.08738790316334 & 0.17477580632668 & 0.91261209683666 \tabularnewline
95 & 0.0790559761014065 & 0.158111952202813 & 0.920944023898594 \tabularnewline
96 & 0.0661568156229523 & 0.132313631245905 & 0.933843184377048 \tabularnewline
97 & 0.0708757304760005 & 0.141751460952001 & 0.929124269524 \tabularnewline
98 & 0.0588724677628206 & 0.117744935525641 & 0.941127532237179 \tabularnewline
99 & 0.0488488408596171 & 0.0976976817192342 & 0.951151159140383 \tabularnewline
100 & 0.0429211722436998 & 0.0858423444873997 & 0.9570788277563 \tabularnewline
101 & 0.0375744296799354 & 0.0751488593598708 & 0.962425570320065 \tabularnewline
102 & 0.0434650218471356 & 0.0869300436942712 & 0.956534978152864 \tabularnewline
103 & 0.0366358021543772 & 0.0732716043087544 & 0.963364197845623 \tabularnewline
104 & 0.0328528463480109 & 0.0657056926960218 & 0.967147153651989 \tabularnewline
105 & 0.0391392019112128 & 0.0782784038224255 & 0.960860798088787 \tabularnewline
106 & 0.0340515709723964 & 0.0681031419447928 & 0.965948429027604 \tabularnewline
107 & 0.0276516450883661 & 0.0553032901767322 & 0.972348354911634 \tabularnewline
108 & 0.0267802706487375 & 0.0535605412974749 & 0.973219729351263 \tabularnewline
109 & 0.0217549951589296 & 0.0435099903178592 & 0.97824500484107 \tabularnewline
110 & 0.0177269006018732 & 0.0354538012037464 & 0.982273099398127 \tabularnewline
111 & 0.0140545390961181 & 0.0281090781922361 & 0.985945460903882 \tabularnewline
112 & 0.0141951812425168 & 0.0283903624850335 & 0.985804818757483 \tabularnewline
113 & 0.0128884921690441 & 0.0257769843380882 & 0.987111507830956 \tabularnewline
114 & 0.0188606395801474 & 0.0377212791602949 & 0.981139360419853 \tabularnewline
115 & 0.017729976921273 & 0.0354599538425461 & 0.982270023078727 \tabularnewline
116 & 0.0172344962398908 & 0.0344689924797817 & 0.982765503760109 \tabularnewline
117 & 0.0141627639097515 & 0.028325527819503 & 0.985837236090249 \tabularnewline
118 & 0.0142532264344367 & 0.0285064528688733 & 0.985746773565563 \tabularnewline
119 & 0.0114884126552615 & 0.022976825310523 & 0.988511587344739 \tabularnewline
120 & 0.0102850543158456 & 0.0205701086316911 & 0.989714945684154 \tabularnewline
121 & 0.00826190974683857 & 0.0165238194936771 & 0.991738090253161 \tabularnewline
122 & 0.0125185784288264 & 0.0250371568576529 & 0.987481421571174 \tabularnewline
123 & 0.0104472014289008 & 0.0208944028578016 & 0.989552798571099 \tabularnewline
124 & 0.00897374536423348 & 0.017947490728467 & 0.991026254635767 \tabularnewline
125 & 0.00729519177711646 & 0.0145903835542329 & 0.992704808222884 \tabularnewline
126 & 0.00577367002463953 & 0.0115473400492791 & 0.99422632997536 \tabularnewline
127 & 0.00525836312851318 & 0.0105167262570264 & 0.994741636871487 \tabularnewline
128 & 0.00425060919945049 & 0.00850121839890098 & 0.995749390800549 \tabularnewline
129 & 0.00600664147032773 & 0.0120132829406555 & 0.993993358529672 \tabularnewline
130 & 0.00660366581214464 & 0.0132073316242893 & 0.993396334187855 \tabularnewline
131 & 0.0137386016812282 & 0.0274772033624564 & 0.986261398318772 \tabularnewline
132 & 0.0164198260589355 & 0.0328396521178709 & 0.983580173941065 \tabularnewline
133 & 0.0176020397246574 & 0.0352040794493148 & 0.982397960275343 \tabularnewline
134 & 0.0166950823017053 & 0.0333901646034105 & 0.983304917698295 \tabularnewline
135 & 0.0133441479647128 & 0.0266882959294256 & 0.986655852035287 \tabularnewline
136 & 0.0112225172738552 & 0.0224450345477104 & 0.988777482726145 \tabularnewline
137 & 0.00891665732174927 & 0.0178333146434985 & 0.991083342678251 \tabularnewline
138 & 0.0111505421035487 & 0.0223010842070974 & 0.988849457896451 \tabularnewline
139 & 0.00955722763970109 & 0.0191144552794022 & 0.990442772360299 \tabularnewline
140 & 0.0113123869945974 & 0.0226247739891949 & 0.988687613005403 \tabularnewline
141 & 0.0179590782372215 & 0.035918156474443 & 0.982040921762778 \tabularnewline
142 & 0.016548886125227 & 0.033097772250454 & 0.983451113874773 \tabularnewline
143 & 0.0133058537213248 & 0.0266117074426496 & 0.986694146278675 \tabularnewline
144 & 0.0136988608033896 & 0.0273977216067793 & 0.98630113919661 \tabularnewline
145 & 0.0245794658590178 & 0.0491589317180356 & 0.975420534140982 \tabularnewline
146 & 0.0298359398435671 & 0.0596718796871343 & 0.970164060156433 \tabularnewline
147 & 0.0313175220167024 & 0.0626350440334047 & 0.968682477983298 \tabularnewline
