Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 17 Nov 2011 10:13:22 -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/2011/Nov/17/t13215428769s96d16cludneec.htm/, Retrieved Fri, 29 Mar 2024 14:42:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=144867, Retrieved Fri, 29 Mar 2024 14:42:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [WS7 - Tutorial (1)] [2011-11-17 15:13:22] [82ceb5b481b3a9ad89a8151bb4a3670f] [Current]
-   PD      [Multiple Regression] [WS7 - tutorial (3)] [2011-11-21 17:37:36] [16760482ab7535714acc81f7eb88a6ca]
-  M          [Multiple Regression] [WS7 3] [2011-11-22 18:27:32] [74be16979710d4c4e7c6647856088456]
-  M        [Multiple Regression] [WS 7 1] [2011-11-22 16:57:21] [74be16979710d4c4e7c6647856088456]
-  M        [Multiple Regression] [WS7 2] [2011-11-22 17:03:03] [74be16979710d4c4e7c6647856088456]
- RMP       [Recursive Partitioning (Regression Trees)] [Regression Tree -...] [2011-12-22 11:26:31] [16760482ab7535714acc81f7eb88a6ca]
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Post a new message
Dataseries X:
146455	1	22	68	128	95556
84944	4	20	72	89	54565
113337	9	24	37	68	63016
128655	2	21	70	108	79774
74398	1	15	30	51	31258
35523	2	16	53	33	52491
293403	0	20	74	119	91256
32750	0	18	22	5	22807
106539	5	19	68	63	77411
130539	0	20	47	66	48821
154991	0	25	87	98	52295
126683	7	37	123	71	63262
100672	6	23	69	55	50466
179562	3	28	89	116	62932
125971	4	25	45	71	38439
234509	0	35	122	120	70817
158980	4	20	75	122	105965
184217	3	22	45	74	73795
107342	0	19	53	111	82043
141371	5	26	96	103	74349
154730	0	27	82	98	82204
264020	1	22	76	100	55709
90938	3	15	51	42	37137
101324	5	26	104	100	70780
130232	0	24	83	105	55027
137793	0	22	78	77	56699
161678	4	21	59	83	65911
151503	0	23	83	98	56316
105324	0	21	71	46	26982
175914	0	25	81	95	54628
181853	3	25	93	91	96750
114928	4	28	72	91	53009
190410	1	30	107	94	64664
61499	4	20	75	15	36990
223004	1	23	84	137	85224
167131	0	25	69	56	37048
233482	0	26	90	78	59635
121185	2	20	51	68	42051
78776	1	8	18	34	26998
188967	2	20	75	94	63717
199512	8	21	59	82	55071
102531	5	25	63	63	40001
118958	3	20	68	58	54506
68948	4	18	47	43	35838
93125	1	21	29	36	50838
277108	2	22	69	64	86997
78800	2	26	66	21	33032
157250	0	30	106	104	61704
210554	6	24	73	124	117986
127324	3	26	87	101	56733
114397	0	18	65	85	55064
24188	0	4	7	7	5950
246209	6	31	111	124	84607
65029	5	18	61	21	32551
98030	3	14	41	35	31701
173587	1	20	70	95	71170
172684	5	30	112	102	101773
191381	5	20	71	212	101653
191276	0	26	90	141	81493
134043	9	20	69	54	55901
233406	6	27	85	117	109104
195304	6	18	47	145	114425
127619	5	27	50	50	36311
162810	6	22	76	80	70027
129100	2	19	60	87	73713
108715	0	15	35	78	40671
106469	3	19	72	86	89041
142069	8	28	88	82	57231
143937	2	20	66	139	78792
84256	5	17	58	75	59155
118807	11	25	81	70	55827
69471	6	20	63	25	22618
122433	5	25	91	66	58425
131122	1	20	50	89	65724
94763	0	22	75	99	56979
188780	3	25	85	98	72369
191467	3	20	75	104	79194
105615	6	23	70	48	202316
89318	1	22	78	81	44970
107335	0	21	61	64	49319
98599	1	18	55	44	36252
260646	0	25	60	104	75741
131876	5	22	83	36	38417
119291	2	25	38	120	64102
80953	0	8	27	58	56622
99768	0	21	62	27	15430
84572	5	22	82	84	72571
202373	1	21	79	56	67271
166790	0	30	59	46	43460
99946	1	23	80	119	99501
116900	1	20	36	57	28340
142146	2	24	88	139	76013
99246	4	21	63	51	37361
156833	1	20	73	85	48204
175078	4	20	71	91	76168
130533	0	20	76	79	85168
142339	2	20	67	142	125410
176789	0	23	66	149	123328
181379	7	33	123	96	83038
228548	7	19	65	198	120087
142141	6	27	87	61	91939
167845	0	25	77	145	103646
103012	0	20	37	26	29467
43287	4	19	64	49	43750
125366	4	15	22	68	34497
118372	0	21	35	145	66477
135171	0	22	61	82	71181
175568	0	24	80	102	74482
74112	0	19	54	52	174949
88817	0	20	60	56	46765
164767	4	23	87	80	90257
141933	0	27	75	99	51370
22938	0	1	0	11	1168
115199	0	20	54	87	51360
61857	4	11	30	28	25162
91185	0	27	66	67	21067
213765	1	22	56	150	58233
21054	0	0	0	4	855
167105	5	17	32	71	85903
31414	0	8	9	39	14116
178863	1	23	78	87	57637
126681	7	26	90	66	94137
64320	5	20	56	23	62147
67746	2	16	35	56	62832
38214	0	8	21	16	8773
90961	1	22	78	49	63785
181510	0	33	118	108	65196
116775	0	28	83	112	73087
223914	2	26	89	110	72631
185139	0	27	83	126	86281
242879	2	35	124	155	162365
139144	0	21	76	75	56530
75812	0	20	57	30	35606
178218	4	24	91	78	70111
246834	4	26	89	135	92046
50999	8	20	66	8	63989
223842	0	22	82	114	104911
93577	4	24	63	60	43448
155383	0	23	75	99	60029
111664	1	22	59	98	38650
75426	0	12	19	33	47261
243551	9	21	57	93	73586
136548	0	21	62	157	83042
173260	3	21	78	15	37238
185039	7	25	73	98	63958
67507	5	32	112	49	78956
139350	2	24	79	88	99518
172964	1	28	96	151	111436
0	9	0	0	0	0
14688	0	0	0	5	6023
98	0	0	0	0	0
455	0	0	0	0	0
0	1	0	0	0	0
0	0	0	0	0	0
128066	2	20	48	80	42564
176460	1	27	55	122	38885
0	0	0	0	0	0
203	0	0	0	0	0
7199	0	0	0	6	1644
46660	0	5	13	13	6179
17547	0	1	4	3	3926
73567	0	23	31	18	23238
969	0	0	0	0	0
101060	2	16	29	48	49288




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144867&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]7 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=144867&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144867&T=0

As an alternative you can also use a 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 time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Time_in_RFC[t] = + 8265.69054333235 + 66.6080746061941Shared_compendiums[t] + 2023.20664315082Reviewed_compendiums[t] + 261.896358450936Long_feedback[t] + 708.747364982016Blogs[t] + 0.139075709621003Characters[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Time_in_RFC[t] =  +  8265.69054333235 +  66.6080746061941Shared_compendiums[t] +  2023.20664315082Reviewed_compendiums[t] +  261.896358450936Long_feedback[t] +  708.747364982016Blogs[t] +  0.139075709621003Characters[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144867&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Time_in_RFC[t] =  +  8265.69054333235 +  66.6080746061941Shared_compendiums[t] +  2023.20664315082Reviewed_compendiums[t] +  261.896358450936Long_feedback[t] +  708.747364982016Blogs[t] +  0.139075709621003Characters[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144867&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144867&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Time_in_RFC[t] = + 8265.69054333235 + 66.6080746061941Shared_compendiums[t] + 2023.20664315082Reviewed_compendiums[t] + 261.896358450936Long_feedback[t] + 708.747364982016Blogs[t] + 0.139075709621003Characters[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8265.690543332358519.648670.97020.3334340.166717
Shared_compendiums66.60807460619411221.1335160.05450.9565690.478284
Reviewed_compendiums2023.20664315082858.5866282.35640.0196780.009839
Long_feedback261.896358450936235.4643561.11230.2677180.133859
Blogs708.747364982016107.2493336.608400
Characters0.1390757096210030.1365111.01880.3098630.154931

\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) & 8265.69054333235 & 8519.64867 & 0.9702 & 0.333434 & 0.166717 \tabularnewline
Shared_compendiums & 66.6080746061941 & 1221.133516 & 0.0545 & 0.956569 & 0.478284 \tabularnewline
Reviewed_compendiums & 2023.20664315082 & 858.586628 & 2.3564 & 0.019678 & 0.009839 \tabularnewline
Long_feedback & 261.896358450936 & 235.464356 & 1.1123 & 0.267718 & 0.133859 \tabularnewline
Blogs & 708.747364982016 & 107.249333 & 6.6084 & 0 & 0 \tabularnewline
Characters & 0.139075709621003 & 0.136511 & 1.0188 & 0.309863 & 0.154931 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144867&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]8265.69054333235[/C][C]8519.64867[/C][C]0.9702[/C][C]0.333434[/C][C]0.166717[/C][/ROW]
[ROW][C]Shared_compendiums[/C][C]66.6080746061941[/C][C]1221.133516[/C][C]0.0545[/C][C]0.956569[/C][C]0.478284[/C][/ROW]
[ROW][C]Reviewed_compendiums[/C][C]2023.20664315082[/C][C]858.586628[/C][C]2.3564[/C][C]0.019678[/C][C]0.009839[/C][/ROW]
[ROW][C]Long_feedback[/C][C]261.896358450936[/C][C]235.464356[/C][C]1.1123[/C][C]0.267718[/C][C]0.133859[/C][/ROW]
[ROW][C]Blogs[/C][C]708.747364982016[/C][C]107.249333[/C][C]6.6084[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Characters[/C][C]0.139075709621003[/C][C]0.136511[/C][C]1.0188[/C][C]0.309863[/C][C]0.154931[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144867&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144867&T=2

As an alternative you can also use a 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)8265.690543332358519.648670.97020.3334340.166717
Shared_compendiums66.60807460619411221.1335160.05450.9565690.478284
Reviewed_compendiums2023.20664315082858.5866282.35640.0196780.009839
Long_feedback261.896358450936235.4643561.11230.2677180.133859
Blogs708.747364982016107.2493336.608400
Characters0.1390757096210030.1365111.01880.3098630.154931







Multiple Linear Regression - Regression Statistics
Multiple R0.809551198801161
R-squared0.655373143480397
Adjusted R-squared0.644467230299397
F-TEST (value)60.0933761899155
F-TEST (DF numerator)5
F-TEST (DF denominator)158
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation38131.154732844
Sum Squared Residuals229729623879.094

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.809551198801161 \tabularnewline
R-squared & 0.655373143480397 \tabularnewline
Adjusted R-squared & 0.644467230299397 \tabularnewline
F-TEST (value) & 60.0933761899155 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 158 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 38131.154732844 \tabularnewline
Sum Squared Residuals & 229729623879.094 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144867&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.809551198801161[/C][/ROW]
[ROW][C]R-squared[/C][C]0.655373143480397[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.644467230299397[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]60.0933761899155[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]158[/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]38131.154732844[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]229729623879.094[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144867&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144867&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.809551198801161
R-squared0.655373143480397
Adjusted R-squared0.644467230299397
F-TEST (value)60.0933761899155
F-TEST (DF numerator)5
F-TEST (DF denominator)158
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation38131.154732844
Sum Squared Residuals229729623879.094







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1146455174660.978368163-28205.9783681628
284944138519.97509211-53575.9750921103
3113337124071.103649347-10734.1036493465
4128655156858.332367641-28203.332367641
57439887030.6331641451-12632.6331641451
63552385339.60609898-49816.60609898
7293403165142.583321752128260.416678248
83275057160.766540204-24410.766540204
9106539120265.683262231-13726.683262231
10130539114606.09356176315932.9064382373
11154991158361.045810202-3370.04581020215
12126683174923.115407388-48240.1154073881
13100672119269.640352297-18597.6403522973
14179562179391.08357329170.916426710045
15125971126564.619166665-593.619166664564
16234509205927.88711069828581.1128893023
17158980169842.818686389-10862.8186863892
18184217127471.79404691256745.2059530879
19107342150668.269718537-43326.2697185372
20141371169685.272577334-28314.272577334
21154730165257.592703304-10527.5927033037
