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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 18 Dec 2011 13:19:05 -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/Dec/18/t1324232502vggy8fajcfuaxp8.htm/, Retrieved Fri, 03 May 2024 14:57:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157110, Retrieved Fri, 03 May 2024 14:57:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

Tree of Dependent Computations

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]
-   PD  [Multiple Regression] [WS 7] [2011-11-17 14:51:59] [088a244c534fec2347300624359db3c1]
-    D    [Multiple Regression] [WS7] [2011-11-17 15:16:59] [088a244c534fec2347300624359db3c1]
- R  D      [Multiple Regression] [] [2011-12-18 16:46:31] [06c08141d7d783218a8164fd2ea166f2]
-   PD          [Multiple Regression] [] [2011-12-18 18:19:05] [ce4468323d272130d499477f5e05a6d2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9	1747	272545	69	96	38
9	1209	179444	64	71	34
9	1844	222373	69	70	42
9	2683	218443	104	134	38
9	1229	167843	52	66	27
9	631	70849	28	8	35
9	4627	506574	123	149	33
9	381	33186	19	1	18
9	2063	216660	59	83	34
9	1758	213274	44	82	33
9	2132	307153	109	92	46
9	2146	239619	117	117	55
9	1805	172780	72	50	37
9	2965	364402	79	139	55
9	2098	244103	84	79	44
9	4904	384448	178	175	59
9	2242	325587	68	114	36
9	3040	333778	160	99	39
9	1438	176082	55	103	29
9	2347	266736	87	135	51
9	2522	278265	70	123	49
9	2889	442703	103	87	39
9	1447	180393	41	66	25
9	1717	189897	54	103	52
9	3363	234247	122	141	45
9	2912	238002	126	113	38
9	2828	267268	127	99	41
9	1972	270787	86	117	43
9	1495	155915	51	57	32
9	2841	342564	70	127	41
9	2300	282172	77	123	47
9	1909	216584	76	44	50
9	2140	322890	87	136	48
9	971	98672	37	43	37
9	3332	391593	98	138	43
9	2764	273950	56	83	42
9	3683	425120	121	112	44
9	1918	227636	83	79	36
9	947	115658	33	33	17
9	3472	354687	197	129	42
9	3247	324178	80	123	39
9	1692	178083	67	71	41
9	1736	195153	74	75	36
9	1790	181810	63	68	49
9	2496	153778	82	50	45
9	5501	455168	151	101	41
9	918	78800	42	20	26
9	2228	208051	76	101	52
9	4051	348077	118	149	47
9	2081	175523	54	99	45
9	1875	224591	74	95	40
9	496	24188	24	8	4
9	2540	372238	317	85	44
10	744	65029	17	21	18
10	1161	101097	64	30	14
10	3027	279012	58	97	37
10	2527	317644	85	122	61
10	3713	340779	187	127	39
10	2668	358958	142	159	42
10	2175	252529	83	89	36
10	3980	379078	142	154	50
10	3165	304468	117	139	28
10	2954	270190	114	101	43
10	2610	264889	88	92	42
10	1427	228595	67	52	37
10	1646	216027	65	96	30
10	1971	198798	132	88	35
10	2747	238146	146	85	44
10	2309	234891	82	135	36
10	1684	175816	69	143	28
10	2537	239314	68	99	45
10	893	73566	32	22	23
10	2195	242622	84	78	45
10	1695	187167	53	79	38
10	2061	209049	63	131	38
10	2340	360726	87	140	46
10	2695	342846	92	130	36
10	1809	207650	107	78	41
10	2290	206500	62	133	38
10	1792	182357	65	83	37
10	1678	153613	46	62	28
10	4024	456979	125	151	45
10	1369	145943	69	30	26
10	2309	280366	105	117	44
10	870	80953	25	49	8
10	1966	150216	54	52	27
10	1459	167878	59	73	38
10	3846	383951	208	81	37
10	2721	331734	117	136	57
10	3086	179797	105	165	45
10	2398	267843	94	81	37
10	2210	262793	78	161	40
10	1829	189142	63	48	31
10	3087	275997	74	149	36
10	2559	328875	82	75	40
10	1624	189252	36	83	36
10	1703	241381	52	99	35
10	2109	287386	79	159	39
10	4027	392647	153	152	65
10	3706	397681	109	165	30
10	2715	287748	137	117	51
10	2325	294320	65	148	41
10	2002	186856	182	73	36
10	602	43287	14	13	19
10	2146	185468	80	89	23
10	2328	236654	147	97	44
10	2618	268077	49	129	40
10	2692	305252	91	169	40
10	1222	151344	73	28	30
11	3170	157458	93	118	41
11	1870	307000	69	76	40
11	2304	298039	88	147	45
11	398	23623	11	12	1
11	2205	195817	73	146	40
11	530	61857	25	23	11
11	1596	163766	48	83	45
11	3093	415339	119	151	38
11	387	21054	16	4	0
11	2137	252805	52	81	30
11	492	31961	22	18	8
11	3474	319629	116	111	39
11	2089	240153	65	76	48
11	1659	175083	89	55	48
11	1685	152043	53	44	29
11	568	38214	34	16	8
11	2060	216299	43	73	43
11	2792	357602	82	137	52
11	1395	198104	61	50	53
11	3591	410803	81	137	48
11	2388	316105	98	154	48
11	3334	397297	124	137	50
11	1250	187992	35	71	40
11	1121	102424	42	42	36
11	2880	286327	335	84	40
11	4142	414049	174	113	46
11	1759	143860	54	63	42
11	4139	391854	133	127	46
11	1831	157429	77	55	39
11	1787	258751	48	110	41
11	2536	282399	95	110	46
11	1816	217665	113	38	32
11	3907	373356	119	95	39
11	2307	246205	92	128	39
11	2035	173260	63	41	21
11	2986	325118	101	145	47
11	1915	168994	57	147	50
11	2648	253330	86	119	36
11	2633	301703	105	185	44
11	2	1	0	0	0
11	207	14688	10	4	0
11	5	98	1	0	0
11	8	455	2	0	0
11	0	0	0	0	0
11	0	0	0	0	0
11	2117	246435	85	69	37
11	3361	392245	158	141	52
11	0	0	0	0	0
11	4	203	4	0	0
11	151	7199	5	7	0
11	474	46660	20	12	5
11	141	17547	5	0	1
11	1047	116678	42	37	43
11	29	969	2	0	0
11	1822	206501	68	52	34