148 & 0.0277117937652308 & 0.0554235875304616 & 0.972288206234769 \tabularnewline
149 & 0.0225524072318607 & 0.0451048144637214 & 0.977447592768139 \tabularnewline
150 & 0.0314966157980885 & 0.0629932315961771 & 0.968503384201912 \tabularnewline
151 & 0.026599896975728 & 0.053199793951456 & 0.973400103024272 \tabularnewline
152 & 0.0289459749746032 & 0.0578919499492064 & 0.971054025025397 \tabularnewline
153 & 0.0585376029886558 & 0.117075205977312 & 0.941462397011344 \tabularnewline
154 & 0.0564049858145926 & 0.112809971629185 & 0.943595014185407 \tabularnewline
155 & 0.0646082436931067 & 0.129216487386213 & 0.935391756306893 \tabularnewline
156 & 0.0549370528174881 & 0.109874105634976 & 0.945062947182512 \tabularnewline
157 & 0.0490188712046713 & 0.0980377424093427 & 0.950981128795329 \tabularnewline
158 & 0.0426895423542244 & 0.0853790847084488 & 0.957310457645776 \tabularnewline
159 & 0.0413295487361358 & 0.0826590974722717 & 0.958670451263864 \tabularnewline
160 & 0.035466989862597 & 0.070933979725194 & 0.964533010137403 \tabularnewline
161 & 0.028956465570349 & 0.0579129311406979 & 0.971043534429651 \tabularnewline
162 & 0.0236357082340207 & 0.0472714164680414 & 0.976364291765979 \tabularnewline
163 & 0.0193096388451007 & 0.0386192776902014 & 0.980690361154899 \tabularnewline
164 & 0.0163291097700003 & 0.0326582195400006 & 0.98367089023 \tabularnewline
165 & 0.0144500833787466 & 0.0289001667574932 & 0.985549916621253 \tabularnewline
166 & 0.0149486117613171 & 0.0298972235226343 & 0.985051388238683 \tabularnewline
167 & 0.0118842173824243 & 0.0237684347648485 & 0.988115782617576 \tabularnewline
168 & 0.0175132783229478 & 0.0350265566458956 & 0.982486721677052 \tabularnewline
169 & 0.0176340081819062 & 0.0352680163638125 & 0.982365991818094 \tabularnewline
170 & 0.0167353882634734 & 0.0334707765269468 & 0.983264611736527 \tabularnewline
171 & 0.0154566616276166 & 0.0309133232552332 & 0.984543338372383 \tabularnewline
172 & 0.0124723728775002 & 0.0249447457550004 & 0.9875276271225 \tabularnewline
173 & 0.012088212109315 & 0.02417642421863 & 0.987911787890685 \tabularnewline
174 & 0.0137748285514894 & 0.0275496571029788 & 0.986225171448511 \tabularnewline
175 & 0.017933505842758 & 0.035867011685516 & 0.982066494157242 \tabularnewline
176 & 0.014378215481752 & 0.028756430963504 & 0.985621784518248 \tabularnewline
177 & 0.0113523802111796 & 0.0227047604223591 & 0.98864761978882 \tabularnewline
178 & 0.00954556262059169 & 0.0190911252411834 & 0.990454437379408 \tabularnewline
179 & 0.00738975804519148 & 0.014779516090383 & 0.992610241954809 \tabularnewline
180 & 0.00650905214283659 & 0.0130181042856732 & 0.993490947857163 \tabularnewline
181 & 0.0053105202952831 & 0.0106210405905662 & 0.994689479704717 \tabularnewline
182 & 0.00408668688473492 & 0.00817337376946984 & 0.995913313115265 \tabularnewline
183 & 0.00442469291715467 & 0.00884938583430934 & 0.995575307082845 \tabularnewline
184 & 0.00335202292034106 & 0.00670404584068213 & 0.996647977079659 \tabularnewline
185 & 0.0916327023750673 & 0.183265404750135 & 0.908367297624933 \tabularnewline
186 & 0.0819279336027133 & 0.163855867205427 & 0.918072066397287 \tabularnewline
187 & 0.0904200022971107 & 0.180840004594221 & 0.909579997702889 \tabularnewline
188 & 0.0759005129200858 & 0.151801025840172 & 0.924099487079914 \tabularnewline
189 & 0.0677469226921066 & 0.135493845384213 & 0.932253077307893 \tabularnewline
190 & 0.056589711889844 & 0.113179423779688 & 0.943410288110156 \tabularnewline
191 & 0.05236507992328 & 0.10473015984656 & 0.94763492007672 \tabularnewline
192 & 0.0432573608856991 & 0.0865147217713982 & 0.956742639114301 \tabularnewline
193 & 0.0443752188199171 & 0.0887504376398343 & 0.955624781180083 \tabularnewline
194 & 0.0448592051783194 & 0.0897184103566387 & 0.955140794821681 \tabularnewline
195 & 0.0387913601226083 & 0.0775827202452165 & 0.961208639877392 \tabularnewline
196 & 0.0312142528712431 & 0.0624285057424862 & 0.968785747128757 \tabularnewline
197 & 0.0394148933458914 & 0.0788297866917827 & 0.960585106654109 \tabularnewline
198 & 0.0321836113026732 & 0.0643672226053465 & 0.967816388697327 \tabularnewline
199 & 0.0289642716290788 & 0.0579285432581575 & 0.971035728370921 \tabularnewline
200 & 0.0248569204696359 & 0.0497138409392718 & 0.975143079530364 \tabularnewline
201 & 0.0232462668440533 & 0.0464925336881065 & 0.976753733155947 \tabularnewline
202 & 0.0196501226195538 & 0.0393002452391076 & 0.980349877380446 \tabularnewline