22264020151369.473215006112650.526784994
239093887102.57265285083835.42734714921
24101324169157.840142358-67833.8401423581
25130232160631.440126806-30399.4401268063
26137793135663.153415242129.84658476016
27161678134463.99788686727214.0021131332
28151503153826.270518483-2323.27051848282
29105324105702.591085683-378.591085682627
30175914154987.88919509620926.1108049037
31181853161353.62730105420499.3726989461
32114928155906.721163111-40978.7211631106
33190410172666.85226195517743.1477380447
346149984414.1035622048-22915.1035622048
35223004185816.32279956337187.6772004375
36167131121759.03468424945371.9653157508
37233482148015.80993768485466.1900623164
38121185116262.8473206094922.15267939128
397877657084.262632998321691.7373670017
40188967143989.00573761244977.9942623877
41199512132514.10212801866997.8978719822
42102531125892.619031959-23361.6190319595
43118958115426.407802393531.59219760975
446894892719.30324129-23771.30324129
459312590999.8685842482125.13141575201
46277108128439.302443725148668.697556275
477880097765.0825770511-18965.0825770511
48157250179014.15737824-21764.1573782401
49210554180634.39252662129919.6074733789
50127324163327.536771416-36003.5367714156
51114397129608.2643174-15211.2643174002
522418823980.5236522112207.476347788754
53246209200106.69253837346102.3074616271
546502980402.8764470807-15373.8764470807
559803076743.155312816721286.8446871833
56173587144358.19449953929228.8055004613
57172684185073.705780817-12389.7057808167
58191381232049.409715687-40668.4097156873
59191276195706.810792447-4430.8107924465
60134043113446.97376347220596.0262365284
61233406183650.26674975749755.7332502431
62195304176074.29341065419229.7065893462
63127619116807.47454513110811.5254548688
64162810139518.8522987523291.1477012501
65129100134466.322956195-5366.32295619481
66108715108718.80539097-3.80539097043272
67106469139098.692444301-32629.692444301
68142069154571.946557932-12502.9465579321
69143937175622.136258281-31685.1362582812
7084256119566.308616363-35310.3086163631
71118807138168.64566705-19361.6456670496
726947186493.2409611531-17022.2409611531
73122433137914.290037589-15481.2900375891
74131122134110.376826032-2988.37682603192
7594763150508.847568185-55745.8475681853
76188780160828.88311205127951.1168879491
77191467153295.56221984338171.4377801571
78105615135688.951661823-30073.9516618234
7989318136933.531951629-47615.5319516294
80107335118947.614196654-11612.6141966539
819859995380.97459384413218.02540615595
82260646158803.097409693101842.902590307
83131876105704.45149297226171.5485070283
84119291162895.849328418-43604.8493284182
858095380504.6373658315448.362634168486
869976888272.721327424111495.2786725759
8784572144212.420440053-59640.4204400532
88202373120555.06494263781817.9350573629
89166790123060.38411576443729.6158842364
9099946173996.868702342-74050.8687023415
91116900102564.70579982314335.2942001773
92142146189090.191319768-46944.1913197683
9399246108861.056131566-9615.05613156638
94156833134862.39717791521970.6028220846
95175078142680.02601856632397.973981434
96130533136469.788519201-5936.78851920068
97142339184493.70614279-42154.70614279
98176789194839.889492022-18050.8894920224
99181379187299.3341928-5920.33419280022
100228548221229.2995924497318.70040755139
101142141142096.97247202144.0275279786062
102167845196194.885144596-28349.8851445956
10310301280945.564093967922066.4359060321
10443287104547.59918252-61260.5991825203
10512536697634.457948512827731.5420514872
106118372171933.10646615-53561.10646615
107135171136768.746573215-1597.74657321536
108175568160425.22688718415142.773112816
10974112122035.039421098-47923.0394210981
11088817110637.332912824-21820.332912824
111164767147103.20434128117663.7956587185
112141933159844.805128675-17911.8051286751
1132293818247.55863012274690.44136987733
114115199131676.175962269-16477.1759622694
1156185761988.6358949243-131.635894924335
11691185130593.410994547-39408.410994547
117213765181919.94138617131845.0586138288
1182105411219.58973498649834.41026501363
119167105113642.01091765353462.9890823467
1203141456412.750865906-24998.750865906
121178863144970.89479844133892.1052015585
122126681144775.488213487-18094.4882134866
1236432088673.3873730349-24353.3873730349
1246774698364.8429546403-30618.8429546403
1253821442511.2362562259-4297.23625622587
12690961116870.325748724-25909.325748724
127181510191547.175447028-10037.1754470284
128116775176197.205570039-59422.205570039
129223914172374.47333010451539.5266698959
130185139185931.426949376-792.426949375889
131242879244123.156815566-1244.15681556604
132139144131675.1555302977468.84446970284
1337581289872.266504278-14060.266504278
134178218145954.68244224732263.3175577527
135246834192926.52850615953907.4714938413
1365099981117.1421637545-30118.1421637545
137223842169639.50946562654202.4905343741
13893577122155.95619032-28578.95619032
139155383152956.235125682426.76487431987
140111664143127.247860951-31463.2478609511
1417542667481.72122851477944.27877148531
142243551142428.125264157101122.874735843
143136548189813.065653981-53265.0656539814
14417326087190.881982088386069.1180179117
145185039156782.79331544228256.2066845578
14667507148383.218256649-80876.218256649
147139350153855.983034269-14505.9830342687
148172964212643.027927062-39679.0279270618
14908865.16321478809-8865.16321478809
1501468812647.08036728972040.91963271028
151988265.69054333234-8167.69054333234
1524558265.69054333234-7810.69054333234
15308332.29861793854-8332.29861793854
15408265.69054333234-8265.69054333234
155128066124053.4724640764012.52753592433
156176460169238.3151942317221.68480576924
15708265.69054333234-8265.69054333234
1582038265.69054333234-8062.69054333234
159719912746.8151998414-5547.81519984137
1604666031859.44097346314800.559026537
1611754714008.7359512053538.26404879499
1627356778907.5243576293-5340.52435762934
1639698265.69054333234-7296.69054333234
16410106089239.844472971711820.1555270283

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 146455 & 174660.978368163 & -28205.9783681628 \tabularnewline
2 & 84944 & 138519.97509211 & -53575.9750921103 \tabularnewline
3 & 113337 & 124071.103649347 & -10734.1036493465 \tabularnewline
4 & 128655 & 156858.332367641 & -28203.332367641 \tabularnewline
5 & 74398 & 87030.6331641451 & -12632.6331641451 \tabularnewline
6 & 35523 & 85339.60609898 & -49816.60609898 \tabularnewline
7 & 293403 & 165142.583321752 & 128260.416678248 \tabularnewline
8 & 32750 & 57160.766540204 & -24410.766540204 \tabularnewline
9 & 106539 & 120265.683262231 & -13726.683262231 \tabularnewline
10 & 130539 & 114606.093561763 & 15932.9064382373 \tabularnewline
11 & 154991 & 158361.045810202 & -3370.04581020215 \tabularnewline
12 & 126683 & 174923.115407388 & -48240.1154073881 \tabularnewline
13 & 100672 & 119269.640352297 & -18597.6403522973 \tabularnewline
14 & 179562 & 179391.08357329 & 170.916426710045 \tabularnewline
15 & 125971 & 126564.619166665 & -593.619166664564 \tabularnewline
16 & 234509 & 205927.887110698 & 28581.1128893023 \tabularnewline
17 & 158980 & 169842.818686389 & -10862.8186863892 \tabularnewline
18 & 184217 & 127471.794046912 & 56745.2059530879 \tabularnewline
19 & 107342 & 150668.269718537 & -43326.2697185372 \tabularnewline
20 & 141371 & 169685.272577334 & -28314.272577334 \tabularnewline
21 & 154730 & 165257.592703304 & -10527.5927033037 \tabularnewline
22 & 264020 & 151369.473215006 & 112650.526784994 \tabularnewline
23 & 90938 & 87102.5726528508 & 3835.42734714921 \tabularnewline
24 & 101324 & 169157.840142358 & -67833.8401423581 \tabularnewline
25 & 130232 & 160631.440126806 & -30399.4401268063 \tabularnewline
26 & 137793 & 135663.15341524 & 2129.84658476016 \tabularnewline
27 & 161678 & 134463.997886867 & 27214.0021131332 \tabularnewline
28 & 151503 & 153826.270518483 & -2323.27051848282 \tabularnewline
29 & 105324 & 105702.591085683 & -378.591085682627 \tabularnewline
30 & 175914 & 154987.889195096 & 20926.1108049037 \tabularnewline
31 & 181853 & 161353.627301054 & 20499.3726989461 \tabularnewline
32 & 114928 & 155906.721163111 & -40978.7211631106 \tabularnewline
33 & 190410 & 172666.852261955 & 17743.1477380447 \tabularnewline
34 & 61499 & 84414.1035622048 & -22915.1035622048 \tabularnewline
35 & 223004 & 185816.322799563 & 37187.6772004375 \tabularnewline
36 & 167131 & 121759.034684249 & 45371.9653157508 \tabularnewline
37 & 233482 & 148015.809937684 & 85466.1900623164 \tabularnewline
38 & 121185 & 116262.847320609 & 4922.15267939128 \tabularnewline
39 & 78776 & 57084.2626329983 & 21691.7373670017 \tabularnewline
40 & 188967 & 143989.005737612 & 44977.9942623877 \tabularnewline
41 & 199512 & 132514.102128018 & 66997.8978719822 \tabularnewline
42 & 102531 & 125892.619031959 & -23361.6190319595 \tabularnewline
43 & 118958 & 115426.40780239 & 3531.59219760975 \tabularnewline
44 & 68948 & 92719.30324129 & -23771.30324129 \tabularnewline
45 & 93125 & 90999.868584248 & 2125.13141575201 \tabularnewline
46 & 277108 & 128439.302443725 & 148668.697556275 \tabularnewline
47 & 78800 & 97765.0825770511 & -18965.0825770511 \tabularnewline
48 & 157250 & 179014.15737824 & -21764.1573782401 \tabularnewline
49 & 210554 & 180634.392526621 & 29919.6074733789 \tabularnewline
50 & 127324 & 163327.536771416 & -36003.5367714156 \tabularnewline
51 & 114397 & 129608.2643174 & -15211.2643174002 \tabularnewline
52 & 24188 & 23980.5236522112 & 207.476347788754 \tabularnewline
53 & 246209 & 200106.692538373 & 46102.3074616271 \tabularnewline
54 & 65029 & 80402.8764470807 & -15373.8764470807 \tabularnewline
55 & 98030 & 76743.1553128167 & 21286.8446871833 \tabularnewline
56 & 173587 & 144358.194499539 & 29228.8055004613 \tabularnewline
57 & 172684 & 185073.705780817 & -12389.7057808167 \tabularnewline
58 & 191381 & 232049.409715687 & -40668.4097156873 \tabularnewline
59 & 191276 & 195706.810792447 & -4430.8107924465 \tabularnewline
60 & 134043 & 113446.973763472 & 20596.0262365284 \tabularnewline
61 & 233406 & 183650.266749757 & 49755.7332502431 \tabularnewline
62 & 195304 & 176074.293410654 & 19229.7065893462 \tabularnewline
63 & 127619 & 116807.474545131 & 10811.5254548688 \tabularnewline
64 & 162810 & 139518.85229875 & 23291.1477012501 \tabularnewline
65 & 129100 & 134466.322956195 & -5366.32295619481 \tabularnewline
66 & 108715 & 108718.80539097 & -3.80539097043272 \tabularnewline
67 & 106469 & 139098.692444301 & -32629.692444301 \tabularnewline
68 & 142069 & 154571.946557932 & -12502.9465579321 \tabularnewline
69 & 143937 & 175622.136258281 & -31685.1362582812 \tabularnewline
70 & 84256 & 119566.308616363 & -35310.3086163631 \tabularnewline
71 & 118807 & 138168.64566705 & -19361.6456670496 \tabularnewline
72 & 69471 & 86493.2409611531 & -17022.2409611531 \tabularnewline
73 & 122433 & 137914.290037589 & -15481.2900375891 \tabularnewline
74 & 131122 & 134110.376826032 & -2988.37682603192 \tabularnewline
75 & 94763 & 150508.847568185 & -55745.8475681853 \tabularnewline
76 & 188780 & 160828.883112051 & 27951.1168879491 \tabularnewline
77 & 191467 & 153295.562219843 & 38171.4377801571 \tabularnewline
78 & 105615 & 135688.951661823 & -30073.9516618234 \tabularnewline
79 & 89318 & 136933.531951629 & -47615.5319516294 \tabularnewline
80 & 107335 & 118947.614196654 & -11612.6141966539 \tabularnewline
81 & 98599 & 95380.9745938441 & 3218.02540615595 \tabularnewline
82 & 260646 & 158803.097409693 & 101842.902590307 \tabularnewline
83 & 131876 & 105704.451492972 & 26171.5485070283 \tabularnewline
84 & 119291 & 162895.849328418 & -43604.8493284182 \tabularnewline