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 6 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157110&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157110&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157110&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Pageviews[t] = + 187.732928612584 -9.84639423108231Month[t] + 0.00581018442251266Time_spent[t] + 4.08856238099806Logins[t] + 4.0308608467313Blogged_computations[t] + 0.618261919258944Reviewed_comp[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Pageviews[t] =  +  187.732928612584 -9.84639423108231Month[t] +  0.00581018442251266Time_spent[t] +  4.08856238099806Logins[t] +  4.0308608467313Blogged_computations[t] +  0.618261919258944Reviewed_comp[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157110&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Pageviews[t] =  +  187.732928612584 -9.84639423108231Month[t] +  0.00581018442251266Time_spent[t] +  4.08856238099806Logins[t] +  4.0308608467313Blogged_computations[t] +  0.618261919258944Reviewed_comp[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157110&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157110&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
Pageviews[t] = + 187.732928612584 -9.84639423108231Month[t] + 0.00581018442251266Time_spent[t] + 4.08856238099806Logins[t] + 4.0308608467313Blogged_computations[t] + 0.618261919258944Reviewed_comp[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)187.732928612584436.5294110.43010.6677390.33387
Month-9.8463942310823140.505105-0.24310.8082510.404125
Time_spent0.005810184422512660.0005889.881700
Logins4.088562380998060.8958664.56381e-055e-06
Blogged_computations4.03086084673131.2199233.30420.0011780.000589
Reviewed_comp0.6182619192589443.5592130.17370.8623180.431159

\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) & 187.732928612584 & 436.529411 & 0.4301 & 0.667739 & 0.33387 \tabularnewline
Month & -9.84639423108231 & 40.505105 & -0.2431 & 0.808251 & 0.404125 \tabularnewline
Time_spent & 0.00581018442251266 & 0.000588 & 9.8817 & 0 & 0 \tabularnewline
Logins & 4.08856238099806 & 0.895866 & 4.5638 & 1e-05 & 5e-06 \tabularnewline
Blogged_computations & 4.0308608467313 & 1.219923 & 3.3042 & 0.001178 & 0.000589 \tabularnewline
Reviewed_comp & 0.618261919258944 & 3.559213 & 0.1737 & 0.862318 & 0.431159 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157110&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]187.732928612584[/C][C]436.529411[/C][C]0.4301[/C][C]0.667739[/C][C]0.33387[/C][/ROW]
[ROW][C]Month[/C][C]-9.84639423108231[/C][C]40.505105[/C][C]-0.2431[/C][C]0.808251[/C][C]0.404125[/C][/ROW]
[ROW][C]Time_spent[/C][C]0.00581018442251266[/C][C]0.000588[/C][C]9.8817[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Logins[/C][C]4.08856238099806[/C][C]0.895866[/C][C]4.5638[/C][C]1e-05[/C][C]5e-06[/C][/ROW]
[ROW][C]Blogged_computations[/C][C]4.0308608467313[/C][C]1.219923[/C][C]3.3042[/C][C]0.001178[/C][C]0.000589[/C][/ROW]
[ROW][C]Reviewed_comp[/C][C]0.618261919258944[/C][C]3.559213[/C][C]0.1737[/C][C]0.862318[/C][C]0.431159[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157110&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157110&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)187.732928612584436.5294110.43010.6677390.33387
Month-9.8463942310823140.505105-0.24310.8082510.404125
Time_spent0.005810184422512660.0005889.881700
Logins4.088562380998060.8958664.56381e-055e-06
Blogged_computations4.03086084673131.2199233.30420.0011780.000589
Reviewed_comp0.6182619192589443.5592130.17370.8623180.431159






Multiple Linear Regression - Regression Statistics
Multiple R0.929796276955384
R-squared0.864521116640093
Adjusted R-squared0.860233810204653
F-TEST (value)201.646681817217
F-TEST (DF numerator)5
F-TEST (DF denominator)158
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation402.453963751783
Sum Squared Residuals25591132.4844444

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.929796276955384 \tabularnewline
R-squared & 0.864521116640093 \tabularnewline
Adjusted R-squared & 0.860233810204653 \tabularnewline
F-TEST (value) & 201.646681817217 \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 & 402.453963751783 \tabularnewline
Sum Squared Residuals & 25591132.4844444 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157110&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.929796276955384[/C][/ROW]
[ROW][C]R-squared[/C][C]0.864521116640093[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.860233810204653[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]201.646681817217[/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]402.453963751783[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]25591132.4844444[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157110&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157110&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Regression Statistics
Multiple R0.929796276955384
R-squared0.864521116640093
Adjusted R-squared0.860233810204653
F-TEST (value)201.646681817217
F-TEST (DF numerator)5
F-TEST (DF denominator)158
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation402.453963751783
Sum Squared Residuals25591132.4844444






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
117472375.21949247347-628.21949247347
212091710.59813180281-501.598131802808
318441981.38158528918-137.381585289185
426832357.14929035741325.85070964259
512291569.64929607679-340.649296076793
6631679.126937299303-48.1269372993025
746274166.29782654404460.702173455957
8381384.774421410705-3.77442141070456
920631954.75747352682108.242526473175
1017581869.10663059124-111.106630591236
1121322728.66350217486-596.663502174855
1221462475.32288487448-329.322884874483
1318051621.79426983559183.205730164412
1429653133.64869581904-168.648695819042
1520982206.47959996446-108.479599964456
1649043802.47136663091101.5286333691