203 & 0.0258061599601844 & 0.0516123199203687 & 0.974193840039816 \tabularnewline
204 & 0.0300558719824149 & 0.0601117439648298 & 0.969944128017585 \tabularnewline
205 & 0.0314773536744986 & 0.0629547073489971 & 0.968522646325501 \tabularnewline
206 & 0.0246734540502822 & 0.0493469081005644 & 0.975326545949718 \tabularnewline
207 & 0.0236195712607923 & 0.0472391425215845 & 0.976380428739208 \tabularnewline
208 & 0.0193097178187444 & 0.0386194356374887 & 0.980690282181256 \tabularnewline
209 & 0.0215317127034812 & 0.0430634254069623 & 0.978468287296519 \tabularnewline
210 & 0.0171599938260061 & 0.0343199876520122 & 0.982840006173994 \tabularnewline
211 & 0.0197200608102488 & 0.0394401216204976 & 0.980279939189751 \tabularnewline
212 & 0.0319860143610665 & 0.0639720287221329 & 0.968013985638933 \tabularnewline
213 & 0.0249009988083478 & 0.0498019976166957 & 0.975099001191652 \tabularnewline
214 & 0.0321996334420403 & 0.0643992668840806 & 0.96780036655796 \tabularnewline
215 & 0.0273232056383283 & 0.0546464112766565 & 0.972676794361672 \tabularnewline
216 & 0.0211375747978418 & 0.0422751495956837 & 0.978862425202158 \tabularnewline
217 & 0.0232205516167757 & 0.0464411032335514 & 0.976779448383224 \tabularnewline
218 & 0.0195797326479916 & 0.0391594652959831 & 0.980420267352008 \tabularnewline
219 & 0.0181914335051249 & 0.0363828670102498 & 0.981808566494875 \tabularnewline
220 & 0.0139104652747253 & 0.0278209305494506 & 0.986089534725275 \tabularnewline
221 & 0.0115846356307567 & 0.0231692712615133 & 0.988415364369243 \tabularnewline
222 & 0.00831863645075521 & 0.0166372729015104 & 0.991681363549245 \tabularnewline
223 & 0.00638020378999746 & 0.0127604075799949 & 0.993619796210003 \tabularnewline
224 & 0.00480906588265554 & 0.00961813176531108 & 0.995190934117344 \tabularnewline
225 & 0.00409375045076022 & 0.00818750090152044 & 0.99590624954924 \tabularnewline
226 & 0.00946681005766529 & 0.0189336201153306 & 0.990533189942335 \tabularnewline
227 & 0.00741795109278939 & 0.0148359021855788 & 0.992582048907211 \tabularnewline
228 & 0.00548896145726457 & 0.0109779229145291 & 0.994511038542735 \tabularnewline
229 & 0.00392589658277771 & 0.00785179316555542 & 0.996074103417222 \tabularnewline
230 & 0.00289046341687466 & 0.00578092683374933 & 0.997109536583125 \tabularnewline
231 & 0.00260618189028514 & 0.00521236378057027 & 0.997393818109715 \tabularnewline
232 & 0.00613734309401658 & 0.0122746861880332 & 0.993862656905983 \tabularnewline
233 & 0.0247649674569371 & 0.0495299349138743 & 0.975235032543063 \tabularnewline
234 & 0.0377477579547085 & 0.075495515909417 & 0.962252242045291 \tabularnewline
235 & 0.0272310989368987 & 0.0544621978737975 & 0.972768901063101 \tabularnewline
236 & 0.0228254490818122 & 0.0456508981636245 & 0.977174550918188 \tabularnewline
237 & 0.19737072198452 & 0.39474144396904 & 0.80262927801548 \tabularnewline
238 & 0.155667521678584 & 0.311335043357167 & 0.844332478321416 \tabularnewline
239 & 0.129607141019934 & 0.259214282039867 & 0.870392858980066 \tabularnewline
240 & 0.100544198023488 & 0.201088396046976 & 0.899455801976512 \tabularnewline
241 & 0.0884081811254627 & 0.176816362250925 & 0.911591818874537 \tabularnewline
242 & 0.137938494268997 & 0.275876988537994 & 0.862061505731003 \tabularnewline
243 & 0.112959828401644 & 0.225919656803287 & 0.887040171598356 \tabularnewline
244 & 0.118293730724496 & 0.236587461448991 & 0.881706269275504 \tabularnewline
245 & 0.0968198344744189 & 0.193639668948838 & 0.903180165525581 \tabularnewline
246 & 0.082174010171872 & 0.164348020343744 & 0.917825989828128 \tabularnewline
247 & 0.0530560832162604 & 0.106112166432521 & 0.94694391678374 \tabularnewline
248 & 0.0452028729880969 & 0.0904057459761938 & 0.954797127011903 \tabularnewline
249 & 0.040451903681973 & 0.080903807363946 & 0.959548096318027 \tabularnewline
250 & 0.115496462193852 & 0.230992924387703 & 0.884503537806148 \tabularnewline
251 & 0.0947038411535398 & 0.18940768230708 & 0.90529615884646 \tabularnewline
252 & 0.431438999835686 & 0.862877999671371 & 0.568561000164314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186039&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]12[/C][C]0.0949069336717827[/C][C]0.189813867343565[/C][C]0.905093066328217[/C][/ROW]
[ROW][C]13[/C][C]0.168821052440469[/C][C]0.337642104880937[/C][C]0.831178947559531[/C][/ROW]
[ROW][C]14[/C][C]0.17886382794067[/C][C]0.357727655881341[/C][C]0.82113617205933[/C][/ROW]