85 & 80953 & 80504.6373658315 & 448.362634168486 \tabularnewline
86 & 99768 & 88272.7213274241 & 11495.2786725759 \tabularnewline
87 & 84572 & 144212.420440053 & -59640.4204400532 \tabularnewline
88 & 202373 & 120555.064942637 & 81817.9350573629 \tabularnewline
89 & 166790 & 123060.384115764 & 43729.6158842364 \tabularnewline
90 & 99946 & 173996.868702342 & -74050.8687023415 \tabularnewline
91 & 116900 & 102564.705799823 & 14335.2942001773 \tabularnewline
92 & 142146 & 189090.191319768 & -46944.1913197683 \tabularnewline
93 & 99246 & 108861.056131566 & -9615.05613156638 \tabularnewline
94 & 156833 & 134862.397177915 & 21970.6028220846 \tabularnewline
95 & 175078 & 142680.026018566 & 32397.973981434 \tabularnewline
96 & 130533 & 136469.788519201 & -5936.78851920068 \tabularnewline
97 & 142339 & 184493.70614279 & -42154.70614279 \tabularnewline
98 & 176789 & 194839.889492022 & -18050.8894920224 \tabularnewline
99 & 181379 & 187299.3341928 & -5920.33419280022 \tabularnewline
100 & 228548 & 221229.299592449 & 7318.70040755139 \tabularnewline
101 & 142141 & 142096.972472021 & 44.0275279786062 \tabularnewline
102 & 167845 & 196194.885144596 & -28349.8851445956 \tabularnewline
103 & 103012 & 80945.5640939679 & 22066.4359060321 \tabularnewline
104 & 43287 & 104547.59918252 & -61260.5991825203 \tabularnewline
105 & 125366 & 97634.4579485128 & 27731.5420514872 \tabularnewline
106 & 118372 & 171933.10646615 & -53561.10646615 \tabularnewline
107 & 135171 & 136768.746573215 & -1597.74657321536 \tabularnewline
108 & 175568 & 160425.226887184 & 15142.773112816 \tabularnewline
109 & 74112 & 122035.039421098 & -47923.0394210981 \tabularnewline
110 & 88817 & 110637.332912824 & -21820.332912824 \tabularnewline
111 & 164767 & 147103.204341281 & 17663.7956587185 \tabularnewline
112 & 141933 & 159844.805128675 & -17911.8051286751 \tabularnewline
113 & 22938 & 18247.5586301227 & 4690.44136987733 \tabularnewline
114 & 115199 & 131676.175962269 & -16477.1759622694 \tabularnewline
115 & 61857 & 61988.6358949243 & -131.635894924335 \tabularnewline
116 & 91185 & 130593.410994547 & -39408.410994547 \tabularnewline
117 & 213765 & 181919.941386171 & 31845.0586138288 \tabularnewline
118 & 21054 & 11219.5897349864 & 9834.41026501363 \tabularnewline
119 & 167105 & 113642.010917653 & 53462.9890823467 \tabularnewline
120 & 31414 & 56412.750865906 & -24998.750865906 \tabularnewline
121 & 178863 & 144970.894798441 & 33892.1052015585 \tabularnewline
122 & 126681 & 144775.488213487 & -18094.4882134866 \tabularnewline
123 & 64320 & 88673.3873730349 & -24353.3873730349 \tabularnewline
124 & 67746 & 98364.8429546403 & -30618.8429546403 \tabularnewline
125 & 38214 & 42511.2362562259 & -4297.23625622587 \tabularnewline
126 & 90961 & 116870.325748724 & -25909.325748724 \tabularnewline
127 & 181510 & 191547.175447028 & -10037.1754470284 \tabularnewline
128 & 116775 & 176197.205570039 & -59422.205570039 \tabularnewline
129 & 223914 & 172374.473330104 & 51539.5266698959 \tabularnewline
130 & 185139 & 185931.426949376 & -792.426949375889 \tabularnewline
131 & 242879 & 244123.156815566 & -1244.15681556604 \tabularnewline
132 & 139144 & 131675.155530297 & 7468.84446970284 \tabularnewline
133 & 75812 & 89872.266504278 & -14060.266504278 \tabularnewline
134 & 178218 & 145954.682442247 & 32263.3175577527 \tabularnewline
135 & 246834 & 192926.528506159 & 53907.4714938413 \tabularnewline
136 & 50999 & 81117.1421637545 & -30118.1421637545 \tabularnewline
137 & 223842 & 169639.509465626 & 54202.4905343741 \tabularnewline
138 & 93577 & 122155.95619032 & -28578.95619032 \tabularnewline
139 & 155383 & 152956.23512568 & 2426.76487431987 \tabularnewline
140 & 111664 & 143127.247860951 & -31463.2478609511 \tabularnewline
141 & 75426 & 67481.7212285147 & 7944.27877148531 \tabularnewline
142 & 243551 & 142428.125264157 & 101122.874735843 \tabularnewline
143 & 136548 & 189813.065653981 & -53265.0656539814 \tabularnewline
144 & 173260 & 87190.8819820883 & 86069.1180179117 \tabularnewline
145 & 185039 & 156782.793315442 & 28256.2066845578 \tabularnewline
146 & 67507 & 148383.218256649 & -80876.218256649 \tabularnewline
147 & 139350 & 153855.983034269 & -14505.9830342687 \tabularnewline
148 & 172964 & 212643.027927062 & -39679.0279270618 \tabularnewline
149 & 0 & 8865.16321478809 & -8865.16321478809 \tabularnewline
150 & 14688 & 12647.0803672897 & 2040.91963271028 \tabularnewline
151 & 98 & 8265.69054333234 & -8167.69054333234 \tabularnewline
152 & 455 & 8265.69054333234 & -7810.69054333234 \tabularnewline
153 & 0 & 8332.29861793854 & -8332.29861793854 \tabularnewline
154 & 0 & 8265.69054333234 & -8265.69054333234 \tabularnewline
155 & 128066 & 124053.472464076 & 4012.52753592433 \tabularnewline
156 & 176460 & 169238.315194231 & 7221.68480576924 \tabularnewline
157 & 0 & 8265.69054333234 & -8265.69054333234 \tabularnewline
158 & 203 & 8265.69054333234 & -8062.69054333234 \tabularnewline
159 & 7199 & 12746.8151998414 & -5547.81519984137 \tabularnewline
160 & 46660 & 31859.440973463 & 14800.559026537 \tabularnewline
161 & 17547 & 14008.735951205 & 3538.26404879499 \tabularnewline
162 & 73567 & 78907.5243576293 & -5340.52435762934 \tabularnewline
163 & 969 & 8265.69054333234 & -7296.69054333234 \tabularnewline
164 & 101060 & 89239.8444729717 & 11820.1555270283 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144867&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]146455[/C][C]174660.978368163[/C][C]-28205.9783681628[/C][/ROW]
[ROW][C]2[/C][C]84944[/C][C]138519.97509211[/C][C]-53575.9750921103[/C][/ROW]
[ROW][C]3[/C][C]113337[/C][C]124071.103649347[/C][C]-10734.1036493465[/C][/ROW]
[ROW][C]4[/C][C]128655[/C][C]156858.332367641[/C][C]-28203.332367641[/C][/ROW]
[ROW][C]5[/C][C]74398[/C][C]87030.6331641451[/C][C]-12632.6331641451[/C][/ROW]
[ROW][C]6[/C][C]35523[/C][C]85339.60609898[/C][C]-49816.60609898[/C][/ROW]
[ROW][C]7[/C][C]293403[/C][C]165142.583321752[/C][C]128260.416678248[/C][/ROW]
[ROW][C]8[/C][C]32750[/C][C]57160.766540204[/C][C]-24410.766540204[/C][/ROW]
[ROW][C]9[/C][C]106539[/C][C]120265.683262231[/C][C]-13726.683262231[/C][/ROW]
[ROW][C]10[/C][C]130539[/C][C]114606.093561763[/C][C]15932.9064382373[/C][/ROW]
[ROW][C]11[/C][C]154991[/C][C]158361.045810202[/C][C]-3370.04581020215[/C][/ROW]
[ROW][C]12[/C][C]126683[/C][C]174923.115407388[/C][C]-48240.1154073881[/C][/ROW]
[ROW][C]13[/C][C]100672[/C][C]119269.640352297[/C][C]-18597.6403522973[/C][/ROW]
[ROW][C]14[/C][C]179562[/C][C]179391.08357329[/C][C]170.916426710045[/C][/ROW]
[ROW][C]15[/C][C]125971[/C][C]126564.619166665[/C][C]-593.619166664564[/C][/ROW]
[ROW][C]16[/C][C]234509[/C][C]205927.887110698[/C][C]28581.1128893023[/C][/ROW]
[ROW][C]17[/C][C]158980[/C][C]169842.818686389[/C][C]-10862.8186863892[/C][/ROW]
[ROW][C]18[/C][C]184217[/C][C]127471.794046912[/C][C]56745.2059530879[/C][/ROW]
[ROW][C]19[/C][C]107342[/C][C]150668.269718537[/C][C]-43326.2697185372[/C][/ROW]
[ROW][C]20[/C][C]141371[/C][C]169685.272577334[/C][C]-28314.272577334[/C][/ROW]
[ROW][C]21[/C][C]154730[/C][C]165257.592703304[/C][C]-10527.5927033037[/C][/ROW]
[ROW][C]22[/C][C]264020[/C][C]151369.473215006[/C][C]112650.526784994[/C][/ROW]
[ROW][C]23[/C][C]90938[/C][C]87102.5726528508[/C][C]3835.42734714921[/C][/ROW]
[ROW][C]24[/C][C]101324[/C][C]169157.840142358[/C][C]-67833.8401423581[/C][/ROW]
[ROW][C]25[/C][C]130232[/C][C]160631.440126806[/C][C]-30399.4401268063[/C][/ROW]
[ROW][C]26[/C][C]137793[/C][C]135663.15341524[/C][C]2129.84658476016[/C][/ROW]
[ROW][C]27[/C][C]161678[/C][C]134463.997886867[/C][C]27214.0021131332[/C][/ROW]
[ROW][C]28[/C][C]151503[/C][C]153826.270518483[/C][C]-2323.27051848282[/C][/ROW]
[ROW][C]29[/C][C]105324[/C][C]105702.591085683[/C][C]-378.591085682627[/C][/ROW]
[ROW][C]30[/C][C]175914[/C][C]154987.889195096[/C][C]20926.1108049037[/C][/ROW]
[ROW][C]31[/C][C]181853[/C][C]161353.627301054[/C][C]20499.3726989461[/C][/ROW]
[ROW][C]32[/C][C]114928[/C][C]155906.721163111[/C][C]-40978.7211631106[/C][/ROW]
[ROW][C]33[/C][C]190410[/C][C]172666.852261955[/C][C]17743.1477380447[/C][/ROW]
[ROW][C]34[/C][C]61499[/C][C]84414.1035622048[/C][C]-22915.1035622048[/C][/ROW]
[ROW][C]35[/C][C]223004[/C][C]185816.322799563[/C][C]37187.6772004375[/C][/ROW]
[ROW][C]36[/C][C]167131[/C][C]121759.034684249[/C][C]45371.9653157508[/C][/ROW]
[ROW][C]37[/C][C]233482[/C][C]148015.809937684[/C][C]85466.1900623164[/C][/ROW]
[ROW][C]38[/C][C]121185[/C][C]116262.847320609[/C][C]4922.15267939128[/C][/ROW]
[ROW][C]39[/C][C]78776[/C][C]57084.2626329983[/C][C]21691.7373670017[/C][/ROW]
[ROW][C]40[/C][C]188967[/C][C]143989.005737612[/C][C]44977.9942623877[/C][/ROW]
[ROW][C]41[/C][C]199512[/C][C]132514.102128018[/C][C]66997.8978719822[/C][/ROW]
[ROW][C]42[/C][C]102531[/C][C]125892.619031959[/C][C]-23361.6190319595[/C][/ROW]
[ROW][C]43[/C][C]118958[/C][C]115426.40780239[/C][C]3531.59219760975[/C][/ROW]
[ROW][C]44[/C][C]68948[/C][C]92719.30324129[/C][C]-23771.30324129[/C][/ROW]
[ROW][C]45[/C][C]93125[/C][C]90999.868584248[/C][C]2125.13141575201[/C][/ROW]
[ROW][C]46[/C][C]277108[/C][C]128439.302443725[/C][C]148668.697556275[/C][/ROW]
[ROW][C]47[/C][C]78800[/C][C]97765.0825770511[/C][C]-18965.0825770511[/C][/ROW]
[ROW][C]48[/C][C]157250[/C][C]179014.15737824[/C][C]-21764.1573782401[/C][/ROW]
[ROW][C]49[/C][C]210554[/C][C]180634.392526621[/C][C]29919.6074733789[/C][/ROW]
[ROW][C]50[/C][C]127324[/C][C]163327.536771416[/C][C]-36003.5367714156[/C][/ROW]
[ROW][C]51[/C][C]114397[/C][C]129608.2643174[/C][C]-15211.2643174002[/C][/ROW]
[ROW][C]52[/C][C]24188[/C][C]23980.5236522112[/C][C]207.476347788754[/C][/ROW]
[ROW][C]53[/C][C]246209[/C][C]200106.692538373[/C][C]46102.3074616271[/C][/ROW]
[ROW][C]54[/C][C]65029[/C][C]80402.8764470807[/C][C]-15373.8764470807[/C][/ROW]
[ROW][C]55[/C][C]98030[/C][C]76743.1553128167[/C][C]21286.8446871833[/C][/ROW]
[ROW][C]56[/C][C]173587[/C][C]144358.194499539[/C][C]29228.8055004613[/C][/ROW]
[ROW][C]57[/C][C]172684[/C][C]185073.705780817[/C][C]-12389.7057808167[/C][/ROW]
[ROW][C]58[/C][C]191381[/C][C]232049.409715687[/C][C]-40668.4097156873[/C][/ROW]
[ROW][C]59[/C][C]191276[/C][C]195706.810792447[/C][C]-4430.8107924465[/C][/ROW]
[ROW][C]60[/C][C]134043[/C][C]113446.973763472[/C][C]20596.0262365284[/C][/ROW]
[ROW][C]61[/C][C]233406[/C][C]183650.266749757[/C][C]49755.7332502431[/C][/ROW]
[ROW][C]62[/C][C]195304[/C][C]176074.293410654[/C][C]19229.7065893462[/C][/ROW]
[ROW][C]63[/C][C]127619[/C][C]116807.474545131[/C][C]10811.5254548688[/C][/ROW]
[ROW][C]64[/C][C]162810[/C][C]139518.85229875[/C][C]23291.1477012501[/C][/ROW]
[ROW][C]65[/C][C]129100[/C][C]134466.322956195[/C][C]-5366.32295619481[/C][/ROW]
[ROW][C]66[/C][C]108715[/C][C]108718.80539097[/C][C]-3.80539097043272[/C][/ROW]
[ROW][C]67[/C][C]106469[/C][C]139098.692444301[/C][C]-32629.692444301[/C][/ROW]
[ROW][C]68[/C][C]142069[/C][C]154571.946557932[/C][C]-12502.9465579321[/C][/ROW]
[ROW][C]69[/C][C]143937[/C][C]175622.136258281[/C][C]-31685.1362582812[/C][/ROW]
[ROW][C]70[/C][C]84256[/C][C]119566.308616363[/C][C]-35310.3086163631[/C][/ROW]
[ROW][C]71[/C][C]118807[/C][C]138168.64566705[/C][C]-19361.6456670496[/C][/ROW]
[ROW][C]72[/C][C]69471[/C][C]86493.2409611531[/C][C]-17022.2409611531[/C][/ROW]
[ROW][C]73[/C][C]122433[/C][C]137914.290037589[/C][C]-15481.2900375891[/C][/ROW]
[ROW][C]74[/C][C]131122[/C][C]134110.376826032[/C][C]-2988.37682603192[/C][/ROW]
[ROW][C]75[/C][C]94763[/C][C]150508.847568185[/C][C]-55745.8475681853[/C][/ROW]
[ROW][C]76[/C][C]188780[/C][C]160828.883112051[/C][C]27951.1168879491[/C][/ROW]