1722422750.63370363403-508.633703634032
1830403115.76453634746-75.7645363474625
1914381780.16346784445-342.163467844445
2023472580.30323199394-233.303231993944
2125222528.17643372483-6.17643372483223
2228893467.22048869199-578.220488691989
2314471596.35640054983-149.35640054983
2417171870.56262740342-153.562627403415
2533632555.1114271907807.888572809303
2629122476.09098207794435.909017922065
2728282595.64313567173232.356864328273
2819722522.25013611331-550.25013611331
2914951463.0704158797831.929584120223
3028412912.94282994083-71.9428299408275
3123002578.26023709206-278.260237092058
3219091876.510077673332.4899223266968
3321402908.74440314467-768.744403144675
349711019.89741338997-48.8974133899684
3533323357.86610181271-25.8661018127086
3627642280.30334730365483.696652696347
3736833542.51696961349140.483030386509
3819182101.76863534387-183.76863534387
399471049.56110961428-102.561109614284
4034723511.30710169442-39.3071016944238
4132472829.64243573305417.357564266953
4216921719.28399138158-27.2839913815753
4317361860.11590993148-124.115909931483
4417901717.4378120141772.5621879858345
4524961557.22086460305938.779135396945
4655013793.564007499271707.43599250073
47918825.36955986411992.6304401358813
4822282057.9273660982170.072633901795
4940513233.61388109369817.386118906311
5020811766.59575969248314.40424030752
5118752114.24638357307-239.246383573073
52496372.49755293942123.50244706058
5325403927.78778079605-1387.78778079605
54744632.381821918323111.618178081677
5511611067.9106855199693.0893144800357
5630272361.38597363927665.614026360731
5725272811.84600976722-284.846009767223
5837133369.85053125382343.149468746185
5926683422.33089957894-754.330899578939
6021752276.86377040971-101.863770409708
6139803524.02360128031455.976398719692
6231652914.24700706702250.752992932979
6329542558.92103490223395.078965097767
6426102384.9226158327225.077384167297
6514271923.86222893552-496.862228935522
6616462015.69275017275-369.692750172751
6719712160.3671851066-189.367185106595
6827472439.69796983073307.302030169267
6923092355.71477413407-46.7147741340719
7016841986.62760984094-302.62760984094
7125372184.62671329188352.373286708124
72893750.43397249131142.56602750869
7321952184.6157236761610.3842763238403
7416951735.3695401267-40.3695401266988
7520612112.99838350013-51.9983835001291
7623403133.61906627219-793.619066272189
7726953003.68455304275-308.68455304275
7818092072.98584113797-263.985841137966
7922902102.16138271961187.838617280391
8017921771.9904830940620.0095169059441
8116781437.0874217597240.912578240299
8240243891.95332536501132.046674634988
8313691356.3361710680612.6638289319353
8423092646.3604456237-337.360445623699
85870864.2931822262865.70681777371428
8619661409.13185393784556.868146062162
8714591623.64310200645-164.643102006453
8838463519.89150035533326.108499644667
8927213078.50450864957-357.504508649567
9030862256.13559099838829.864409001616
9123982379.1864959924518.8135040075455
9222102608.75172005908-398.751720059077
9318291658.44575848766170.554241512341
9430872618.27176781213468.728232187869
9525592662.40054377266-103.40054377266
9616241692.86513371908-68.865133719078
9717032125.03674720465-422.036747204651
9821092747.05016433021-638.050164330208
9940273649.04838699578377.951613004217
10037063529.16213444824176.837865551759
10127152824.41305665744-109.413056657438
10223252686.99516430641-361.995164306411
10320022235.56543100114-233.565431001142
104602462.162480206467139.837519793533
10521461866.92390075823279.076099241774
10623282483.48806721412-155.488067214118
10726182391.89687840329226.103121596711
10826922940.84453818137-248.844538181368
10912221398.48255264162-176.482552641621
11031701875.509230907411294.49076909259
11118702476.33591519287-606.335915192869
11223042791.23596753591-487.235967535914
113398310.63935695470987.3606430452909
11422052128.8566893398376.1433106601727
115530640.547910005665-110.547910005665
11615961589.567485141156.43251485885477
11730933611.3116440597-518.311644059701
118387283.290656385155103.709343614845
11921372105.919094978931.0809050211044
120492432.57185937579959.4281406242012
12134742882.33703388803591.662966111973
12220892076.5343629312412.4656370687553
12316591711.94308192094-52.9430819209419
12416851374.80174133036310.198258669644
125568509.90396944828558.0960305517154
12620601832.80595919818227.194040801818
12727923076.79583297555-284.795832975546
12813951714.1565962063-319.156596206298
12935913379.34184437961211.658155620391
13023882967.1591948079-579.159194807904
13133343477.91419979059-143.914199790587
13212501625.71206225089-375.712062250892
13311211037.7981260200783.2018739799287
13428803476.0264527456-596.0264527456
13541423680.46082028784461.539179712165
13617591415.96932562019343.030674379806
13741393440.30477126348698.695228736515
13818311554.7429802806276.257019719404
13917872247.80804769822-460.80804769822
14025362580.461030425-44.4610304250028
14118161979.06102704175-163.061027041754
14239073142.27272595166764.727274048342
14323072426.12919009994-119.129190099936
14420351521.92337013852513.076629861478
14529862994.89606461116-8.89606461116402
14619151917.80659451812-2.80659451812199
14726482404.86284644599243.137153554008
14826333034.5844939935-401.584493993498
149279.4284022551017-77.4284022551017
150207221.771648065451-14.7716480654509
151584.0805525250835-79.0805525250835