[ROW][C]15[/C][C]0.102108221816446[/C][C]0.204216443632893[/C][C]0.897891778183554[/C][/ROW]
[ROW][C]16[/C][C]0.0784281971443364[/C][C]0.156856394288673[/C][C]0.921571802855664[/C][/ROW]
[ROW][C]17[/C][C]0.0870237660597908[/C][C]0.174047532119582[/C][C]0.912976233940209[/C][/ROW]
[ROW][C]18[/C][C]0.213223439837097[/C][C]0.426446879674194[/C][C]0.786776560162903[/C][/ROW]
[ROW][C]19[/C][C]0.175810464451898[/C][C]0.351620928903795[/C][C]0.824189535548102[/C][/ROW]
[ROW][C]20[/C][C]0.139406041965233[/C][C]0.278812083930466[/C][C]0.860593958034767[/C][/ROW]
[ROW][C]21[/C][C]0.107616872867732[/C][C]0.215233745735463[/C][C]0.892383127132269[/C][/ROW]
[ROW][C]22[/C][C]0.131400316307911[/C][C]0.262800632615821[/C][C]0.868599683692089[/C][/ROW]
[ROW][C]23[/C][C]0.22984858009041[/C][C]0.45969716018082[/C][C]0.77015141990959[/C][/ROW]
[ROW][C]24[/C][C]0.34540067818832[/C][C]0.690801356376639[/C][C]0.65459932181168[/C][/ROW]
[ROW][C]25[/C][C]0.282158756508175[/C][C]0.564317513016349[/C][C]0.717841243491825[/C][/ROW]
[ROW][C]26[/C][C]0.237323312240147[/C][C]0.474646624480294[/C][C]0.762676687759853[/C][/ROW]
[ROW][C]27[/C][C]0.227896245738457[/C][C]0.455792491476914[/C][C]0.772103754261543[/C][/ROW]
[ROW][C]28[/C][C]0.338485052212977[/C][C]0.676970104425954[/C][C]0.661514947787023[/C][/ROW]
[ROW][C]29[/C][C]0.289325481134631[/C][C]0.578650962269262[/C][C]0.710674518865369[/C][/ROW]
[ROW][C]30[/C][C]0.397882859936623[/C][C]0.795765719873245[/C][C]0.602117140063377[/C][/ROW]
[ROW][C]31[/C][C]0.356890257488035[/C][C]0.71378051497607[/C][C]0.643109742511965[/C][/ROW]
[ROW][C]32[/C][C]0.32941658209055[/C][C]0.6588331641811[/C][C]0.67058341790945[/C][/ROW]
[ROW][C]33[/C][C]0.314121460060036[/C][C]0.628242920120072[/C][C]0.685878539939964[/C][/ROW]
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[ROW][C]180[/C][C]0.00650905214283659[/C][C]0.0130181042856732[/C][C]0.993490947857163[/C][/ROW]
[ROW][C]181[/C][C]0.0053105202952831[/C][C]0.0106210405905662[/C][C]0.994689479704717[/C][/ROW]
[ROW][C]182[/C][C]0.00408668688473492[/C][C]0.00817337376946984[/C][C]0.995913313115265[/C][/ROW]
[ROW][C]183[/C][C]0.00442469291715467[/C][C]0.00884938583430934[/C][C]0.995575307082845[/C][/ROW]
[ROW][C]184[/C][C]0.00335202292034106[/C][C]0.00670404584068213[/C][C]0.996647977079659[/C][/ROW]
[ROW][C]185[/C][C]0.0916327023750673[/C][C]0.183265404750135[/C][C]0.908367297624933[/C][/ROW]
[ROW][C]186[/C][C]0.0819279336027133[/C][C]0.163855867205427[/C][C]0.918072066397287[/C][/ROW]
[ROW][C]187[/C][C]0.0904200022971107[/C][C]0.180840004594221[/C][C]0.909579997702889[/C][/ROW]
[ROW][C]188[/C][C]0.0759005129200858[/C][C]0.151801025840172[/C][C]0.924099487079914[/C][/ROW]
[ROW][C]189[/C][C]0.0677469226921066[/C][C]0.135493845384213[/C][C]0.932253077307893[/C][/ROW]
[ROW][C]190[/C][C]0.056589711889844[/C][C]0.113179423779688[/C][C]0.943410288110156[/C][/ROW]
[ROW][C]191[/C][C]0.05236507992328[/C][C]0.10473015984656[/C][C]0.94763492007672[/C][/ROW]
[ROW][C]192[/C][C]0.0432573608856991[/C][C]0.0865147217713982[/C][C]0.956742639114301[/C][/ROW]
[ROW][C]193[/C][C]0.0443752188199171[/C][C]0.0887504376398343[/C][C]0.955624781180083[/C][/ROW]
[ROW][C]194[/C][C]0.0448592051783194[/C][C]0.0897184103566387[/C][C]0.955140794821681[/C][/ROW]
[ROW][C]195[/C][C]0.0387913601226083[/C][C]0.0775827202452165[/C][C]0.961208639877392[/C][/ROW]
[ROW][C]196[/C][C]0.0312142528712431[/C][C]0.0624285057424862[/C][C]0.968785747128757[/C][/ROW]
[ROW][C]197[/C][C]0.0394148933458914[/C][C]0.0788297866917827[/C][C]0.960585106654109[/C][/ROW]
[ROW][C]198[/C][C]0.0321836113026732[/C][C]0.0643672226053465[/C][C]0.967816388697327[/C][/ROW]
[ROW][C]199[/C][C]0.0289642716290788[/C][C]0.0579285432581575[/C][C]0.971035728370921[/C][/ROW]
[ROW][C]200[/C][C]0.0248569204696359[/C][C]0.0497138409392718[/C][C]0.975143079530364[/C][/ROW]
[ROW][C]201[/C][C]0.0232462668440533[/C][C]0.0464925336881065[/C][C]0.976753733155947[/C][/ROW]
[ROW][C]202[/C][C]0.0196501226195538[/C][C]0.0393002452391076[/C][C]0.980349877380446[/C][/ROW]
[ROW][C]203[/C][C]0.0258061599601844[/C][C]0.0516123199203687[/C][C]0.974193840039816[/C][/ROW]
[ROW][C]204[/C][C]0.0300558719824149[/C][C]0.0601117439648298[/C][C]0.969944128017585[/C][/ROW]
[ROW][C]205[/C][C]0.0314773536744986[/C][C]0.0629547073489971[/C][C]0.968522646325501[/C][/ROW]
[ROW][C]206[/C][C]0.0246734540502822[/C][C]0.0493469081005644[/C][C]0.975326545949718[/C][/ROW]