[ROW][C]77[/C][C]191467[/C][C]153295.562219843[/C][C]38171.4377801571[/C][/ROW]
[ROW][C]78[/C][C]105615[/C][C]135688.951661823[/C][C]-30073.9516618234[/C][/ROW]
[ROW][C]79[/C][C]89318[/C][C]136933.531951629[/C][C]-47615.5319516294[/C][/ROW]
[ROW][C]80[/C][C]107335[/C][C]118947.614196654[/C][C]-11612.6141966539[/C][/ROW]
[ROW][C]81[/C][C]98599[/C][C]95380.9745938441[/C][C]3218.02540615595[/C][/ROW]
[ROW][C]82[/C][C]260646[/C][C]158803.097409693[/C][C]101842.902590307[/C][/ROW]
[ROW][C]83[/C][C]131876[/C][C]105704.451492972[/C][C]26171.5485070283[/C][/ROW]
[ROW][C]84[/C][C]119291[/C][C]162895.849328418[/C][C]-43604.8493284182[/C][/ROW]
[ROW][C]85[/C][C]80953[/C][C]80504.6373658315[/C][C]448.362634168486[/C][/ROW]
[ROW][C]86[/C][C]99768[/C][C]88272.7213274241[/C][C]11495.2786725759[/C][/ROW]
[ROW][C]87[/C][C]84572[/C][C]144212.420440053[/C][C]-59640.4204400532[/C][/ROW]
[ROW][C]88[/C][C]202373[/C][C]120555.064942637[/C][C]81817.9350573629[/C][/ROW]
[ROW][C]89[/C][C]166790[/C][C]123060.384115764[/C][C]43729.6158842364[/C][/ROW]
[ROW][C]90[/C][C]99946[/C][C]173996.868702342[/C][C]-74050.8687023415[/C][/ROW]
[ROW][C]91[/C][C]116900[/C][C]102564.705799823[/C][C]14335.2942001773[/C][/ROW]
[ROW][C]92[/C][C]142146[/C][C]189090.191319768[/C][C]-46944.1913197683[/C][/ROW]
[ROW][C]93[/C][C]99246[/C][C]108861.056131566[/C][C]-9615.05613156638[/C][/ROW]
[ROW][C]94[/C][C]156833[/C][C]134862.397177915[/C][C]21970.6028220846[/C][/ROW]
[ROW][C]95[/C][C]175078[/C][C]142680.026018566[/C][C]32397.973981434[/C][/ROW]
[ROW][C]96[/C][C]130533[/C][C]136469.788519201[/C][C]-5936.78851920068[/C][/ROW]
[ROW][C]97[/C][C]142339[/C][C]184493.70614279[/C][C]-42154.70614279[/C][/ROW]
[ROW][C]98[/C][C]176789[/C][C]194839.889492022[/C][C]-18050.8894920224[/C][/ROW]
[ROW][C]99[/C][C]181379[/C][C]187299.3341928[/C][C]-5920.33419280022[/C][/ROW]
[ROW][C]100[/C][C]228548[/C][C]221229.299592449[/C][C]7318.70040755139[/C][/ROW]
[ROW][C]101[/C][C]142141[/C][C]142096.972472021[/C][C]44.0275279786062[/C][/ROW]
[ROW][C]102[/C][C]167845[/C][C]196194.885144596[/C][C]-28349.8851445956[/C][/ROW]
[ROW][C]103[/C][C]103012[/C][C]80945.5640939679[/C][C]22066.4359060321[/C][/ROW]
[ROW][C]104[/C][C]43287[/C][C]104547.59918252[/C][C]-61260.5991825203[/C][/ROW]
[ROW][C]105[/C][C]125366[/C][C]97634.4579485128[/C][C]27731.5420514872[/C][/ROW]
[ROW][C]106[/C][C]118372[/C][C]171933.10646615[/C][C]-53561.10646615[/C][/ROW]
[ROW][C]107[/C][C]135171[/C][C]136768.746573215[/C][C]-1597.74657321536[/C][/ROW]
[ROW][C]108[/C][C]175568[/C][C]160425.226887184[/C][C]15142.773112816[/C][/ROW]
[ROW][C]109[/C][C]74112[/C][C]122035.039421098[/C][C]-47923.0394210981[/C][/ROW]
[ROW][C]110[/C][C]88817[/C][C]110637.332912824[/C][C]-21820.332912824[/C][/ROW]
[ROW][C]111[/C][C]164767[/C][C]147103.204341281[/C][C]17663.7956587185[/C][/ROW]
[ROW][C]112[/C][C]141933[/C][C]159844.805128675[/C][C]-17911.8051286751[/C][/ROW]
[ROW][C]113[/C][C]22938[/C][C]18247.5586301227[/C][C]4690.44136987733[/C][/ROW]
[ROW][C]114[/C][C]115199[/C][C]131676.175962269[/C][C]-16477.1759622694[/C][/ROW]
[ROW][C]115[/C][C]61857[/C][C]61988.6358949243[/C][C]-131.635894924335[/C][/ROW]
[ROW][C]116[/C][C]91185[/C][C]130593.410994547[/C][C]-39408.410994547[/C][/ROW]
[ROW][C]117[/C][C]213765[/C][C]181919.941386171[/C][C]31845.0586138288[/C][/ROW]
[ROW][C]118[/C][C]21054[/C][C]11219.5897349864[/C][C]9834.41026501363[/C][/ROW]
[ROW][C]119[/C][C]167105[/C][C]113642.010917653[/C][C]53462.9890823467[/C][/ROW]
[ROW][C]120[/C][C]31414[/C][C]56412.750865906[/C][C]-24998.750865906[/C][/ROW]
[ROW][C]121[/C][C]178863[/C][C]144970.894798441[/C][C]33892.1052015585[/C][/ROW]
[ROW][C]122[/C][C]126681[/C][C]144775.488213487[/C][C]-18094.4882134866[/C][/ROW]
[ROW][C]123[/C][C]64320[/C][C]88673.3873730349[/C][C]-24353.3873730349[/C][/ROW]
[ROW][C]124[/C][C]67746[/C][C]98364.8429546403[/C][C]-30618.8429546403[/C][/ROW]
[ROW][C]125[/C][C]38214[/C][C]42511.2362562259[/C][C]-4297.23625622587[/C][/ROW]
[ROW][C]126[/C][C]90961[/C][C]116870.325748724[/C][C]-25909.325748724[/C][/ROW]
[ROW][C]127[/C][C]181510[/C][C]191547.175447028[/C][C]-10037.1754470284[/C][/ROW]
[ROW][C]128[/C][C]116775[/C][C]176197.205570039[/C][C]-59422.205570039[/C][/ROW]
[ROW][C]129[/C][C]223914[/C][C]172374.473330104[/C][C]51539.5266698959[/C][/ROW]
[ROW][C]130[/C][C]185139[/C][C]185931.426949376[/C][C]-792.426949375889[/C][/ROW]
[ROW][C]131[/C][C]242879[/C][C]244123.156815566[/C][C]-1244.15681556604[/C][/ROW]
[ROW][C]132[/C][C]139144[/C][C]131675.155530297[/C][C]7468.84446970284[/C][/ROW]
[ROW][C]133[/C][C]75812[/C][C]89872.266504278[/C][C]-14060.266504278[/C][/ROW]
[ROW][C]134[/C][C]178218[/C][C]145954.682442247[/C][C]32263.3175577527[/C][/ROW]
[ROW][C]135[/C][C]246834[/C][C]192926.528506159[/C][C]53907.4714938413[/C][/ROW]
[ROW][C]136[/C][C]50999[/C][C]81117.1421637545[/C][C]-30118.1421637545[/C][/ROW]
[ROW][C]137[/C][C]223842[/C][C]169639.509465626[/C][C]54202.4905343741[/C][/ROW]
[ROW][C]138[/C][C]93577[/C][C]122155.95619032[/C][C]-28578.95619032[/C][/ROW]
[ROW][C]139[/C][C]155383[/C][C]152956.23512568[/C][C]2426.76487431987[/C][/ROW]
[ROW][C]140[/C][C]111664[/C][C]143127.247860951[/C][C]-31463.2478609511[/C][/ROW]
[ROW][C]141[/C][C]75426[/C][C]67481.7212285147[/C][C]7944.27877148531[/C][/ROW]
[ROW][C]142[/C][C]243551[/C][C]142428.125264157[/C][C]101122.874735843[/C][/ROW]
[ROW][C]143[/C][C]136548[/C][C]189813.065653981[/C][C]-53265.0656539814[/C][/ROW]
[ROW][C]144[/C][C]173260[/C][C]87190.8819820883[/C][C]86069.1180179117[/C][/ROW]
[ROW][C]145[/C][C]185039[/C][C]156782.793315442[/C][C]28256.2066845578[/C][/ROW]
[ROW][C]146[/C][C]67507[/C][C]148383.218256649[/C][C]-80876.218256649[/C][/ROW]
[ROW][C]147[/C][C]139350[/C][C]153855.983034269[/C][C]-14505.9830342687[/C][/ROW]
[ROW][C]148[/C][C]172964[/C][C]212643.027927062[/C][C]-39679.0279270618[/C][/ROW]
[ROW][C]149[/C][C]0[/C][C]8865.16321478809[/C][C]-8865.16321478809[/C][/ROW]
[ROW][C]150[/C][C]14688[/C][C]12647.0803672897[/C][C]2040.91963271028[/C][/ROW]
[ROW][C]151[/C][C]98[/C][C]8265.69054333234[/C][C]-8167.69054333234[/C][/ROW]
[ROW][C]152[/C][C]455[/C][C]8265.69054333234[/C][C]-7810.69054333234[/C][/ROW]
[ROW][C]153[/C][C]0[/C][C]8332.29861793854[/C][C]-8332.29861793854[/C][/ROW]
[ROW][C]154[/C][C]0[/C][C]8265.69054333234[/C][C]-8265.69054333234[/C][/ROW]
[ROW][C]155[/C][C]128066[/C][C]124053.472464076[/C][C]4012.52753592433[/C][/ROW]
[ROW][C]156[/C][C]176460[/C][C]169238.315194231[/C][C]7221.68480576924[/C][/ROW]
[ROW][C]157[/C][C]0[/C][C]8265.69054333234[/C][C]-8265.69054333234[/C][/ROW]
[ROW][C]158[/C][C]203[/C][C]8265.69054333234[/C][C]-8062.69054333234[/C][/ROW]
[ROW][C]159[/C][C]7199[/C][C]12746.8151998414[/C][C]-5547.81519984137[/C][/ROW]
[ROW][C]160[/C][C]46660[/C][C]31859.440973463[/C][C]14800.559026537[/C][/ROW]
[ROW][C]161[/C][C]17547[/C][C]14008.735951205[/C][C]3538.26404879499[/C][/ROW]
[ROW][C]162[/C][C]73567[/C][C]78907.5243576293[/C][C]-5340.52435762934[/C][/ROW]
[ROW][C]163[/C][C]969[/C][C]8265.69054333234[/C][C]-7296.69054333234[/C][/ROW]
[ROW][C]164[/C][C]101060[/C][C]89239.8444729717[/C][C]11820.1555270283[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144867&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144867&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1146455174660.978368163-28205.9783681628
284944138519.97509211-53575.9750921103
3113337124071.103649347-10734.1036493465
4128655156858.332367641-28203.332367641
57439887030.6331641451-12632.6331641451
63552385339.60609898-49816.60609898
7293403165142.583321752128260.416678248
83275057160.766540204-24410.766540204
9106539120265.683262231-13726.683262231
10130539114606.09356176315932.9064382373
11154991158361.045810202-3370.04581020215
12126683174923.115407388-48240.1154073881
13100672119269.640352297-18597.6403522973
14179562179391.08357329170.916426710045
15125971126564.619166665-593.619166664564
16234509205927.88711069828581.1128893023
17158980169842.818686389-10862.8186863892
18184217127471.79404691256745.2059530879
19107342150668.269718537-43326.2697185372
20141371169685.272577334-28314.272577334
21154730165257.592703304-10527.5927033037
22264020151369.473215006112650.526784994
239093887102.57265285083835.42734714921
24101324169157.840142358-67833.8401423581
25130232160631.440126806-30399.4401268063
26137793135663.153415242129.84658476016
27161678134463.99788686727214.0021131332
28151503153826.270518483-2323.27051848282
29105324105702.591085683-378.591085682627
30175914154987.88919509620926.1108049037
31181853161353.62730105420499.3726989461
32114928155906.721163111-40978.7211631106
33190410172666.85226195517743.1477380447
346149984414.1035622048-22915.1035622048
35223004185816.32279956337187.6772004375
36167131121759.03468424945371.9653157508
37233482148015.80993768485466.1900623164
38121185116262.8473206094922.15267939128
397877657084.262632998321691.7373670017
40188967143989.00573761244977.9942623877
41199512132514.10212801866997.8978719822
42102531125892.619031959-23361.6190319595
43118958115426.407802393531.59219760975
446894892719.30324129-23771.30324129
459312590999.8685842482125.13141575201
46277108128439.302443725148668.697556275
477880097765.0825770511-18965.0825770511
48157250179014.15737824-21764.1573782401
49210554180634.39252662129919.6074733789
50127324163327.536771416-36003.5367714156
51114397129608.2643174-15211.2643174002
522418823980.5236522112207.476347788754
53246209200106.69253837346102.3074616271
546502980402.8764470807-15373.8764470807
559803076743.155312816721286.8446871833
56173587144358.19449953929228.8055004613
57172684185073.705780817-12389.7057808167
58191381232049.409715687-40668.4097156873
59191276195706.810792447-4430.8107924465
60134043113446.97376347220596.0262365284
61233406183650.26674975749755.7332502431
62195304176074.29341065419229.7065893462
63127619116807.47454513110811.5254548688
64162810139518.8522987523291.1477012501
65129100134466.322956195-5366.32295619481
66108715108718.80539097-3.80539097043272
67106469139098.692444301-32629.692444301
68142069154571.946557932-12502.9465579321
69143937175622.136258281-31685.1362582812
7084256119566.308616363-35310.3086163631
71118807138168.64566705-19361.6456670496
726947186493.2409611531-17022.2409611531
73122433137914.290037589-15481.2900375891
74131122134110.376826032-2988.37682603192
7594763150508.847568185-55745.8475681853
76188780160828.88311205127951.1168879491
77191467153295.56221984338171.4377801571
78105615135688.951661823-30073.9516618234
7989318136933.531951629-47615.5319516294
80107335118947.614196654-11612.6141966539
819859995380.97459384413218.02540615595
82260646158803.097409693101842.902590307
83131876105704.45149297226171.5485070283
84119291162895.849328418-43604.8493284182
858095380504.6373658315448.362634168486
869976888272.721327424111495.2786725759
8784572144212.420440053-59640.4204400532
88202373120555.06494263781817.9350573629
89166790123060.38411576443729.6158842364
9099946173996.868702342-74050.8687023415
91116900102564.70579982314335.2942001773
92142146189090.191319768-46944.1913197683
9399246108861.056131566-9615.05613156638
94156833134862.39717791521970.6028220846
95175078142680.02601856632397.973981434
96130533136469.788519201-5936.78851920068
97142339184493.70614279-42154.70614279
98176789194839.889492022-18050.8894920224
99181379187299.3341928-5920.33419280022
100228548221229.2995924497318.70040755139
101142141142096.97247202144.0275279786062
102167845196194.885144596-28349.8851445956
10310301280945.564093967922066.4359060321