152890.2433507449186-82.2433507449186
153079.4225920706794-79.4225920706794
154079.4225920706794-79.4225920706794
15521172159.78828205446-42.788282054463
15633613604.93223626743-243.932236267431
157079.4225920706794-79.4225920706794
158496.9563090324415-92.9563090324415
159151169.908947560457-18.9089475604574
160474483.758684602152-9.75868460215161
161141202.434971956758-61.4349719567582
16210471104.79002397972-57.7900239797229
1632993.2297855380901-64.2297855380901
16418221787.8793966966734.1206033033337

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1747 & 2375.21949247347 & -628.21949247347 \tabularnewline
2 & 1209 & 1710.59813180281 & -501.598131802808 \tabularnewline
3 & 1844 & 1981.38158528918 & -137.381585289185 \tabularnewline
4 & 2683 & 2357.14929035741 & 325.85070964259 \tabularnewline
5 & 1229 & 1569.64929607679 & -340.649296076793 \tabularnewline
6 & 631 & 679.126937299303 & -48.1269372993025 \tabularnewline
7 & 4627 & 4166.29782654404 & 460.702173455957 \tabularnewline
8 & 381 & 384.774421410705 & -3.77442141070456 \tabularnewline
9 & 2063 & 1954.75747352682 & 108.242526473175 \tabularnewline
10 & 1758 & 1869.10663059124 & -111.106630591236 \tabularnewline
11 & 2132 & 2728.66350217486 & -596.663502174855 \tabularnewline
12 & 2146 & 2475.32288487448 & -329.322884874483 \tabularnewline
13 & 1805 & 1621.79426983559 & 183.205730164412 \tabularnewline
14 & 2965 & 3133.64869581904 & -168.648695819042 \tabularnewline
15 & 2098 & 2206.47959996446 & -108.479599964456 \tabularnewline
16 & 4904 & 3802.4713666309 & 1101.5286333691 \tabularnewline
17 & 2242 & 2750.63370363403 & -508.633703634032 \tabularnewline
18 & 3040 & 3115.76453634746 & -75.7645363474625 \tabularnewline
19 & 1438 & 1780.16346784445 & -342.163467844445 \tabularnewline
20 & 2347 & 2580.30323199394 & -233.303231993944 \tabularnewline
21 & 2522 & 2528.17643372483 & -6.17643372483223 \tabularnewline
22 & 2889 & 3467.22048869199 & -578.220488691989 \tabularnewline
23 & 1447 & 1596.35640054983 & -149.35640054983 \tabularnewline
24 & 1717 & 1870.56262740342 & -153.562627403415 \tabularnewline
25 & 3363 & 2555.1114271907 & 807.888572809303 \tabularnewline
26 & 2912 & 2476.09098207794 & 435.909017922065 \tabularnewline
27 & 2828 & 2595.64313567173 & 232.356864328273 \tabularnewline
28 & 1972 & 2522.25013611331 & -550.25013611331 \tabularnewline
29 & 1495 & 1463.07041587978 & 31.929584120223 \tabularnewline
30 & 2841 & 2912.94282994083 & -71.9428299408275 \tabularnewline
31 & 2300 & 2578.26023709206 & -278.260237092058 \tabularnewline
32 & 1909 & 1876.5100776733 & 32.4899223266968 \tabularnewline
33 & 2140 & 2908.74440314467 & -768.744403144675 \tabularnewline
34 & 971 & 1019.89741338997 & -48.8974133899684 \tabularnewline
35 & 3332 & 3357.86610181271 & -25.8661018127086 \tabularnewline
36 & 2764 & 2280.30334730365 & 483.696652696347 \tabularnewline
37 & 3683 & 3542.51696961349 & 140.483030386509 \tabularnewline
38 & 1918 & 2101.76863534387 & -183.76863534387 \tabularnewline
39 & 947 & 1049.56110961428 & -102.561109614284 \tabularnewline
40 & 3472 & 3511.30710169442 & -39.3071016944238 \tabularnewline
41 & 3247 & 2829.64243573305 & 417.357564266953 \tabularnewline
42 & 1692 & 1719.28399138158 & -27.2839913815753 \tabularnewline
43 & 1736 & 1860.11590993148 & -124.115909931483 \tabularnewline
44 & 1790 & 1717.43781201417 & 72.5621879858345 \tabularnewline
45 & 2496 & 1557.22086460305 & 938.779135396945 \tabularnewline
46 & 5501 & 3793.56400749927 & 1707.43599250073 \tabularnewline
47 & 918 & 825.369559864119 & 92.6304401358813 \tabularnewline
48 & 2228 & 2057.9273660982 & 170.072633901795 \tabularnewline
49 & 4051 & 3233.61388109369 & 817.386118906311 \tabularnewline
50 & 2081 & 1766.59575969248 & 314.40424030752 \tabularnewline
51 & 1875 & 2114.24638357307 & -239.246383573073 \tabularnewline
52 & 496 & 372.49755293942 & 123.50244706058 \tabularnewline
53 & 2540 & 3927.78778079605 & -1387.78778079605 \tabularnewline
54 & 744 & 632.381821918323 & 111.618178081677 \tabularnewline
55 & 1161 & 1067.91068551996 & 93.0893144800357 \tabularnewline
56 & 3027 & 2361.38597363927 & 665.614026360731 \tabularnewline
57 & 2527 & 2811.84600976722 & -284.846009767223 \tabularnewline
58 & 3713 & 3369.85053125382 & 343.149468746185 \tabularnewline
59 & 2668 & 3422.33089957894 & -754.330899578939 \tabularnewline
60 & 2175 & 2276.86377040971 & -101.863770409708 \tabularnewline
61 & 3980 & 3524.02360128031 & 455.976398719692 \tabularnewline
62 & 3165 & 2914.24700706702 & 250.752992932979 \tabularnewline
63 & 2954 & 2558.92103490223 & 395.078965097767 \tabularnewline
64 & 2610 & 2384.9226158327 & 225.077384167297 \tabularnewline
65 & 1427 & 1923.86222893552 & -496.862228935522 \tabularnewline
66 & 1646 & 2015.69275017275 & -369.692750172751 \tabularnewline
67 & 1971 & 2160.3671851066 & -189.367185106595 \tabularnewline
68 & 2747 & 2439.69796983073 & 307.302030169267 \tabularnewline
69 & 2309 & 2355.71477413407 & -46.7147741340719 \tabularnewline
70 & 1684 & 1986.62760984094 & -302.62760984094 \tabularnewline
71 & 2537 & 2184.62671329188 & 352.373286708124 \tabularnewline
72 & 893 & 750.43397249131 & 142.56602750869 \tabularnewline
73 & 2195 & 2184.61572367616 & 10.3842763238403 \tabularnewline
74 & 1695 & 1735.3695401267 & -40.3695401266988 \tabularnewline
75 & 2061 & 2112.99838350013 & -51.9983835001291 \tabularnewline