[ROW][C]207[/C][C]0.0236195712607923[/C][C]0.0472391425215845[/C][C]0.976380428739208[/C][/ROW]
[ROW][C]208[/C][C]0.0193097178187444[/C][C]0.0386194356374887[/C][C]0.980690282181256[/C][/ROW]
[ROW][C]209[/C][C]0.0215317127034812[/C][C]0.0430634254069623[/C][C]0.978468287296519[/C][/ROW]
[ROW][C]210[/C][C]0.0171599938260061[/C][C]0.0343199876520122[/C][C]0.982840006173994[/C][/ROW]
[ROW][C]211[/C][C]0.0197200608102488[/C][C]0.0394401216204976[/C][C]0.980279939189751[/C][/ROW]
[ROW][C]212[/C][C]0.0319860143610665[/C][C]0.0639720287221329[/C][C]0.968013985638933[/C][/ROW]
[ROW][C]213[/C][C]0.0249009988083478[/C][C]0.0498019976166957[/C][C]0.975099001191652[/C][/ROW]
[ROW][C]214[/C][C]0.0321996334420403[/C][C]0.0643992668840806[/C][C]0.96780036655796[/C][/ROW]
[ROW][C]215[/C][C]0.0273232056383283[/C][C]0.0546464112766565[/C][C]0.972676794361672[/C][/ROW]
[ROW][C]216[/C][C]0.0211375747978418[/C][C]0.0422751495956837[/C][C]0.978862425202158[/C][/ROW]
[ROW][C]217[/C][C]0.0232205516167757[/C][C]0.0464411032335514[/C][C]0.976779448383224[/C][/ROW]
[ROW][C]218[/C][C]0.0195797326479916[/C][C]0.0391594652959831[/C][C]0.980420267352008[/C][/ROW]
[ROW][C]219[/C][C]0.0181914335051249[/C][C]0.0363828670102498[/C][C]0.981808566494875[/C][/ROW]
[ROW][C]220[/C][C]0.0139104652747253[/C][C]0.0278209305494506[/C][C]0.986089534725275[/C][/ROW]
[ROW][C]221[/C][C]0.0115846356307567[/C][C]0.0231692712615133[/C][C]0.988415364369243[/C][/ROW]
[ROW][C]222[/C][C]0.00831863645075521[/C][C]0.0166372729015104[/C][C]0.991681363549245[/C][/ROW]
[ROW][C]223[/C][C]0.00638020378999746[/C][C]0.0127604075799949[/C][C]0.993619796210003[/C][/ROW]
[ROW][C]224[/C][C]0.00480906588265554[/C][C]0.00961813176531108[/C][C]0.995190934117344[/C][/ROW]
[ROW][C]225[/C][C]0.00409375045076022[/C][C]0.00818750090152044[/C][C]0.99590624954924[/C][/ROW]
[ROW][C]226[/C][C]0.00946681005766529[/C][C]0.0189336201153306[/C][C]0.990533189942335[/C][/ROW]
[ROW][C]227[/C][C]0.00741795109278939[/C][C]0.0148359021855788[/C][C]0.992582048907211[/C][/ROW]
[ROW][C]228[/C][C]0.00548896145726457[/C][C]0.0109779229145291[/C][C]0.994511038542735[/C][/ROW]
[ROW][C]229[/C][C]0.00392589658277771[/C][C]0.00785179316555542[/C][C]0.996074103417222[/C][/ROW]
[ROW][C]230[/C][C]0.00289046341687466[/C][C]0.00578092683374933[/C][C]0.997109536583125[/C][/ROW]
[ROW][C]231[/C][C]0.00260618189028514[/C][C]0.00521236378057027[/C][C]0.997393818109715[/C][/ROW]
[ROW][C]232[/C][C]0.00613734309401658[/C][C]0.0122746861880332[/C][C]0.993862656905983[/C][/ROW]
[ROW][C]233[/C][C]0.0247649674569371[/C][C]0.0495299349138743[/C][C]0.975235032543063[/C][/ROW]
[ROW][C]234[/C][C]0.0377477579547085[/C][C]0.075495515909417[/C][C]0.962252242045291[/C][/ROW]
[ROW][C]235[/C][C]0.0272310989368987[/C][C]0.0544621978737975[/C][C]0.972768901063101[/C][/ROW]
[ROW][C]236[/C][C]0.0228254490818122[/C][C]0.0456508981636245[/C][C]0.977174550918188[/C][/ROW]
[ROW][C]237[/C][C]0.19737072198452[/C][C]0.39474144396904[/C][C]0.80262927801548[/C][/ROW]
[ROW][C]238[/C][C]0.155667521678584[/C][C]0.311335043357167[/C][C]0.844332478321416[/C][/ROW]
[ROW][C]239[/C][C]0.129607141019934[/C][C]0.259214282039867[/C][C]0.870392858980066[/C][/ROW]
[ROW][C]240[/C][C]0.100544198023488[/C][C]0.201088396046976[/C][C]0.899455801976512[/C][/ROW]
[ROW][C]241[/C][C]0.0884081811254627[/C][C]0.176816362250925[/C][C]0.911591818874537[/C][/ROW]
[ROW][C]242[/C][C]0.137938494268997[/C][C]0.275876988537994[/C][C]0.862061505731003[/C][/ROW]
[ROW][C]243[/C][C]0.112959828401644[/C][C]0.225919656803287[/C][C]0.887040171598356[/C][/ROW]
[ROW][C]244[/C][C]0.118293730724496[/C][C]0.236587461448991[/C][C]0.881706269275504[/C][/ROW]
[ROW][C]245[/C][C]0.0968198344744189[/C][C]0.193639668948838[/C][C]0.903180165525581[/C][/ROW]
[ROW][C]246[/C][C]0.082174010171872[/C][C]0.164348020343744[/C][C]0.917825989828128[/C][/ROW]
[ROW][C]247[/C][C]0.0530560832162604[/C][C]0.106112166432521[/C][C]0.94694391678374[/C][/ROW]
[ROW][C]248[/C][C]0.0452028729880969[/C][C]0.0904057459761938[/C][C]0.954797127011903[/C][/ROW]
[ROW][C]249[/C][C]0.040451903681973[/C][C]0.080903807363946[/C][C]0.959548096318027[/C][/ROW]
[ROW][C]250[/C][C]0.115496462193852[/C][C]0.230992924387703[/C][C]0.884503537806148[/C][/ROW]
[ROW][C]251[/C][C]0.0947038411535398[/C][C]0.18940768230708[/C][C]0.90529615884646[/C][/ROW]
[ROW][C]252[/C][C]0.431438999835686[/C][C]0.862877999671371[/C][C]0.568561000164314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186039&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186039&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