10443287104547.59918252-61260.5991825203
10512536697634.457948512827731.5420514872
106118372171933.10646615-53561.10646615
107135171136768.746573215-1597.74657321536
108175568160425.22688718415142.773112816
10974112122035.039421098-47923.0394210981
11088817110637.332912824-21820.332912824
111164767147103.20434128117663.7956587185
112141933159844.805128675-17911.8051286751
1132293818247.55863012274690.44136987733
114115199131676.175962269-16477.1759622694
1156185761988.6358949243-131.635894924335
11691185130593.410994547-39408.410994547
117213765181919.94138617131845.0586138288
1182105411219.58973498649834.41026501363
119167105113642.01091765353462.9890823467
1203141456412.750865906-24998.750865906
121178863144970.89479844133892.1052015585
122126681144775.488213487-18094.4882134866
1236432088673.3873730349-24353.3873730349
1246774698364.8429546403-30618.8429546403
1253821442511.2362562259-4297.23625622587
12690961116870.325748724-25909.325748724
127181510191547.175447028-10037.1754470284
128116775176197.205570039-59422.205570039
129223914172374.47333010451539.5266698959
130185139185931.426949376-792.426949375889
131242879244123.156815566-1244.15681556604
132139144131675.1555302977468.84446970284
1337581289872.266504278-14060.266504278
134178218145954.68244224732263.3175577527
135246834192926.52850615953907.4714938413
1365099981117.1421637545-30118.1421637545
137223842169639.50946562654202.4905343741
13893577122155.95619032-28578.95619032
139155383152956.235125682426.76487431987
140111664143127.247860951-31463.2478609511
1417542667481.72122851477944.27877148531
142243551142428.125264157101122.874735843
143136548189813.065653981-53265.0656539814
14417326087190.881982088386069.1180179117
145185039156782.79331544228256.2066845578
14667507148383.218256649-80876.218256649
147139350153855.983034269-14505.9830342687
148172964212643.027927062-39679.0279270618
14908865.16321478809-8865.16321478809
1501468812647.08036728972040.91963271028
151988265.69054333234-8167.69054333234
1524558265.69054333234-7810.69054333234
15308332.29861793854-8332.29861793854
15408265.69054333234-8265.69054333234
155128066124053.4724640764012.52753592433
156176460169238.3151942317221.68480576924
15708265.69054333234-8265.69054333234
1582038265.69054333234-8062.69054333234
159719912746.8151998414-5547.81519984137
1604666031859.44097346314800.559026537
1611754714008.7359512053538.26404879499
1627356778907.5243576293-5340.52435762934
1639698265.69054333234-7296.69054333234
16410106089239.844472971711820.1555270283







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9895451185742080.02090976285158320.0104548814257916
100.9797638492505820.04047230149883580.0202361507494179
110.9629377665008690.0741244669982620.037062233499131
120.9374258842179840.1251482315640310.0625741157820157
130.9151328104613070.1697343790773850.0848671895386926
140.8701897132668330.2596205734663330.129810286733167
150.8188541575016210.3622916849967570.181145842498379
160.7584935782567180.4830128434865630.241506421743282
170.7049061930056610.5901876139886780.295093806994339
180.7046153818943790.5907692362112420.295384618105621
190.8289953746633040.3420092506733910.171004625336696
200.7785272855146880.4429454289706240.221472714485312
210.7583866851787320.4832266296425370.241613314821268
220.9684782255967580.06304354880648310.0315217744032416
230.9584934973259560.0830130053480880.041506502674044
240.966553163216550.0668936735668990.0334468367834495
250.9653610643899220.06927787122015610.034638935610078
260.9510035968234620.09799280635307660.0489964031765383
270.9450648265100950.1098703469798090.0549351734899046
280.9256591779616940.1486816440766120.0743408220383061
290.9027950873507460.1944098252985080.0972049126492542
300.8778105050519640.2443789898960730.122189494948036
310.8602367095372450.279526580925510.139763290462755
320.8538698678793240.2922602642413520.146130132120676
330.8254131220114610.3491737559770770.174586877988539
340.7921841252453890.4156317495092220.207815874754611
350.7696081600072560.4607836799854890.230391839992745
360.7762872084910.4474255830180010.223712791509
370.8768824829460540.2462350341078930.123117517053946
380.8472553988302250.3054892023395490.152744601169775
390.8269861435162370.3460277129675260.173013856483763
400.8369498906630320.3261002186739350.163050109336968
410.9295213784586910.1409572430826180.0704786215413091
420.9144835612796130.1710328774407750.0855164387203873
430.8926750965393990.2146498069212020.107324903460601
440.8734682432900520.2530635134198960.126531756709948
450.8445109720301070.3109780559397860.155489027969893
460.9936679325639640.01266413487207170.00633206743603585
470.9916737932944460.01665241341110720.00832620670555362
480.9899345461974390.0201309076051220.010065453802561
490.9872436952475140.02551260950497130.0127563047524856
500.9857808104214780.02843837915704470.0142191895785223
510.9825613599529740.03487728009405280.0174386400470264
520.9765746365124910.0468507269750190.0234253634875095
530.9807932208143550.03841355837129020.0192067791856451
540.9751412034745920.04971759305081510.0248587965254076
550.9708036712913460.05839265741730760.0291963287086538
560.9658606769405370.06827864611892520.0341393230594626
570.9588163521490790.08236729570184250.0411836478509213
580.9591350375306550.08172992493869060.0408649624693453
590.9493164013705280.1013671972589450.0506835986294723
600.9449314771543650.1101370456912690.0550685228456346
610.9471023026447040.1057953947105920.0528976973552959
620.9356724137928140.1286551724143720.0643275862071861
630.922921594791870.1541568104162610.0770784052081303
640.91181633898680.1763673220263990.0881836610131997
650.895853179486510.2082936410269810.10414682051349
660.8732778399903550.253444320019290.126722160009645
670.881401502909850.2371969941803010.11859849709015
680.859255882097160.281488235805680.14074411790284
690.850320386341860.2993592273162790.14967961365814
700.8438036365436810.3123927269126390.156196363456319
710.8256225656726150.3487548686547690.174377434327385
720.8023127525701390.3953744948597220.197687247429861
730.7752160079073330.4495679841853330.224783992092667
740.7425203635561930.5149592728876140.257479636443807
750.7809033806989690.4381932386020610.219096619301031
760.7624219288900180.4751561422199650.237578071109982
770.7602361961630170.4795276076739670.239763803836983
780.8154661806933830.3690676386132340.184533819306617
790.8317920487298670.3364159025402660.168207951270133
800.8051437804565210.3897124390869580.194856219543479
810.7720307395105810.4559385209788380.227969260489419
820.9243657005876430.1512685988247140.075634299412357
830.9167513883477440.1664972233045130.0832486116522563
840.9251220275274230.1497559449451540.0748779724725768
850.9083636053393150.1832727893213690.0916363946606846
860.8898351337756580.2203297324486850.110164866224342
870.9214078708740330.1571842582519340.0785921291259671
880.9704219233140790.05915615337184150.0295780766859208
890.9750972149405140.04980557011897250.0249027850594862
900.989486792699210.02102641460157960.0105132073007898
910.98675516248320.02648967503359950.0132448375167997
920.9898239866515660.02035202669686750.0101760133484338
930.9865822010190120.02683559796197580.0134177989809879
940.9836573922916840.03268521541663240.0163426077083162
950.9819515245070370.03609695098592550.0180484754929627
960.9766140536836060.04677189263278710.0233859463163936
970.978811616384050.04237676723190030.0211883836159501
980.9735611180381610.0528777639236770.0264388819618385
990.9667238665378890.06655226692422180.0332761334621109
1000.9618006547017440.07639869059651110.0381993452982555
1010.9506234744033780.09875305119324430.0493765255966222
1020.9455598627501690.1088802744996620.0544401372498308
1030.9483074203559180.1033851592881640.0516925796440819
1040.9715657374747730.05686852505045430.0284342625252271
1050.9671807813066420.06563843738671650.0328192186933582
1060.9771601745611950.04567965087761040.0228398254388052
1070.9701113070419190.05977738591616140.0298886929580807
1080.9631067552378710.07378648952425770.0368932447621288
1090.9626260396469540.07474792070609230.0373739603530462
1100.9532178711849290.09356425763014140.0467821288150707
1110.9411516998505750.117696600298850.0588483001494252
1120.9267023150892620.1465953698214760.0732976849107381
1130.9073754114163840.1852491771672320.092624588583616
1140.8874683815842170.2250632368315650.112531618415783
1150.8612165574887740.2775668850224510.138783442511226
1160.8499202516222130.3001594967555740.150079748377787
1170.8294164266995190.3411671466009610.170583573300481
1180.7966924295510960.4066151408978090.203307570448904
1190.8296461368840210.3407077262319570.170353863115979
1200.8057738978593330.3884522042813340.194226102140667
1210.7984207325428050.403158534914390.201579267457195
1220.7745999114385880.4508001771228240.225400088561412
1230.7470612852989640.5058774294020710.252938714701036
1240.726865186316490.5462696273670190.27313481368351
1250.6782636815119990.6434726369760020.321736318488001
1260.6416829378297310.7166341243405380.358317062170269
1270.5880809837073420.8238380325853160.411919016292658
1280.6544438184295820.6911123631408370.345556181570418
1290.6836672348719380.6326655302561240.316332765128062
1300.628401178122740.743197643754520.37159882187726
1310.5711442542350790.8577114915298420.428855745764921
1320.5165403325487360.9669193349025270.483459667451264
1330.4566326340298710.9132652680597420.543367365970129
1340.4309902692279530.8619805384559050.569009730772047
1350.4700240812241510.9400481624483020.529975918775849
1360.5016416665254510.9967166669490980.498358333474549
1370.6485347032537730.7029305934924540.351465296746227
1380.6497618411332870.7004763177334270.350238158866713
1390.6140598918893550.771880216221290.385940108110645
1400.5715097743119180.8569804513761640.428490225688082
1410.5072892625099540.9854214749800920.492710737490046
1420.8436918058131020.3126163883737950.156308194186898
1430.8312589477581640.3374821044836730.168741052241836
1440.9998832411133620.0002335177732755610.000116758886637781
1450.9999979227347944.15453041151827e-062.07726520575914e-06
1460.9999945908493911.08183012185309e-055.40915060926543e-06
1470.9999914968596131.70062807748814e-058.50314038744071e-06
1480.9999995413366789.17326644376279e-074.58663322188139e-07
1490.9999991398192151.72036156979472e-068.60180784897359e-07
1500.9999946909022351.06181955298644e-055.30909776493222e-06
1510.9999699165251776.01669496469368e-053.00834748234684e-05
1520.9998359843821320.0003280312357363920.000164015617868196
1530.9999935944604681.28110790649289e-056.40553953246443e-06
1540.9999084410513390.0001831178973214889.15589486607438e-05
1550.9997353023687260.0005293952625489090.000264697631274455

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.989545118574208 & 0.0209097628515832 & 0.0104548814257916 \tabularnewline
10 & 0.979763849250582 & 0.0404723014988358 & 0.0202361507494179 \tabularnewline
11 & 0.962937766500869 & 0.074124466998262 & 0.037062233499131 \tabularnewline
12 & 0.937425884217984 & 0.125148231564031 & 0.0625741157820157 \tabularnewline
13 & 0.915132810461307 & 0.169734379077385 & 0.0848671895386926 \tabularnewline
14 & 0.870189713266833 & 0.259620573466333 & 0.129810286733167 \tabularnewline
15 & 0.818854157501621 & 0.362291684996757 & 0.181145842498379 \tabularnewline
16 & 0.758493578256718 & 0.483012843486563 & 0.241506421743282 \tabularnewline
17 & 0.704906193005661 & 0.590187613988678 & 0.295093806994339 \tabularnewline