76 & 2340 & 3133.61906627219 & -793.619066272189 \tabularnewline
77 & 2695 & 3003.68455304275 & -308.68455304275 \tabularnewline
78 & 1809 & 2072.98584113797 & -263.985841137966 \tabularnewline
79 & 2290 & 2102.16138271961 & 187.838617280391 \tabularnewline
80 & 1792 & 1771.99048309406 & 20.0095169059441 \tabularnewline
81 & 1678 & 1437.0874217597 & 240.912578240299 \tabularnewline
82 & 4024 & 3891.95332536501 & 132.046674634988 \tabularnewline
83 & 1369 & 1356.33617106806 & 12.6638289319353 \tabularnewline
84 & 2309 & 2646.3604456237 & -337.360445623699 \tabularnewline
85 & 870 & 864.293182226286 & 5.70681777371428 \tabularnewline
86 & 1966 & 1409.13185393784 & 556.868146062162 \tabularnewline
87 & 1459 & 1623.64310200645 & -164.643102006453 \tabularnewline
88 & 3846 & 3519.89150035533 & 326.108499644667 \tabularnewline
89 & 2721 & 3078.50450864957 & -357.504508649567 \tabularnewline
90 & 3086 & 2256.13559099838 & 829.864409001616 \tabularnewline
91 & 2398 & 2379.18649599245 & 18.8135040075455 \tabularnewline
92 & 2210 & 2608.75172005908 & -398.751720059077 \tabularnewline
93 & 1829 & 1658.44575848766 & 170.554241512341 \tabularnewline
94 & 3087 & 2618.27176781213 & 468.728232187869 \tabularnewline
95 & 2559 & 2662.40054377266 & -103.40054377266 \tabularnewline
96 & 1624 & 1692.86513371908 & -68.865133719078 \tabularnewline
97 & 1703 & 2125.03674720465 & -422.036747204651 \tabularnewline
98 & 2109 & 2747.05016433021 & -638.050164330208 \tabularnewline
99 & 4027 & 3649.04838699578 & 377.951613004217 \tabularnewline
100 & 3706 & 3529.16213444824 & 176.837865551759 \tabularnewline
101 & 2715 & 2824.41305665744 & -109.413056657438 \tabularnewline
102 & 2325 & 2686.99516430641 & -361.995164306411 \tabularnewline
103 & 2002 & 2235.56543100114 & -233.565431001142 \tabularnewline
104 & 602 & 462.162480206467 & 139.837519793533 \tabularnewline
105 & 2146 & 1866.92390075823 & 279.076099241774 \tabularnewline
106 & 2328 & 2483.48806721412 & -155.488067214118 \tabularnewline
107 & 2618 & 2391.89687840329 & 226.103121596711 \tabularnewline
108 & 2692 & 2940.84453818137 & -248.844538181368 \tabularnewline
109 & 1222 & 1398.48255264162 & -176.482552641621 \tabularnewline
110 & 3170 & 1875.50923090741 & 1294.49076909259 \tabularnewline
111 & 1870 & 2476.33591519287 & -606.335915192869 \tabularnewline
112 & 2304 & 2791.23596753591 & -487.235967535914 \tabularnewline
113 & 398 & 310.639356954709 & 87.3606430452909 \tabularnewline
114 & 2205 & 2128.85668933983 & 76.1433106601727 \tabularnewline
115 & 530 & 640.547910005665 & -110.547910005665 \tabularnewline
116 & 1596 & 1589.56748514115 & 6.43251485885477 \tabularnewline
117 & 3093 & 3611.3116440597 & -518.311644059701 \tabularnewline
118 & 387 & 283.290656385155 & 103.709343614845 \tabularnewline
119 & 2137 & 2105.9190949789 & 31.0809050211044 \tabularnewline
120 & 492 & 432.571859375799 & 59.4281406242012 \tabularnewline
121 & 3474 & 2882.33703388803 & 591.662966111973 \tabularnewline
122 & 2089 & 2076.53436293124 & 12.4656370687553 \tabularnewline
123 & 1659 & 1711.94308192094 & -52.9430819209419 \tabularnewline
124 & 1685 & 1374.80174133036 & 310.198258669644 \tabularnewline
125 & 568 & 509.903969448285 & 58.0960305517154 \tabularnewline
126 & 2060 & 1832.80595919818 & 227.194040801818 \tabularnewline
127 & 2792 & 3076.79583297555 & -284.795832975546 \tabularnewline
128 & 1395 & 1714.1565962063 & -319.156596206298 \tabularnewline
129 & 3591 & 3379.34184437961 & 211.658155620391 \tabularnewline
130 & 2388 & 2967.1591948079 & -579.159194807904 \tabularnewline
131 & 3334 & 3477.91419979059 & -143.914199790587 \tabularnewline
132 & 1250 & 1625.71206225089 & -375.712062250892 \tabularnewline
133 & 1121 & 1037.79812602007 & 83.2018739799287 \tabularnewline
134 & 2880 & 3476.0264527456 & -596.0264527456 \tabularnewline
135 & 4142 & 3680.46082028784 & 461.539179712165 \tabularnewline
136 & 1759 & 1415.96932562019 & 343.030674379806 \tabularnewline
137 & 4139 & 3440.30477126348 & 698.695228736515 \tabularnewline
138 & 1831 & 1554.7429802806 & 276.257019719404 \tabularnewline
139 & 1787 & 2247.80804769822 & -460.80804769822 \tabularnewline
140 & 2536 & 2580.461030425 & -44.4610304250028 \tabularnewline
141 & 1816 & 1979.06102704175 & -163.061027041754 \tabularnewline
142 & 3907 & 3142.27272595166 & 764.727274048342 \tabularnewline
143 & 2307 & 2426.12919009994 & -119.129190099936 \tabularnewline
144 & 2035 & 1521.92337013852 & 513.076629861478 \tabularnewline
145 & 2986 & 2994.89606461116 & -8.89606461116402 \tabularnewline
146 & 1915 & 1917.80659451812 & -2.80659451812199 \tabularnewline
147 & 2648 & 2404.86284644599 & 243.137153554008 \tabularnewline
148 & 2633 & 3034.5844939935 & -401.584493993498 \tabularnewline
149 & 2 & 79.4284022551017 & -77.4284022551017 \tabularnewline
150 & 207 & 221.771648065451 & -14.7716480654509 \tabularnewline
151 & 5 & 84.0805525250835 & -79.0805525250835 \tabularnewline
152 & 8 & 90.2433507449186 & -82.2433507449186 \tabularnewline
153 & 0 & 79.4225920706794 & -79.4225920706794 \tabularnewline
154 & 0 & 79.4225920706794 & -79.4225920706794 \tabularnewline
155 & 2117 & 2159.78828205446 & -42.788282054463 \tabularnewline
156 & 3361 & 3604.93223626743 & -243.932236267431 \tabularnewline
157 & 0 & 79.4225920706794 & -79.4225920706794 \tabularnewline
158 & 4 & 96.9563090324415 & -92.9563090324415 \tabularnewline