120.09490693367178270.1898138673435650.905093066328217
130.1688210524404690.3376421048809370.831178947559531
140.178863827940670.3577276558813410.82113617205933
150.1021082218164460.2042164436328930.897891778183554
160.07842819714433640.1568563942886730.921571802855664
170.08702376605979080.1740475321195820.912976233940209
180.2132234398370970.4264468796741940.786776560162903
190.1758104644518980.3516209289037950.824189535548102
200.1394060419652330.2788120839304660.860593958034767
210.1076168728677320.2152337457354630.892383127132269
220.1314003163079110.2628006326158210.868599683692089
230.229848580090410.459697160180820.77015141990959
240.345400678188320.6908013563766390.65459932181168
250.2821587565081750.5643175130163490.717841243491825
260.2373233122401470.4746466244802940.762676687759853
270.2278962457384570.4557924914769140.772103754261543
280.3384850522129770.6769701044259540.661514947787023
290.2893254811346310.5786509622692620.710674518865369
300.3978828599366230.7957657198732450.602117140063377
310.3568902574880350.713780514976070.643109742511965
320.329416582090550.65883316418110.67058341790945
330.3141214600600360.6282429201200720.685878539939964
340.2782628951098780.5565257902197550.721737104890122
350.2368206844126130.4736413688252260.763179315587387
360.3669047636406810.7338095272813620.633095236359319
370.3956217287057510.7912434574115020.604378271294249
380.37157667251540.7431533450308010.6284233274846
390.416207602576150.83241520515230.58379239742385
400.3965466505621470.7930933011242930.603453349437853
410.3577995707434310.7155991414868630.642200429256569
420.319486473803070.6389729476061410.68051352619693
430.3384091031573870.6768182063147750.661590896842613
440.291402618208390.5828052364167810.70859738179161
450.264493101647080.528986203294160.73550689835292
460.4416124751845530.8832249503691070.558387524815447
470.5322670026109670.9354659947780670.467732997389033
480.4892016963859960.9784033927719920.510798303614004
490.5136426551357230.9727146897285540.486357344864277
500.4866219481787860.9732438963575720.513378051821214
510.4415572589751860.8831145179503720.558442741024814
520.4004250108969730.8008500217939450.599574989103027
530.3998641474306660.7997282948613320.600135852569334
540.3580805641964730.7161611283929460.641919435803527
550.3460959966995090.6921919933990180.653904003300491
560.3433011269468690.6866022538937380.656698873053131
570.3042398889216210.6084797778432420.695760111078379
580.2857200862422750.571440172484550.714279913757725
590.255885142827490.5117702856549790.74411485717251
600.2763078016978720.5526156033957430.723692198302128
610.2529929042034120.5059858084068250.747007095796588
620.228275085332220.4565501706644410.77172491466778
630.199677701775130.3993554035502610.80032229822487
640.1720118990507720.3440237981015430.827988100949228
650.1517815382386840.3035630764773680.848218461761316
660.1430713872026180.2861427744052370.856928612797382
670.1390475535876250.2780951071752490.860952446412375
680.2692032311029030.5384064622058060.730796768897097
690.3644951757875050.7289903515750090.635504824212495
700.3340009024832860.6680018049665710.665999097516714
710.4431017811684230.8862035623368450.556898218831578
720.4083901990131820.8167803980263650.591609800986818
730.4088932175450150.8177864350900310.591106782454984
740.3971357235217690.7942714470435380.602864276478231
750.3600340565442360.7200681130884710.639965943455764
760.4257931817071380.8515863634142770.574206818292862
770.3880424411457730.7760848822915470.611957558854227
780.3620947587099960.7241895174199930.637905241290004
790.3767932495497760.7535864990995520.623206750450224
800.3431168503060020.6862337006120050.656883149693998
810.3145228214193750.629045642838750.685477178580625
820.2808624843347370.5617249686694740.719137515665263
830.2532822022560530.5065644045121060.746717797743947
840.223423532033940.446847064067880.77657646796606
850.2172941130128580.4345882260257150.782705886987142
860.1898215960811270.3796431921622530.810178403918873
870.1674870500495880.3349741000991770.832512949950412
880.1551269114241020.3102538228482030.844873088575898
890.1336367401632070.2672734803264140.866363259836793
900.1322699266580860.2645398533161710.867730073341914
910.1131565212513720.2263130425027450.886843478748628
920.09888473584626070.1977694716925210.901115264153739