18 & 0.704615381894379 & 0.590769236211242 & 0.295384618105621 \tabularnewline
19 & 0.828995374663304 & 0.342009250673391 & 0.171004625336696 \tabularnewline
20 & 0.778527285514688 & 0.442945428970624 & 0.221472714485312 \tabularnewline
21 & 0.758386685178732 & 0.483226629642537 & 0.241613314821268 \tabularnewline
22 & 0.968478225596758 & 0.0630435488064831 & 0.0315217744032416 \tabularnewline
23 & 0.958493497325956 & 0.083013005348088 & 0.041506502674044 \tabularnewline
24 & 0.96655316321655 & 0.066893673566899 & 0.0334468367834495 \tabularnewline
25 & 0.965361064389922 & 0.0692778712201561 & 0.034638935610078 \tabularnewline
26 & 0.951003596823462 & 0.0979928063530766 & 0.0489964031765383 \tabularnewline
27 & 0.945064826510095 & 0.109870346979809 & 0.0549351734899046 \tabularnewline
28 & 0.925659177961694 & 0.148681644076612 & 0.0743408220383061 \tabularnewline
29 & 0.902795087350746 & 0.194409825298508 & 0.0972049126492542 \tabularnewline
30 & 0.877810505051964 & 0.244378989896073 & 0.122189494948036 \tabularnewline
31 & 0.860236709537245 & 0.27952658092551 & 0.139763290462755 \tabularnewline
32 & 0.853869867879324 & 0.292260264241352 & 0.146130132120676 \tabularnewline
33 & 0.825413122011461 & 0.349173755977077 & 0.174586877988539 \tabularnewline
34 & 0.792184125245389 & 0.415631749509222 & 0.207815874754611 \tabularnewline
35 & 0.769608160007256 & 0.460783679985489 & 0.230391839992745 \tabularnewline
36 & 0.776287208491 & 0.447425583018001 & 0.223712791509 \tabularnewline
37 & 0.876882482946054 & 0.246235034107893 & 0.123117517053946 \tabularnewline
38 & 0.847255398830225 & 0.305489202339549 & 0.152744601169775 \tabularnewline
39 & 0.826986143516237 & 0.346027712967526 & 0.173013856483763 \tabularnewline
40 & 0.836949890663032 & 0.326100218673935 & 0.163050109336968 \tabularnewline
41 & 0.929521378458691 & 0.140957243082618 & 0.0704786215413091 \tabularnewline
42 & 0.914483561279613 & 0.171032877440775 & 0.0855164387203873 \tabularnewline
43 & 0.892675096539399 & 0.214649806921202 & 0.107324903460601 \tabularnewline
44 & 0.873468243290052 & 0.253063513419896 & 0.126531756709948 \tabularnewline
45 & 0.844510972030107 & 0.310978055939786 & 0.155489027969893 \tabularnewline
46 & 0.993667932563964 & 0.0126641348720717 & 0.00633206743603585 \tabularnewline
47 & 0.991673793294446 & 0.0166524134111072 & 0.00832620670555362 \tabularnewline
48 & 0.989934546197439 & 0.020130907605122 & 0.010065453802561 \tabularnewline
49 & 0.987243695247514 & 0.0255126095049713 & 0.0127563047524856 \tabularnewline
50 & 0.985780810421478 & 0.0284383791570447 & 0.0142191895785223 \tabularnewline
51 & 0.982561359952974 & 0.0348772800940528 & 0.0174386400470264 \tabularnewline
52 & 0.976574636512491 & 0.046850726975019 & 0.0234253634875095 \tabularnewline
53 & 0.980793220814355 & 0.0384135583712902 & 0.0192067791856451 \tabularnewline
54 & 0.975141203474592 & 0.0497175930508151 & 0.0248587965254076 \tabularnewline
55 & 0.970803671291346 & 0.0583926574173076 & 0.0291963287086538 \tabularnewline
56 & 0.965860676940537 & 0.0682786461189252 & 0.0341393230594626 \tabularnewline
57 & 0.958816352149079 & 0.0823672957018425 & 0.0411836478509213 \tabularnewline
58 & 0.959135037530655 & 0.0817299249386906 & 0.0408649624693453 \tabularnewline
59 & 0.949316401370528 & 0.101367197258945 & 0.0506835986294723 \tabularnewline
60 & 0.944931477154365 & 0.110137045691269 & 0.0550685228456346 \tabularnewline
61 & 0.947102302644704 & 0.105795394710592 & 0.0528976973552959 \tabularnewline
62 & 0.935672413792814 & 0.128655172414372 & 0.0643275862071861 \tabularnewline
63 & 0.92292159479187 & 0.154156810416261 & 0.0770784052081303 \tabularnewline
64 & 0.9118163389868 & 0.176367322026399 & 0.0881836610131997 \tabularnewline
65 & 0.89585317948651 & 0.208293641026981 & 0.10414682051349 \tabularnewline
66 & 0.873277839990355 & 0.25344432001929 & 0.126722160009645 \tabularnewline
67 & 0.88140150290985 & 0.237196994180301 & 0.11859849709015 \tabularnewline
68 & 0.85925588209716 & 0.28148823580568 & 0.14074411790284 \tabularnewline
69 & 0.85032038634186 & 0.299359227316279 & 0.14967961365814 \tabularnewline
70 & 0.843803636543681 & 0.312392726912639 & 0.156196363456319 \tabularnewline
71 & 0.825622565672615 & 0.348754868654769 & 0.174377434327385 \tabularnewline
72 & 0.802312752570139 & 0.395374494859722 & 0.197687247429861 \tabularnewline
73 & 0.775216007907333 & 0.449567984185333 & 0.224783992092667 \tabularnewline
74 & 0.742520363556193 & 0.514959272887614 & 0.257479636443807 \tabularnewline
75 & 0.780903380698969 & 0.438193238602061 & 0.219096619301031 \tabularnewline
76 & 0.762421928890018 & 0.475156142219965 & 0.237578071109982 \tabularnewline
77 & 0.760236196163017 & 0.479527607673967 & 0.239763803836983 \tabularnewline
78 & 0.815466180693383 & 0.369067638613234 & 0.184533819306617 \tabularnewline
79 & 0.831792048729867 & 0.336415902540266 & 0.168207951270133 \tabularnewline
80 & 0.805143780456521 & 0.389712439086958 & 0.194856219543479 \tabularnewline
81 & 0.772030739510581 & 0.455938520978838 & 0.227969260489419 \tabularnewline
82 & 0.924365700587643 & 0.151268598824714 & 0.075634299412357 \tabularnewline
83 & 0.916751388347744 & 0.166497223304513 & 0.0832486116522563 \tabularnewline
84 & 0.925122027527423 & 0.149755944945154 & 0.0748779724725768 \tabularnewline
85 & 0.908363605339315 & 0.183272789321369 & 0.0916363946606846 \tabularnewline
86 & 0.889835133775658 & 0.220329732448685 & 0.110164866224342 \tabularnewline
87 & 0.921407870874033 & 0.157184258251934 & 0.0785921291259671 \tabularnewline
88 & 0.970421923314079 & 0.0591561533718415 & 0.0295780766859208 \tabularnewline
89 & 0.975097214940514 & 0.0498055701189725 & 0.0249027850594862 \tabularnewline
90 & 0.98948679269921 & 0.0210264146015796 & 0.0105132073007898 \tabularnewline
91 & 0.9867551624832 & 0.0264896750335995 & 0.0132448375167997 \tabularnewline
92 & 0.989823986651566 & 0.0203520266968675 & 0.0101760133484338 \tabularnewline
93 & 0.986582201019012 & 0.0268355979619758 & 0.0134177989809879 \tabularnewline
94 & 0.983657392291684 & 0.0326852154166324 & 0.0163426077083162 \tabularnewline
95 & 0.981951524507037 & 0.0360969509859255 & 0.0180484754929627 \tabularnewline
96 & 0.976614053683606 & 0.0467718926327871 & 0.0233859463163936 \tabularnewline
97 & 0.97881161638405 & 0.0423767672319003 & 0.0211883836159501 \tabularnewline
98 & 0.973561118038161 & 0.052877763923677 & 0.0264388819618385 \tabularnewline
99 & 0.966723866537889 & 0.0665522669242218 & 0.0332761334621109 \tabularnewline
100 & 0.961800654701744 & 0.0763986905965111 & 0.0381993452982555 \tabularnewline
101 & 0.950623474403378 & 0.0987530511932443 & 0.0493765255966222 \tabularnewline
102 & 0.945559862750169 & 0.108880274499662 & 0.0544401372498308 \tabularnewline
103 & 0.948307420355918 & 0.103385159288164 & 0.0516925796440819 \tabularnewline
104 & 0.971565737474773 & 0.0568685250504543 & 0.0284342625252271 \tabularnewline
105 & 0.967180781306642 & 0.0656384373867165 & 0.0328192186933582 \tabularnewline
106 & 0.977160174561195 & 0.0456796508776104 & 0.0228398254388052 \tabularnewline
107 & 0.970111307041919 & 0.0597773859161614 & 0.0298886929580807 \tabularnewline
108 & 0.963106755237871 & 0.0737864895242577 & 0.0368932447621288 \tabularnewline
109 & 0.962626039646954 & 0.0747479207060923 & 0.0373739603530462 \tabularnewline
110 & 0.953217871184929 & 0.0935642576301414 & 0.0467821288150707 \tabularnewline
111 & 0.941151699850575 & 0.11769660029885 & 0.0588483001494252 \tabularnewline
112 & 0.926702315089262 & 0.146595369821476 & 0.0732976849107381 \tabularnewline
113 & 0.907375411416384 & 0.185249177167232 & 0.092624588583616 \tabularnewline
114 & 0.887468381584217 & 0.225063236831565 & 0.112531618415783 \tabularnewline
115 & 0.861216557488774 & 0.277566885022451 & 0.138783442511226 \tabularnewline
116 & 0.849920251622213 & 0.300159496755574 & 0.150079748377787 \tabularnewline
117 & 0.829416426699519 & 0.341167146600961 & 0.170583573300481 \tabularnewline
118 & 0.796692429551096 & 0.406615140897809 & 0.203307570448904 \tabularnewline
119 & 0.829646136884021 & 0.340707726231957 & 0.170353863115979 \tabularnewline
120 & 0.805773897859333 & 0.388452204281334 & 0.194226102140667 \tabularnewline
121 & 0.798420732542805 & 0.40315853491439 & 0.201579267457195 \tabularnewline
122 & 0.774599911438588 & 0.450800177122824 & 0.225400088561412 \tabularnewline
123 & 0.747061285298964 & 0.505877429402071 & 0.252938714701036 \tabularnewline
124 & 0.72686518631649 & 0.546269627367019 & 0.27313481368351 \tabularnewline
125 & 0.678263681511999 & 0.643472636976002 & 0.321736318488001 \tabularnewline
126 & 0.641682937829731 & 0.716634124340538 & 0.358317062170269 \tabularnewline
127 & 0.588080983707342 & 0.823838032585316 & 0.411919016292658 \tabularnewline
128 & 0.654443818429582 & 0.691112363140837 & 0.345556181570418 \tabularnewline
129 & 0.683667234871938 & 0.632665530256124 & 0.316332765128062 \tabularnewline
130 & 0.62840117812274 & 0.74319764375452 & 0.37159882187726 \tabularnewline
131 & 0.571144254235079 & 0.857711491529842 & 0.428855745764921 \tabularnewline
132 & 0.516540332548736 & 0.966919334902527 & 0.483459667451264 \tabularnewline
133 & 0.456632634029871 & 0.913265268059742 & 0.543367365970129 \tabularnewline
134 & 0.430990269227953 & 0.861980538455905 & 0.569009730772047 \tabularnewline
135 & 0.470024081224151 & 0.940048162448302 & 0.529975918775849 \tabularnewline
136 & 0.501641666525451 & 0.996716666949098 & 0.498358333474549 \tabularnewline
137 & 0.648534703253773 & 0.702930593492454 & 0.351465296746227 \tabularnewline
138 & 0.649761841133287 & 0.700476317733427 & 0.350238158866713 \tabularnewline
139 & 0.614059891889355 & 0.77188021622129 & 0.385940108110645 \tabularnewline
140 & 0.571509774311918 & 0.856980451376164 & 0.428490225688082 \tabularnewline
141 & 0.507289262509954 & 0.985421474980092 & 0.492710737490046 \tabularnewline
142 & 0.843691805813102 & 0.312616388373795 & 0.156308194186898 \tabularnewline
143 & 0.831258947758164 & 0.337482104483673 & 0.168741052241836 \tabularnewline
144 & 0.999883241113362 & 0.000233517773275561 & 0.000116758886637781 \tabularnewline
145 & 0.999997922734794 & 4.15453041151827e-06 & 2.07726520575914e-06 \tabularnewline
146 & 0.999994590849391 & 1.08183012185309e-05 & 5.40915060926543e-06 \tabularnewline
147 & 0.999991496859613 & 1.70062807748814e-05 & 8.50314038744071e-06 \tabularnewline
148 & 0.999999541336678 & 9.17326644376279e-07 & 4.58663322188139e-07 \tabularnewline
149 & 0.999999139819215 & 1.72036156979472e-06 & 8.60180784897359e-07 \tabularnewline
150 & 0.999994690902235 & 1.06181955298644e-05 & 5.30909776493222e-06 \tabularnewline
151 & 0.999969916525177 & 6.01669496469368e-05 & 3.00834748234684e-05 \tabularnewline
152 & 0.999835984382132 & 0.000328031235736392 & 0.000164015617868196 \tabularnewline
153 & 0.999993594460468 & 1.28110790649289e-05 & 6.40553953246443e-06 \tabularnewline
154 & 0.999908441051339 & 0.000183117897321488 & 9.15589486607438e-05 \tabularnewline
155 & 0.999735302368726 & 0.000529395262548909 & 0.000264697631274455 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144867&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]9[/C][C]0.989545118574208[/C][C]0.0209097628515832[/C][C]0.0104548814257916[/C][/ROW]
[ROW][C]10[/C][C]0.979763849250582[/C][C]0.0404723014988358[/C][C]0.0202361507494179[/C][/ROW]
[ROW][C]11[/C][C]0.962937766500869[/C][C]0.074124466998262[/C][C]0.037062233499131[/C][/ROW]