159 & 151 & 169.908947560457 & -18.9089475604574 \tabularnewline
160 & 474 & 483.758684602152 & -9.75868460215161 \tabularnewline
161 & 141 & 202.434971956758 & -61.4349719567582 \tabularnewline
162 & 1047 & 1104.79002397972 & -57.7900239797229 \tabularnewline
163 & 29 & 93.2297855380901 & -64.2297855380901 \tabularnewline
164 & 1822 & 1787.87939669667 & 34.1206033033337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157110&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]1747[/C][C]2375.21949247347[/C][C]-628.21949247347[/C][/ROW]
[ROW][C]2[/C][C]1209[/C][C]1710.59813180281[/C][C]-501.598131802808[/C][/ROW]
[ROW][C]3[/C][C]1844[/C][C]1981.38158528918[/C][C]-137.381585289185[/C][/ROW]
[ROW][C]4[/C][C]2683[/C][C]2357.14929035741[/C][C]325.85070964259[/C][/ROW]
[ROW][C]5[/C][C]1229[/C][C]1569.64929607679[/C][C]-340.649296076793[/C][/ROW]
[ROW][C]6[/C][C]631[/C][C]679.126937299303[/C][C]-48.1269372993025[/C][/ROW]
[ROW][C]7[/C][C]4627[/C][C]4166.29782654404[/C][C]460.702173455957[/C][/ROW]
[ROW][C]8[/C][C]381[/C][C]384.774421410705[/C][C]-3.77442141070456[/C][/ROW]
[ROW][C]9[/C][C]2063[/C][C]1954.75747352682[/C][C]108.242526473175[/C][/ROW]
[ROW][C]10[/C][C]1758[/C][C]1869.10663059124[/C][C]-111.106630591236[/C][/ROW]
[ROW][C]11[/C][C]2132[/C][C]2728.66350217486[/C][C]-596.663502174855[/C][/ROW]
[ROW][C]12[/C][C]2146[/C][C]2475.32288487448[/C][C]-329.322884874483[/C][/ROW]
[ROW][C]13[/C][C]1805[/C][C]1621.79426983559[/C][C]183.205730164412[/C][/ROW]
[ROW][C]14[/C][C]2965[/C][C]3133.64869581904[/C][C]-168.648695819042[/C][/ROW]
[ROW][C]15[/C][C]2098[/C][C]2206.47959996446[/C][C]-108.479599964456[/C][/ROW]
[ROW][C]16[/C][C]4904[/C][C]3802.4713666309[/C][C]1101.5286333691[/C][/ROW]
[ROW][C]17[/C][C]2242[/C][C]2750.63370363403[/C][C]-508.633703634032[/C][/ROW]
[ROW][C]18[/C][C]3040[/C][C]3115.76453634746[/C][C]-75.7645363474625[/C][/ROW]
[ROW][C]19[/C][C]1438[/C][C]1780.16346784445[/C][C]-342.163467844445[/C][/ROW]
[ROW][C]20[/C][C]2347[/C][C]2580.30323199394[/C][C]-233.303231993944[/C][/ROW]
[ROW][C]21[/C][C]2522[/C][C]2528.17643372483[/C][C]-6.17643372483223[/C][/ROW]
[ROW][C]22[/C][C]2889[/C][C]3467.22048869199[/C][C]-578.220488691989[/C][/ROW]
[ROW][C]23[/C][C]1447[/C][C]1596.35640054983[/C][C]-149.35640054983[/C][/ROW]
[ROW][C]24[/C][C]1717[/C][C]1870.56262740342[/C][C]-153.562627403415[/C][/ROW]
[ROW][C]25[/C][C]3363[/C][C]2555.1114271907[/C][C]807.888572809303[/C][/ROW]
[ROW][C]26[/C][C]2912[/C][C]2476.09098207794[/C][C]435.909017922065[/C][/ROW]
[ROW][C]27[/C][C]2828[/C][C]2595.64313567173[/C][C]232.356864328273[/C][/ROW]
[ROW][C]28[/C][C]1972[/C][C]2522.25013611331[/C][C]-550.25013611331[/C][/ROW]
[ROW][C]29[/C][C]1495[/C][C]1463.07041587978[/C][C]31.929584120223[/C][/ROW]
[ROW][C]30[/C][C]2841[/C][C]2912.94282994083[/C][C]-71.9428299408275[/C][/ROW]
[ROW][C]31[/C][C]2300[/C][C]2578.26023709206[/C][C]-278.260237092058[/C][/ROW]
[ROW][C]32[/C][C]1909[/C][C]1876.5100776733[/C][C]32.4899223266968[/C][/ROW]
[ROW][C]33[/C][C]2140[/C][C]2908.74440314467[/C][C]-768.744403144675[/C][/ROW]
[ROW][C]34[/C][C]971[/C][C]1019.89741338997[/C][C]-48.8974133899684[/C][/ROW]
[ROW][C]35[/C][C]3332[/C][C]3357.86610181271[/C][C]-25.8661018127086[/C][/ROW]
[ROW][C]36[/C][C]2764[/C][C]2280.30334730365[/C][C]483.696652696347[/C][/ROW]
[ROW][C]37[/C][C]3683[/C][C]3542.51696961349[/C][C]140.483030386509[/C][/ROW]
[ROW][C]38[/C][C]1918[/C][C]2101.76863534387[/C][C]-183.76863534387[/C][/ROW]
[ROW][C]39[/C][C]947[/C][C]1049.56110961428[/C][C]-102.561109614284[/C][/ROW]
[ROW][C]40[/C][C]3472[/C][C]3511.30710169442[/C][C]-39.3071016944238[/C][/ROW]
[ROW][C]41[/C][C]3247[/C][C]2829.64243573305[/C][C]417.357564266953[/C][/ROW]
[ROW][C]42[/C][C]1692[/C][C]1719.28399138158[/C][C]-27.2839913815753[/C][/ROW]
[ROW][C]43[/C][C]1736[/C][C]1860.11590993148[/C][C]-124.115909931483[/C][/ROW]
[ROW][C]44[/C][C]1790[/C][C]1717.43781201417[/C][C]72.5621879858345[/C][/ROW]
[ROW][C]45[/C][C]2496[/C][C]1557.22086460305[/C][C]938.779135396945[/C][/ROW]
[ROW][C]46[/C][C]5501[/C][C]3793.56400749927[/C][C]1707.43599250073[/C][/ROW]
[ROW][C]47[/C][C]918[/C][C]825.369559864119[/C][C]92.6304401358813[/C][/ROW]
[ROW][C]48[/C][C]2228[/C][C]2057.9273660982[/C][C]170.072633901795[/C][/ROW]
[ROW][C]49[/C][C]4051[/C][C]3233.61388109369[/C][C]817.386118906311[/C][/ROW]
[ROW][C]50[/C][C]2081[/C][C]1766.59575969248[/C][C]314.40424030752[/C][/ROW]
[ROW][C]51[/C][C]1875[/C][C]2114.24638357307[/C][C]-239.246383573073[/C][/ROW]
[ROW][C]52[/C][C]496[/C][C]372.49755293942[/C][C]123.50244706058[/C][/ROW]
[ROW][C]53[/C][C]2540[/C][C]3927.78778079605[/C][C]-1387.78778079605[/C][/ROW]
[ROW][C]54[/C][C]744[/C][C]632.381821918323[/C][C]111.618178081677[/C][/ROW]
[ROW][C]55[/C][C]1161[/C][C]1067.91068551996[/C][C]93.0893144800357[/C][/ROW]
[ROW][C]56[/C][C]3027[/C][C]2361.38597363927[/C][C]665.614026360731[/C][/ROW]
[ROW][C]57[/C][C]2527[/C][C]2811.84600976722[/C][C]-284.846009767223[/C][/ROW]
[ROW][C]58[/C][C]3713[/C][C]3369.85053125382[/C][C]343.149468746185[/C][/ROW]
[ROW][C]59[/C][C]2668[/C][C]3422.33089957894[/C][C]-754.330899578939[/C][/ROW]
[ROW][C]60[/C][C]2175[/C][C]2276.86377040971[/C][C]-101.863770409708[/C][/ROW]
[ROW][C]61[/C][C]3980[/C][C]3524.02360128031[/C][C]455.976398719692[/C][/ROW]
[ROW][C]62[/C][C]3165[/C][C]2914.24700706702[/C][C]250.752992932979[/C][/ROW]