930.0841070314242160.1682140628484320.915892968575784
940.087387903163340.174775806326680.91261209683666
950.07905597610140650.1581119522028130.920944023898594
960.06615681562295230.1323136312459050.933843184377048
970.07087573047600050.1417514609520010.929124269524
980.05887246776282060.1177449355256410.941127532237179
990.04884884085961710.09769768171923420.951151159140383
1000.04292117224369980.08584234448739970.9570788277563
1010.03757442967993540.07514885935987080.962425570320065
1020.04346502184713560.08693004369427120.956534978152864
1030.03663580215437720.07327160430875440.963364197845623
1040.03285284634801090.06570569269602180.967147153651989
1050.03913920191121280.07827840382242550.960860798088787
1060.03405157097239640.06810314194479280.965948429027604
1070.02765164508836610.05530329017673220.972348354911634
1080.02678027064873750.05356054129747490.973219729351263
1090.02175499515892960.04350999031785920.97824500484107
1100.01772690060187320.03545380120374640.982273099398127
1110.01405453909611810.02810907819223610.985945460903882
1120.01419518124251680.02839036248503350.985804818757483
1130.01288849216904410.02577698433808820.987111507830956
1140.01886063958014740.03772127916029490.981139360419853
1150.0177299769212730.03545995384254610.982270023078727
1160.01723449623989080.03446899247978170.982765503760109
1170.01416276390975150.0283255278195030.985837236090249
1180.01425322643443670.02850645286887330.985746773565563
1190.01148841265526150.0229768253105230.988511587344739
1200.01028505431584560.02057010863169110.989714945684154
1210.008261909746838570.01652381949367710.991738090253161
1220.01251857842882640.02503715685765290.987481421571174
1230.01044720142890080.02089440285780160.989552798571099
1240.008973745364233480.0179474907284670.991026254635767
1250.007295191777116460.01459038355423290.992704808222884
1260.005773670024639530.01154734004927910.99422632997536
1270.005258363128513180.01051672625702640.994741636871487
1280.004250609199450490.008501218398900980.995749390800549
1290.006006641470327730.01201328294065550.993993358529672
1300.006603665812144640.01320733162428930.993396334187855
1310.01373860168122820.02747720336245640.986261398318772
1320.01641982605893550.03283965211787090.983580173941065
1330.01760203972465740.03520407944931480.982397960275343
1340.01669508230170530.03339016460341050.983304917698295
1350.01334414796471280.02668829592942560.986655852035287
1360.01122251727385520.02244503454771040.988777482726145
1370.008916657321749270.01783331464349850.991083342678251
1380.01115054210354870.02230108420709740.988849457896451
1390.009557227639701090.01911445527940220.990442772360299
1400.01131238699459740.02262477398919490.988687613005403
1410.01795907823722150.0359181564744430.982040921762778
1420.0165488861252270.0330977722504540.983451113874773
1430.01330585372132480.02661170744264960.986694146278675
1440.01369886080338960.02739772160677930.98630113919661
1450.02457946585901780.04915893171803560.975420534140982
1460.02983593984356710.05967187968713430.970164060156433
1470.03131752201670240.06263504403340470.968682477983298
1480.02771179376523080.05542358753046160.972288206234769
1490.02255240723186070.04510481446372140.977447592768139
1500.03149661579808850.06299323159617710.968503384201912
1510.0265998969757280.0531997939514560.973400103024272
1520.02894597497460320.05789194994920640.971054025025397
1530.05853760298865580.1170752059773120.941462397011344
1540.05640498581459260.1128099716291850.943595014185407
1550.06460824369310670.1292164873862130.935391756306893
1560.05493705281748810.1098741056349760.945062947182512
1570.04901887120467130.09803774240934270.950981128795329
1580.04268954235422440.08537908470844880.957310457645776
1590.04132954873613580.08265909747227170.958670451263864
1600.0354669898625970.0709339797251940.964533010137403
1610.0289564655703490.05791293114069790.971043534429651
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1750.0179335058427580.0358670116855160.982066494157242
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1770.01135238021117960.02270476042235910.98864761978882
1780.009545562620591690.01909112524118340.990454437379408
1790.007389758045191480.0147795160903830.992610241954809
1800.006509052142836590.01301810428567320.993490947857163
1810.00531052029528310.01062104059056620.994689479704717
1820.004086686884734920.008173373769469840.995913313115265
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1860.08192793360271330.1638558672054270.918072066397287