[ROW][C]12[/C][C]0.937425884217984[/C][C]0.125148231564031[/C][C]0.0625741157820157[/C][/ROW]
[ROW][C]13[/C][C]0.915132810461307[/C][C]0.169734379077385[/C][C]0.0848671895386926[/C][/ROW]
[ROW][C]14[/C][C]0.870189713266833[/C][C]0.259620573466333[/C][C]0.129810286733167[/C][/ROW]
[ROW][C]15[/C][C]0.818854157501621[/C][C]0.362291684996757[/C][C]0.181145842498379[/C][/ROW]
[ROW][C]16[/C][C]0.758493578256718[/C][C]0.483012843486563[/C][C]0.241506421743282[/C][/ROW]
[ROW][C]17[/C][C]0.704906193005661[/C][C]0.590187613988678[/C][C]0.295093806994339[/C][/ROW]
[ROW][C]18[/C][C]0.704615381894379[/C][C]0.590769236211242[/C][C]0.295384618105621[/C][/ROW]
[ROW][C]19[/C][C]0.828995374663304[/C][C]0.342009250673391[/C][C]0.171004625336696[/C][/ROW]
[ROW][C]20[/C][C]0.778527285514688[/C][C]0.442945428970624[/C][C]0.221472714485312[/C][/ROW]
[ROW][C]21[/C][C]0.758386685178732[/C][C]0.483226629642537[/C][C]0.241613314821268[/C][/ROW]
[ROW][C]22[/C][C]0.968478225596758[/C][C]0.0630435488064831[/C][C]0.0315217744032416[/C][/ROW]
[ROW][C]23[/C][C]0.958493497325956[/C][C]0.083013005348088[/C][C]0.041506502674044[/C][/ROW]
[ROW][C]24[/C][C]0.96655316321655[/C][C]0.066893673566899[/C][C]0.0334468367834495[/C][/ROW]
[ROW][C]25[/C][C]0.965361064389922[/C][C]0.0692778712201561[/C][C]0.034638935610078[/C][/ROW]
[ROW][C]26[/C][C]0.951003596823462[/C][C]0.0979928063530766[/C][C]0.0489964031765383[/C][/ROW]
[ROW][C]27[/C][C]0.945064826510095[/C][C]0.109870346979809[/C][C]0.0549351734899046[/C][/ROW]
[ROW][C]28[/C][C]0.925659177961694[/C][C]0.148681644076612[/C][C]0.0743408220383061[/C][/ROW]
[ROW][C]29[/C][C]0.902795087350746[/C][C]0.194409825298508[/C][C]0.0972049126492542[/C][/ROW]
[ROW][C]30[/C][C]0.877810505051964[/C][C]0.244378989896073[/C][C]0.122189494948036[/C][/ROW]
[ROW][C]31[/C][C]0.860236709537245[/C][C]0.27952658092551[/C][C]0.139763290462755[/C][/ROW]
[ROW][C]32[/C][C]0.853869867879324[/C][C]0.292260264241352[/C][C]0.146130132120676[/C][/ROW]
[ROW][C]33[/C][C]0.825413122011461[/C][C]0.349173755977077[/C][C]0.174586877988539[/C][/ROW]
[ROW][C]34[/C][C]0.792184125245389[/C][C]0.415631749509222[/C][C]0.207815874754611[/C][/ROW]
[ROW][C]35[/C][C]0.769608160007256[/C][C]0.460783679985489[/C][C]0.230391839992745[/C][/ROW]
[ROW][C]36[/C][C]0.776287208491[/C][C]0.447425583018001[/C][C]0.223712791509[/C][/ROW]
[ROW][C]37[/C][C]0.876882482946054[/C][C]0.246235034107893[/C][C]0.123117517053946[/C][/ROW]
[ROW][C]38[/C][C]0.847255398830225[/C][C]0.305489202339549[/C][C]0.152744601169775[/C][/ROW]
[ROW][C]39[/C][C]0.826986143516237[/C][C]0.346027712967526[/C][C]0.173013856483763[/C][/ROW]
[ROW][C]40[/C][C]0.836949890663032[/C][C]0.326100218673935[/C][C]0.163050109336968[/C][/ROW]
[ROW][C]41[/C][C]0.929521378458691[/C][C]0.140957243082618[/C][C]0.0704786215413091[/C][/ROW]
[ROW][C]42[/C][C]0.914483561279613[/C][C]0.171032877440775[/C][C]0.0855164387203873[/C][/ROW]
[ROW][C]43[/C][C]0.892675096539399[/C][C]0.214649806921202[/C][C]0.107324903460601[/C][/ROW]
[ROW][C]44[/C][C]0.873468243290052[/C][C]0.253063513419896[/C][C]0.126531756709948[/C][/ROW]
[ROW][C]45[/C][C]0.844510972030107[/C][C]0.310978055939786[/C][C]0.155489027969893[/C][/ROW]
[ROW][C]46[/C][C]0.993667932563964[/C][C]0.0126641348720717[/C][C]0.00633206743603585[/C][/ROW]
[ROW][C]47[/C][C]0.991673793294446[/C][C]0.0166524134111072[/C][C]0.00832620670555362[/C][/ROW]
[ROW][C]48[/C][C]0.989934546197439[/C][C]0.020130907605122[/C][C]0.010065453802561[/C][/ROW]
[ROW][C]49[/C][C]0.987243695247514[/C][C]0.0255126095049713[/C][C]0.0127563047524856[/C][/ROW]
[ROW][C]50[/C][C]0.985780810421478[/C][C]0.0284383791570447[/C][C]0.0142191895785223[/C][/ROW]
[ROW][C]51[/C][C]0.982561359952974[/C][C]0.0348772800940528[/C][C]0.0174386400470264[/C][/ROW]
[ROW][C]52[/C][C]0.976574636512491[/C][C]0.046850726975019[/C][C]0.0234253634875095[/C][/ROW]
[ROW][C]53[/C][C]0.980793220814355[/C][C]0.0384135583712902[/C][C]0.0192067791856451[/C][/ROW]
[ROW][C]54[/C][C]0.975141203474592[/C][C]0.0497175930508151[/C][C]0.0248587965254076[/C][/ROW]
[ROW][C]55[/C][C]0.970803671291346[/C][C]0.0583926574173076[/C][C]0.0291963287086538[/C][/ROW]
[ROW][C]56[/C][C]0.965860676940537[/C][C]0.0682786461189252[/C][C]0.0341393230594626[/C][/ROW]
[ROW][C]57[/C][C]0.958816352149079[/C][C]0.0823672957018425[/C][C]0.0411836478509213[/C][/ROW]
[ROW][C]58[/C][C]0.959135037530655[/C][C]0.0817299249386906[/C][C]0.0408649624693453[/C][/ROW]
[ROW][C]59[/C][C]0.949316401370528[/C][C]0.101367197258945[/C][C]0.0506835986294723[/C][/ROW]
[ROW][C]60[/C][C]0.944931477154365[/C][C]0.110137045691269[/C][C]0.0550685228456346[/C][/ROW]
[ROW][C]61[/C][C]0.947102302644704[/C][C]0.105795394710592[/C][C]0.0528976973552959[/C][/ROW]
[ROW][C]62[/C][C]0.935672413792814[/C][C]0.128655172414372[/C][C]0.0643275862071861[/C][/ROW]
[ROW][C]63[/C][C]0.92292159479187[/C][C]0.154156810416261[/C][C]0.0770784052081303[/C][/ROW]
[ROW][C]64[/C][C]0.9118163389868[/C][C]0.176367322026399[/C][C]0.0881836610131997[/C][/ROW]
[ROW][C]65[/C][C]0.89585317948651[/C][C]0.208293641026981[/C][C]0.10414682051349[/C][/ROW]
[ROW][C]66[/C][C]0.873277839990355[/C][C]0.25344432001929[/C][C]0.126722160009645[/C][/ROW]
[ROW][C]67[/C][C]0.88140150290985[/C][C]0.237196994180301[/C][C]0.11859849709015[/C][/ROW]
[ROW][C]68[/C][C]0.85925588209716[/C][C]0.28148823580568[/C][C]0.14074411790284[/C][/ROW]
[ROW][C]69[/C][C]0.85032038634186[/C][C]0.299359227316279[/C][C]0.14967961365814[/C][/ROW]
[ROW][C]70[/C][C]0.843803636543681[/C][C]0.312392726912639[/C][C]0.156196363456319[/C][/ROW]
[ROW][C]71[/C][C]0.825622565672615[/C][C]0.348754868654769[/C][C]0.174377434327385[/C][/ROW]
[ROW][C]72[/C][C]0.802312752570139[/C][C]0.395374494859722[/C][C]0.197687247429861[/C][/ROW]
[ROW][C]73[/C][C]0.775216007907333[/C][C]0.449567984185333[/C][C]0.224783992092667[/C][/ROW]
[ROW][C]74[/C][C]0.742520363556193[/C][C]0.514959272887614[/C][C]0.257479636443807[/C][/ROW]
[ROW][C]75[/C][C]0.780903380698969[/C][C]0.438193238602061[/C][C]0.219096619301031[/C][/ROW]
[ROW][C]76[/C][C]0.762421928890018[/C][C]0.475156142219965[/C][C]0.237578071109982[/C][/ROW]
[ROW][C]77[/C][C]0.760236196163017[/C][C]0.479527607673967[/C][C]0.239763803836983[/C][/ROW]
[ROW][C]78[/C][C]0.815466180693383[/C][C]0.369067638613234[/C][C]0.184533819306617[/C][/ROW]
[ROW][C]79[/C][C]0.831792048729867[/C][C]0.336415902540266[/C][C]0.168207951270133[/C][/ROW]
[ROW][C]80[/C][C]0.805143780456521[/C][C]0.389712439086958[/C][C]0.194856219543479[/C][/ROW]
[ROW][C]81[/C][C]0.772030739510581[/C][C]0.455938520978838[/C][C]0.227969260489419[/C][/ROW]
[ROW][C]82[/C][C]0.924365700587643[/C][C]0.151268598824714[/C][C]0.075634299412357[/C][/ROW]
[ROW][C]83[/C][C]0.916751388347744[/C][C]0.166497223304513[/C][C]0.0832486116522563[/C][/ROW]
[ROW][C]84[/C][C]0.925122027527423[/C][C]0.149755944945154[/C][C]0.0748779724725768[/C][/ROW]
[ROW][C]85[/C][C]0.908363605339315[/C][C]0.183272789321369[/C][C]0.0916363946606846[/C][/ROW]
[ROW][C]86[/C][C]0.889835133775658[/C][C]0.220329732448685[/C][C]0.110164866224342[/C][/ROW]
[ROW][C]87[/C][C]0.921407870874033[/C][C]0.157184258251934[/C][C]0.0785921291259671[/C][/ROW]
[ROW][C]88[/C][C]0.970421923314079[/C][C]0.0591561533718415[/C][C]0.0295780766859208[/C][/ROW]
[ROW][C]89[/C][C]0.975097214940514[/C][C]0.0498055701189725[/C][C]0.0249027850594862[/C][/ROW]
[ROW][C]90[/C][C]0.98948679269921[/C][C]0.0210264146015796[/C][C]0.0105132073007898[/C][/ROW]
[ROW][C]91[/C][C]0.9867551624832[/C][C]0.0264896750335995[/C][C]0.0132448375167997[/C][/ROW]
[ROW][C]92[/C][C]0.989823986651566[/C][C]0.0203520266968675[/C][C]0.0101760133484338[/C][/ROW]
[ROW][C]93[/C][C]0.986582201019012[/C][C]0.0268355979619758[/C][C]0.0134177989809879[/C][/ROW]
[ROW][C]94[/C][C]0.983657392291684[/C][C]0.0326852154166324[/C][C]0.0163426077083162[/C][/ROW]
[ROW][C]95[/C][C]0.981951524507037[/C][C]0.0360969509859255[/C][C]0.0180484754929627[/C][/ROW]
[ROW][C]96[/C][C]0.976614053683606[/C][C]0.0467718926327871[/C][C]0.0233859463163936[/C][/ROW]
[ROW][C]97[/C][C]0.97881161638405[/C][C]0.0423767672319003[/C][C]0.0211883836159501[/C][/ROW]
[ROW][C]98[/C][C]0.973561118038161[/C][C]0.052877763923677[/C][C]0.0264388819618385[/C][/ROW]
[ROW][C]99[/C][C]0.966723866537889[/C][C]0.0665522669242218[/C][C]0.0332761334621109[/C][/ROW]
[ROW][C]100[/C][C]0.961800654701744[/C][C]0.0763986905965111[/C][C]0.0381993452982555[/C][/ROW]
[ROW][C]101[/C][C]0.950623474403378[/C][C]0.0987530511932443[/C][C]0.0493765255966222[/C][/ROW]
[ROW][C]102[/C][C]0.945559862750169[/C][C]0.108880274499662[/C][C]0.0544401372498308[/C][/ROW]
[ROW][C]103[/C][C]0.948307420355918[/C][C]0.103385159288164[/C][C]0.0516925796440819[/C][/ROW]
[ROW][C]104[/C][C]0.971565737474773[/C][C]0.0568685250504543[/C][C]0.0284342625252271[/C][/ROW]
[ROW][C]105[/C][C]0.967180781306642[/C][C]0.0656384373867165[/C][C]0.0328192186933582[/C][/ROW]
[ROW][C]106[/C][C]0.977160174561195[/C][C]0.0456796508776104[/C][C]0.0228398254388052[/C][/ROW]
[ROW][C]107[/C][C]0.970111307041919[/C][C]0.0597773859161614[/C][C]0.0298886929580807[/C][/ROW]
[ROW][C]108[/C][C]0.963106755237871[/C][C]0.0737864895242577[/C][C]0.0368932447621288[/C][/ROW]
[ROW][C]109[/C][C]0.962626039646954[/C][C]0.0747479207060923[/C][C]0.0373739603530462[/C][/ROW]
[ROW][C]110[/C][C]0.953217871184929[/C][C]0.0935642576301414[/C][C]0.0467821288150707[/C][/ROW]
[ROW][C]111[/C][C]0.941151699850575[/C][C]0.11769660029885[/C][C]0.0588483001494252[/C][/ROW]
[ROW][C]112[/C][C]0.926702315089262[/C][C]0.146595369821476[/C][C]0.0732976849107381[/C][/ROW]
[ROW][C]113[/C][C]0.907375411416384[/C][C]0.185249177167232[/C][C]0.092624588583616[/C][/ROW]
[ROW][C]114[/C][C]0.887468381584217[/C][C]0.225063236831565[/C][C]0.112531618415783[/C][/ROW]
[ROW][C]115[/C][C]0.861216557488774[/C][C]0.277566885022451[/C][C]0.138783442511226[/C][/ROW]
[ROW][C]116[/C][C]0.849920251622213[/C][C]0.300159496755574[/C][C]0.150079748377787[/C][/ROW]
[ROW][C]117[/C][C]0.829416426699519[/C][C]0.341167146600961[/C][C]0.170583573300481[/C][/ROW]
[ROW][C]118[/C][C]0.796692429551096[/C][C]0.406615140897809[/C][C]0.203307570448904[/C][/ROW]
[ROW][C]119[/C][C]0.829646136884021[/C][C]0.340707726231957[/C][C]0.170353863115979[/C][/ROW]
[ROW][C]120[/C][C]0.805773897859333[/C][C]0.388452204281334[/C][C]0.194226102140667[/C][/ROW]
[ROW][C]121[/C][C]0.798420732542805[/C][C]0.40315853491439[/C][C]0.201579267457195[/C][/ROW]
[ROW][C]122[/C][C]0.774599911438588[/C][C]0.450800177122824[/C][C]0.225400088561412[/C][/ROW]
[ROW][C]123[/C][C]0.747061285298964[/C][C]0.505877429402071[/C][C]0.252938714701036[/C][/ROW]
[ROW][C]124[/C][C]0.72686518631649[/C][C]0.546269627367019[/C][C]0.27313481368351[/C][/ROW]
[ROW][C]125[/C][C]0.678263681511999[/C][C]0.643472636976002[/C][C]0.321736318488001[/C][/ROW]
[ROW][C]126[/C][C]0.641682937829731[/C][C]0.716634124340538[/C][C]0.358317062170269[/C][/ROW]
[ROW][C]127[/C][C]0.588080983707342[/C][C]0.823838032585316[/C][C]0.411919016292658[/C][/ROW]
[ROW][C]128[/C][C]0.654443818429582[/C][C]0.691112363140837[/C][C]0.345556181570418[/C][/ROW]
[ROW][C]129[/C][C]0.683667234871938[/C][C]0.632665530256124[/C][C]0.316332765128062[/C][/ROW]
[ROW][C]130[/C][C]0.62840117812274[/C][C]0.74319764375452[/C][C]0.37159882187726[/C][/ROW]
[ROW][C]131[/C][C]0.571144254235079[/C][C]0.857711491529842[/C][C]0.428855745764921[/C][/ROW]
[ROW][C]132[/C][C]0.516540332548736[/C][C]0.966919334902527[/C][C]0.483459667451264[/C][/ROW]
[ROW][C]133[/C][C]0.456632634029871[/C][C]0.913265268059742[/C][C]0.543367365970129[/C][/ROW]