[ROW][C]63[/C][C]2954[/C][C]2558.92103490223[/C][C]395.078965097767[/C][/ROW]
[ROW][C]64[/C][C]2610[/C][C]2384.9226158327[/C][C]225.077384167297[/C][/ROW]
[ROW][C]65[/C][C]1427[/C][C]1923.86222893552[/C][C]-496.862228935522[/C][/ROW]
[ROW][C]66[/C][C]1646[/C][C]2015.69275017275[/C][C]-369.692750172751[/C][/ROW]
[ROW][C]67[/C][C]1971[/C][C]2160.3671851066[/C][C]-189.367185106595[/C][/ROW]
[ROW][C]68[/C][C]2747[/C][C]2439.69796983073[/C][C]307.302030169267[/C][/ROW]
[ROW][C]69[/C][C]2309[/C][C]2355.71477413407[/C][C]-46.7147741340719[/C][/ROW]
[ROW][C]70[/C][C]1684[/C][C]1986.62760984094[/C][C]-302.62760984094[/C][/ROW]
[ROW][C]71[/C][C]2537[/C][C]2184.62671329188[/C][C]352.373286708124[/C][/ROW]
[ROW][C]72[/C][C]893[/C][C]750.43397249131[/C][C]142.56602750869[/C][/ROW]
[ROW][C]73[/C][C]2195[/C][C]2184.61572367616[/C][C]10.3842763238403[/C][/ROW]
[ROW][C]74[/C][C]1695[/C][C]1735.3695401267[/C][C]-40.3695401266988[/C][/ROW]
[ROW][C]75[/C][C]2061[/C][C]2112.99838350013[/C][C]-51.9983835001291[/C][/ROW]
[ROW][C]76[/C][C]2340[/C][C]3133.61906627219[/C][C]-793.619066272189[/C][/ROW]
[ROW][C]77[/C][C]2695[/C][C]3003.68455304275[/C][C]-308.68455304275[/C][/ROW]
[ROW][C]78[/C][C]1809[/C][C]2072.98584113797[/C][C]-263.985841137966[/C][/ROW]
[ROW][C]79[/C][C]2290[/C][C]2102.16138271961[/C][C]187.838617280391[/C][/ROW]
[ROW][C]80[/C][C]1792[/C][C]1771.99048309406[/C][C]20.0095169059441[/C][/ROW]
[ROW][C]81[/C][C]1678[/C][C]1437.0874217597[/C][C]240.912578240299[/C][/ROW]
[ROW][C]82[/C][C]4024[/C][C]3891.95332536501[/C][C]132.046674634988[/C][/ROW]
[ROW][C]83[/C][C]1369[/C][C]1356.33617106806[/C][C]12.6638289319353[/C][/ROW]
[ROW][C]84[/C][C]2309[/C][C]2646.3604456237[/C][C]-337.360445623699[/C][/ROW]
[ROW][C]85[/C][C]870[/C][C]864.293182226286[/C][C]5.70681777371428[/C][/ROW]
[ROW][C]86[/C][C]1966[/C][C]1409.13185393784[/C][C]556.868146062162[/C][/ROW]
[ROW][C]87[/C][C]1459[/C][C]1623.64310200645[/C][C]-164.643102006453[/C][/ROW]
[ROW][C]88[/C][C]3846[/C][C]3519.89150035533[/C][C]326.108499644667[/C][/ROW]
[ROW][C]89[/C][C]2721[/C][C]3078.50450864957[/C][C]-357.504508649567[/C][/ROW]
[ROW][C]90[/C][C]3086[/C][C]2256.13559099838[/C][C]829.864409001616[/C][/ROW]
[ROW][C]91[/C][C]2398[/C][C]2379.18649599245[/C][C]18.8135040075455[/C][/ROW]
[ROW][C]92[/C][C]2210[/C][C]2608.75172005908[/C][C]-398.751720059077[/C][/ROW]
[ROW][C]93[/C][C]1829[/C][C]1658.44575848766[/C][C]170.554241512341[/C][/ROW]
[ROW][C]94[/C][C]3087[/C][C]2618.27176781213[/C][C]468.728232187869[/C][/ROW]
[ROW][C]95[/C][C]2559[/C][C]2662.40054377266[/C][C]-103.40054377266[/C][/ROW]
[ROW][C]96[/C][C]1624[/C][C]1692.86513371908[/C][C]-68.865133719078[/C][/ROW]
[ROW][C]97[/C][C]1703[/C][C]2125.03674720465[/C][C]-422.036747204651[/C][/ROW]
[ROW][C]98[/C][C]2109[/C][C]2747.05016433021[/C][C]-638.050164330208[/C][/ROW]
[ROW][C]99[/C][C]4027[/C][C]3649.04838699578[/C][C]377.951613004217[/C][/ROW]
[ROW][C]100[/C][C]3706[/C][C]3529.16213444824[/C][C]176.837865551759[/C][/ROW]
[ROW][C]101[/C][C]2715[/C][C]2824.41305665744[/C][C]-109.413056657438[/C][/ROW]
[ROW][C]102[/C][C]2325[/C][C]2686.99516430641[/C][C]-361.995164306411[/C][/ROW]
[ROW][C]103[/C][C]2002[/C][C]2235.56543100114[/C][C]-233.565431001142[/C][/ROW]
[ROW][C]104[/C][C]602[/C][C]462.162480206467[/C][C]139.837519793533[/C][/ROW]
[ROW][C]105[/C][C]2146[/C][C]1866.92390075823[/C][C]279.076099241774[/C][/ROW]
[ROW][C]106[/C][C]2328[/C][C]2483.48806721412[/C][C]-155.488067214118[/C][/ROW]
[ROW][C]107[/C][C]2618[/C][C]2391.89687840329[/C][C]226.103121596711[/C][/ROW]
[ROW][C]108[/C][C]2692[/C][C]2940.84453818137[/C][C]-248.844538181368[/C][/ROW]
[ROW][C]109[/C][C]1222[/C][C]1398.48255264162[/C][C]-176.482552641621[/C][/ROW]
[ROW][C]110[/C][C]3170[/C][C]1875.50923090741[/C][C]1294.49076909259[/C][/ROW]
[ROW][C]111[/C][C]1870[/C][C]2476.33591519287[/C][C]-606.335915192869[/C][/ROW]
[ROW][C]112[/C][C]2304[/C][C]2791.23596753591[/C][C]-487.235967535914[/C][/ROW]
[ROW][C]113[/C][C]398[/C][C]310.639356954709[/C][C]87.3606430452909[/C][/ROW]
[ROW][C]114[/C][C]2205[/C][C]2128.85668933983[/C][C]76.1433106601727[/C][/ROW]
[ROW][C]115[/C][C]530[/C][C]640.547910005665[/C][C]-110.547910005665[/C][/ROW]
[ROW][C]116[/C][C]1596[/C][C]1589.56748514115[/C][C]6.43251485885477[/C][/ROW]
[ROW][C]117[/C][C]3093[/C][C]3611.3116440597[/C][C]-518.311644059701[/C][/ROW]
[ROW][C]118[/C][C]387[/C][C]283.290656385155[/C][C]103.709343614845[/C][/ROW]
[ROW][C]119[/C][C]2137[/C][C]2105.9190949789[/C][C]31.0809050211044[/C][/ROW]
[ROW][C]120[/C][C]492[/C][C]432.571859375799[/C][C]59.4281406242012[/C][/ROW]
[ROW][C]121[/C][C]3474[/C][C]2882.33703388803[/C][C]591.662966111973[/C][/ROW]
[ROW][C]122[/C][C]2089[/C][C]2076.53436293124[/C][C]12.4656370687553[/C][/ROW]
[ROW][C]123[/C][C]1659[/C][C]1711.94308192094[/C][C]-52.9430819209419[/C][/ROW]
[ROW][C]124[/C][C]1685[/C][C]1374.80174133036[/C][C]310.198258669644[/C][/ROW]
[ROW][C]125[/C][C]568[/C][C]509.903969448285[/C][C]58.0960305517154[/C][/ROW]
[ROW][C]126[/C][C]2060[/C][C]1832.80595919818[/C][C]227.194040801818[/C][/ROW]
[ROW][C]127[/C][C]2792[/C][C]3076.79583297555[/C][C]-284.795832975546[/C][/ROW]
[ROW][C]128[/C][C]1395[/C][C]1714.1565962063[/C][C]-319.156596206298[/C][/ROW]
[ROW][C]129[/C][C]3591[/C][C]3379.34184437961[/C][C]211.658155620391[/C][/ROW]
[ROW][C]130[/C][C]2388[/C][C]2967.1591948079[/C][C]-579.159194807904[/C][/ROW]