1870.09042000229711070.1808400045942210.909579997702889
1880.07590051292008580.1518010258401720.924099487079914
1890.06774692269210660.1354938453842130.932253077307893
1900.0565897118898440.1131794237796880.943410288110156
1910.052365079923280.104730159846560.94763492007672
1920.04325736088569910.08651472177139820.956742639114301
1930.04437521881991710.08875043763983430.955624781180083
1940.04485920517831940.08971841035663870.955140794821681
1950.03879136012260830.07758272024521650.961208639877392
1960.03121425287124310.06242850574248620.968785747128757
1970.03941489334589140.07882978669178270.960585106654109
1980.03218361130267320.06436722260534650.967816388697327
1990.02896427162907880.05792854325815750.971035728370921
2000.02485692046963590.04971384093927180.975143079530364
2010.02324626684405330.04649253368810650.976753733155947
2020.01965012261955380.03930024523910760.980349877380446
2030.02580615996018440.05161231992036870.974193840039816
2040.03005587198241490.06011174396482980.969944128017585
2050.03147735367449860.06295470734899710.968522646325501
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2090.02153171270348120.04306342540696230.978468287296519
2100.01715999382600610.03431998765201220.982840006173994
2110.01972006081024880.03944012162049760.980279939189751
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2130.02490099880834780.04980199761669570.975099001191652
2140.03219963344204030.06439926688408060.96780036655796
2150.02732320563832830.05464641127665650.972676794361672
2160.02113757479784180.04227514959568370.978862425202158
2170.02322055161677570.04644110323355140.976779448383224
2180.01957973264799160.03915946529598310.980420267352008
2190.01819143350512490.03638286701024980.981808566494875
2200.01391046527472530.02782093054945060.986089534725275
2210.01158463563075670.02316927126151330.988415364369243
2220.008318636450755210.01663727290151040.991681363549245
2230.006380203789997460.01276040757999490.993619796210003
2240.004809065882655540.009618131765311080.995190934117344
2250.004093750450760220.008187500901520440.99590624954924
2260.009466810057665290.01893362011533060.990533189942335
2270.007417951092789390.01483590218557880.992582048907211
2280.005488961457264570.01097792291452910.994511038542735
2290.003925896582777710.007851793165555420.996074103417222
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2320.006137343094016580.01227468618803320.993862656905983
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2360.02282544908181220.04565089816362450.977174550918188
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2400.1005441980234880.2010883960469760.899455801976512
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2420.1379384942689970.2758769885379940.862061505731003
2430.1129598284016440.2259196568032870.887040171598356
2440.1182937307244960.2365874614489910.881706269275504
2450.09681983447441890.1936396689488380.903180165525581
2460.0821740101718720.1643480203437440.917825989828128
2470.05305608321626040.1061121664325210.94694391678374
2480.04520287298809690.09040574597619380.954797127011903
2490.0404519036819730.0809038073639460.959548096318027
2500.1154964621938520.2309929243877030.884503537806148
2510.09470384115353980.189407682307080.90529615884646
2520.4314389998356860.8628779996713710.568561000164314






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.037344398340249NOK
5% type I error level900.37344398340249NOK
10% type I error level1290.535269709543568NOK

\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 & 9 & 0.037344398340249 & NOK \tabularnewline
5% type I error level & 90 & 0.37344398340249 & NOK \tabularnewline
10% type I error level & 129 & 0.535269709543568 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=186039&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]9[/C][C]0.037344398340249[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]90[/C][C]0.37344398340249[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]129[/C][C]0.535269709543568[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=186039&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=186039&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.037344398340249NOK
5% type I error level900.37344398340249NOK
10% type I error level1290.535269709543568NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

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