[ROW][C]134[/C][C]0.430990269227953[/C][C]0.861980538455905[/C][C]0.569009730772047[/C][/ROW]
[ROW][C]135[/C][C]0.470024081224151[/C][C]0.940048162448302[/C][C]0.529975918775849[/C][/ROW]
[ROW][C]136[/C][C]0.501641666525451[/C][C]0.996716666949098[/C][C]0.498358333474549[/C][/ROW]
[ROW][C]137[/C][C]0.648534703253773[/C][C]0.702930593492454[/C][C]0.351465296746227[/C][/ROW]
[ROW][C]138[/C][C]0.649761841133287[/C][C]0.700476317733427[/C][C]0.350238158866713[/C][/ROW]
[ROW][C]139[/C][C]0.614059891889355[/C][C]0.77188021622129[/C][C]0.385940108110645[/C][/ROW]
[ROW][C]140[/C][C]0.571509774311918[/C][C]0.856980451376164[/C][C]0.428490225688082[/C][/ROW]
[ROW][C]141[/C][C]0.507289262509954[/C][C]0.985421474980092[/C][C]0.492710737490046[/C][/ROW]
[ROW][C]142[/C][C]0.843691805813102[/C][C]0.312616388373795[/C][C]0.156308194186898[/C][/ROW]
[ROW][C]143[/C][C]0.831258947758164[/C][C]0.337482104483673[/C][C]0.168741052241836[/C][/ROW]
[ROW][C]144[/C][C]0.999883241113362[/C][C]0.000233517773275561[/C][C]0.000116758886637781[/C][/ROW]
[ROW][C]145[/C][C]0.999997922734794[/C][C]4.15453041151827e-06[/C][C]2.07726520575914e-06[/C][/ROW]
[ROW][C]146[/C][C]0.999994590849391[/C][C]1.08183012185309e-05[/C][C]5.40915060926543e-06[/C][/ROW]
[ROW][C]147[/C][C]0.999991496859613[/C][C]1.70062807748814e-05[/C][C]8.50314038744071e-06[/C][/ROW]
[ROW][C]148[/C][C]0.999999541336678[/C][C]9.17326644376279e-07[/C][C]4.58663322188139e-07[/C][/ROW]
[ROW][C]149[/C][C]0.999999139819215[/C][C]1.72036156979472e-06[/C][C]8.60180784897359e-07[/C][/ROW]
[ROW][C]150[/C][C]0.999994690902235[/C][C]1.06181955298644e-05[/C][C]5.30909776493222e-06[/C][/ROW]
[ROW][C]151[/C][C]0.999969916525177[/C][C]6.01669496469368e-05[/C][C]3.00834748234684e-05[/C][/ROW]
[ROW][C]152[/C][C]0.999835984382132[/C][C]0.000328031235736392[/C][C]0.000164015617868196[/C][/ROW]
[ROW][C]153[/C][C]0.999993594460468[/C][C]1.28110790649289e-05[/C][C]6.40553953246443e-06[/C][/ROW]
[ROW][C]154[/C][C]0.999908441051339[/C][C]0.000183117897321488[/C][C]9.15589486607438e-05[/C][/ROW]
[ROW][C]155[/C][C]0.999735302368726[/C][C]0.000529395262548909[/C][C]0.000264697631274455[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144867&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144867&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9895451185742080.02090976285158320.0104548814257916
100.9797638492505820.04047230149883580.0202361507494179
110.9629377665008690.0741244669982620.037062233499131
120.9374258842179840.1251482315640310.0625741157820157
130.9151328104613070.1697343790773850.0848671895386926
140.8701897132668330.2596205734663330.129810286733167
150.8188541575016210.3622916849967570.181145842498379
160.7584935782567180.4830128434865630.241506421743282
170.7049061930056610.5901876139886780.295093806994339
180.7046153818943790.5907692362112420.295384618105621
190.8289953746633040.3420092506733910.171004625336696
200.7785272855146880.4429454289706240.221472714485312
210.7583866851787320.4832266296425370.241613314821268
220.9684782255967580.06304354880648310.0315217744032416
230.9584934973259560.0830130053480880.041506502674044
240.966553163216550.0668936735668990.0334468367834495
250.9653610643899220.06927787122015610.034638935610078
260.9510035968234620.09799280635307660.0489964031765383
270.9450648265100950.1098703469798090.0549351734899046
280.9256591779616940.1486816440766120.0743408220383061
290.9027950873507460.1944098252985080.0972049126492542
300.8778105050519640.2443789898960730.122189494948036
310.8602367095372450.279526580925510.139763290462755
320.8538698678793240.2922602642413520.146130132120676
330.8254131220114610.3491737559770770.174586877988539
340.7921841252453890.4156317495092220.207815874754611
350.7696081600072560.4607836799854890.230391839992745
360.7762872084910.4474255830180010.223712791509
370.8768824829460540.2462350341078930.123117517053946
380.8472553988302250.3054892023395490.152744601169775
390.8269861435162370.3460277129675260.173013856483763
400.8369498906630320.3261002186739350.163050109336968
410.9295213784586910.1409572430826180.0704786215413091
420.9144835612796130.1710328774407750.0855164387203873
430.8926750965393990.2146498069212020.107324903460601
440.8734682432900520.2530635134198960.126531756709948
450.8445109720301070.3109780559397860.155489027969893
460.9936679325639640.01266413487207170.00633206743603585
470.9916737932944460.01665241341110720.00832620670555362
480.9899345461974390.0201309076051220.010065453802561
490.9872436952475140.02551260950497130.0127563047524856
500.9857808104214780.02843837915704470.0142191895785223
510.9825613599529740.03487728009405280.0174386400470264
520.9765746365124910.0468507269750190.0234253634875095
530.9807932208143550.03841355837129020.0192067791856451
540.9751412034745920.04971759305081510.0248587965254076
550.9708036712913460.05839265741730760.0291963287086538
560.9658606769405370.06827864611892520.0341393230594626
570.9588163521490790.08236729570184250.0411836478509213
580.9591350375306550.08172992493869060.0408649624693453
590.9493164013705280.1013671972589450.0506835986294723
600.9449314771543650.1101370456912690.0550685228456346
610.9471023026447040.1057953947105920.0528976973552959
620.9356724137928140.1286551724143720.0643275862071861
630.922921594791870.1541568104162610.0770784052081303
640.91181633898680.1763673220263990.0881836610131997
650.895853179486510.2082936410269810.10414682051349
660.8732778399903550.253444320019290.126722160009645
670.881401502909850.2371969941803010.11859849709015
680.859255882097160.281488235805680.14074411790284
690.850320386341860.2993592273162790.14967961365814
700.8438036365436810.3123927269126390.156196363456319
710.8256225656726150.3487548686547690.174377434327385
720.8023127525701390.3953744948597220.197687247429861
730.7752160079073330.4495679841853330.224783992092667
740.7425203635561930.5149592728876140.257479636443807
750.7809033806989690.4381932386020610.219096619301031
760.7624219288900180.4751561422199650.237578071109982
770.7602361961630170.4795276076739670.239763803836983
780.8154661806933830.3690676386132340.184533819306617
790.8317920487298670.3364159025402660.168207951270133
800.8051437804565210.3897124390869580.194856219543479
810.7720307395105810.4559385209788380.227969260489419
820.9243657005876430.1512685988247140.075634299412357
830.9167513883477440.1664972233045130.0832486116522563
840.9251220275274230.1497559449451540.0748779724725768
850.9083636053393150.1832727893213690.0916363946606846
860.8898351337756580.2203297324486850.110164866224342
870.9214078708740330.1571842582519340.0785921291259671
880.9704219233140790.05915615337184150.0295780766859208
890.9750972149405140.04980557011897250.0249027850594862
900.989486792699210.02102641460157960.0105132073007898
910.98675516248320.02648967503359950.0132448375167997
920.9898239866515660.02035202669686750.0101760133484338
930.9865822010190120.02683559796197580.0134177989809879
940.9836573922916840.03268521541663240.0163426077083162
950.9819515245070370.03609695098592550.0180484754929627
960.9766140536836060.04677189263278710.0233859463163936
970.978811616384050.04237676723190030.0211883836159501
980.9735611180381610.0528777639236770.0264388819618385
990.9667238665378890.06655226692422180.0332761334621109
1000.9618006547017440.07639869059651110.0381993452982555
1010.9506234744033780.09875305119324430.0493765255966222
1020.9455598627501690.1088802744996620.0544401372498308
1030.9483074203559180.1033851592881640.0516925796440819
1040.9715657374747730.05686852505045430.0284342625252271
1050.9671807813066420.06563843738671650.0328192186933582
1060.9771601745611950.04567965087761040.0228398254388052
1070.9701113070419190.05977738591616140.0298886929580807
1080.9631067552378710.07378648952425770.0368932447621288
1090.9626260396469540.07474792070609230.0373739603530462
1100.9532178711849290.09356425763014140.0467821288150707
1110.9411516998505750.117696600298850.0588483001494252
1120.9267023150892620.1465953698214760.0732976849107381
1130.9073754114163840.1852491771672320.092624588583616
1140.8874683815842170.2250632368315650.112531618415783
1150.8612165574887740.2775668850224510.138783442511226
1160.8499202516222130.3001594967555740.150079748377787
1170.8294164266995190.3411671466009610.170583573300481
1180.7966924295510960.4066151408978090.203307570448904
1190.8296461368840210.3407077262319570.170353863115979
1200.8057738978593330.3884522042813340.194226102140667
1210.7984207325428050.403158534914390.201579267457195
1220.7745999114385880.4508001771228240.225400088561412
1230.7470612852989640.5058774294020710.252938714701036
1240.726865186316490.5462696273670190.27313481368351
1250.6782636815119990.6434726369760020.321736318488001
1260.6416829378297310.7166341243405380.358317062170269
1270.5880809837073420.8238380325853160.411919016292658
1280.6544438184295820.6911123631408370.345556181570418
1290.6836672348719380.6326655302561240.316332765128062
1300.628401178122740.743197643754520.37159882187726
1310.5711442542350790.8577114915298420.428855745764921
1320.5165403325487360.9669193349025270.483459667451264
1330.4566326340298710.9132652680597420.543367365970129
1340.4309902692279530.8619805384559050.569009730772047
1350.4700240812241510.9400481624483020.529975918775849
1360.5016416665254510.9967166669490980.498358333474549
1370.6485347032537730.7029305934924540.351465296746227
1380.6497618411332870.7004763177334270.350238158866713
1390.6140598918893550.771880216221290.385940108110645
1400.5715097743119180.8569804513761640.428490225688082
1410.5072892625099540.9854214749800920.492710737490046
1420.8436918058131020.3126163883737950.156308194186898
1430.8312589477581640.3374821044836730.168741052241836
1440.9998832411133620.0002335177732755610.000116758886637781
1450.9999979227347944.15453041151827e-062.07726520575914e-06
1460.9999945908493911.08183012185309e-055.40915060926543e-06
1470.9999914968596131.70062807748814e-058.50314038744071e-06
1480.9999995413366789.17326644376279e-074.58663322188139e-07
1490.9999991398192151.72036156979472e-068.60180784897359e-07
1500.9999946909022351.06181955298644e-055.30909776493222e-06
1510.9999699165251776.01669496469368e-053.00834748234684e-05
1520.9998359843821320.0003280312357363920.000164015617868196
1530.9999935944604681.28110790649289e-056.40553953246443e-06
1540.9999084410513390.0001831178973214889.15589486607438e-05
1550.9997353023687260.0005293952625489090.000264697631274455







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level120.0816326530612245NOK
5% type I error level330.224489795918367NOK
10% type I error level540.36734693877551NOK

\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 & 12 & 0.0816326530612245 & NOK \tabularnewline
5% type I error level & 33 & 0.224489795918367 & NOK \tabularnewline
10% type I error level & 54 & 0.36734693877551 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144867&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]12[/C][C]0.0816326530612245[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]33[/C][C]0.224489795918367[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]54[/C][C]0.36734693877551[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144867&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144867&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level120.0816326530612245NOK
5% type I error level330.224489795918367NOK
10% type I error level540.36734693877551NOK



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