[ROW][C]131[/C][C]3334[/C][C]3477.91419979059[/C][C]-143.914199790587[/C][/ROW]
[ROW][C]132[/C][C]1250[/C][C]1625.71206225089[/C][C]-375.712062250892[/C][/ROW]
[ROW][C]133[/C][C]1121[/C][C]1037.79812602007[/C][C]83.2018739799287[/C][/ROW]
[ROW][C]134[/C][C]2880[/C][C]3476.0264527456[/C][C]-596.0264527456[/C][/ROW]
[ROW][C]135[/C][C]4142[/C][C]3680.46082028784[/C][C]461.539179712165[/C][/ROW]
[ROW][C]136[/C][C]1759[/C][C]1415.96932562019[/C][C]343.030674379806[/C][/ROW]
[ROW][C]137[/C][C]4139[/C][C]3440.30477126348[/C][C]698.695228736515[/C][/ROW]
[ROW][C]138[/C][C]1831[/C][C]1554.7429802806[/C][C]276.257019719404[/C][/ROW]
[ROW][C]139[/C][C]1787[/C][C]2247.80804769822[/C][C]-460.80804769822[/C][/ROW]
[ROW][C]140[/C][C]2536[/C][C]2580.461030425[/C][C]-44.4610304250028[/C][/ROW]
[ROW][C]141[/C][C]1816[/C][C]1979.06102704175[/C][C]-163.061027041754[/C][/ROW]
[ROW][C]142[/C][C]3907[/C][C]3142.27272595166[/C][C]764.727274048342[/C][/ROW]
[ROW][C]143[/C][C]2307[/C][C]2426.12919009994[/C][C]-119.129190099936[/C][/ROW]
[ROW][C]144[/C][C]2035[/C][C]1521.92337013852[/C][C]513.076629861478[/C][/ROW]
[ROW][C]145[/C][C]2986[/C][C]2994.89606461116[/C][C]-8.89606461116402[/C][/ROW]
[ROW][C]146[/C][C]1915[/C][C]1917.80659451812[/C][C]-2.80659451812199[/C][/ROW]
[ROW][C]147[/C][C]2648[/C][C]2404.86284644599[/C][C]243.137153554008[/C][/ROW]
[ROW][C]148[/C][C]2633[/C][C]3034.5844939935[/C][C]-401.584493993498[/C][/ROW]
[ROW][C]149[/C][C]2[/C][C]79.4284022551017[/C][C]-77.4284022551017[/C][/ROW]
[ROW][C]150[/C][C]207[/C][C]221.771648065451[/C][C]-14.7716480654509[/C][/ROW]
[ROW][C]151[/C][C]5[/C][C]84.0805525250835[/C][C]-79.0805525250835[/C][/ROW]
[ROW][C]152[/C][C]8[/C][C]90.2433507449186[/C][C]-82.2433507449186[/C][/ROW]
[ROW][C]153[/C][C]0[/C][C]79.4225920706794[/C][C]-79.4225920706794[/C][/ROW]
[ROW][C]154[/C][C]0[/C][C]79.4225920706794[/C][C]-79.4225920706794[/C][/ROW]
[ROW][C]155[/C][C]2117[/C][C]2159.78828205446[/C][C]-42.788282054463[/C][/ROW]
[ROW][C]156[/C][C]3361[/C][C]3604.93223626743[/C][C]-243.932236267431[/C][/ROW]
[ROW][C]157[/C][C]0[/C][C]79.4225920706794[/C][C]-79.4225920706794[/C][/ROW]
[ROW][C]158[/C][C]4[/C][C]96.9563090324415[/C][C]-92.9563090324415[/C][/ROW]
[ROW][C]159[/C][C]151[/C][C]169.908947560457[/C][C]-18.9089475604574[/C][/ROW]
[ROW][C]160[/C][C]474[/C][C]483.758684602152[/C][C]-9.75868460215161[/C][/ROW]
[ROW][C]161[/C][C]141[/C][C]202.434971956758[/C][C]-61.4349719567582[/C][/ROW]
[ROW][C]162[/C][C]1047[/C][C]1104.79002397972[/C][C]-57.7900239797229[/C][/ROW]
[ROW][C]163[/C][C]29[/C][C]93.2297855380901[/C][C]-64.2297855380901[/C][/ROW]
[ROW][C]164[/C][C]1822[/C][C]1787.87939669667[/C][C]34.1206033033337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157110&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157110&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
117472375.21949247347-628.21949247347
212091710.59813180281-501.598131802808
318441981.38158528918-137.381585289185
426832357.14929035741325.85070964259
512291569.64929607679-340.649296076793
6631679.126937299303-48.1269372993025
746274166.29782654404460.702173455957
8381384.774421410705-3.77442141070456
920631954.75747352682108.242526473175
1017581869.10663059124-111.106630591236
1121322728.66350217486-596.663502174855
1221462475.32288487448-329.322884874483
1318051621.79426983559183.205730164412
1429653133.64869581904-168.648695819042
1520982206.47959996446-108.479599964456
1649043802.47136663091101.5286333691
1722422750.63370363403-508.633703634032
1830403115.76453634746-75.7645363474625
1914381780.16346784445-342.163467844445
2023472580.30323199394-233.303231993944
2125222528.17643372483-6.17643372483223
2228893467.22048869199-578.220488691989
2314471596.35640054983-149.35640054983
2417171870.56262740342-153.562627403415
2533632555.1114271907807.888572809303
2629122476.09098207794435.909017922065
2728282595.64313567173232.356864328273
2819722522.25013611331-550.25013611331
2914951463.0704158797831.929584120223
3028412912.94282994083-71.9428299408275
3123002578.26023709206-278.260237092058
3219091876.510077673332.4899223266968
3321402908.74440314467-768.744403144675
349711019.89741338997-48.8974133899684
3533323357.86610181271-25.8661018127086
3627642280.30334730365483.696652696347
3736833542.51696961349140.483030386509
3819182101.76863534387-183.76863534387
399471049.56110961428-102.561109614284
4034723511.30710169442-39.3071016944238
4132472829.64243573305417.357564266953
4216921719.28399138158-27.2839913815753
4317361860.11590993148-124.115909931483
4417901717.4378120141772.5621879858345
4524961557.22086460305938.779135396945
4655013793.564007499271707.43599250073
47918825.36955986411992.6304401358813
4822282057.9273660982170.072633901795
4940513233.61388109369817.386118906311
5020811766.59575969248314.40424030752
5118752114.24638357307-239.246383573073
52496372.49755293942123.50244706058
5325403927.78778079605-1387.78778079605
54744632.381821918323111.618178081677
5511611067.9106855199693.0893144800357
5630272361.38597363927665.614026360731
5725272811.84600976722-284.846009767223
5837133369.85053125382343.149468746185
5926683422.33089957894-754.330899578939
6021752276.86377040971-101.863770409708
6139803524.02360128031455.976398719692
6231652914.24700706702250.752992932979
6329542558.92103490223395.078965097767
6426102384.9226158327225.077384167297
6514271923.86222893552-496.862228935522
6616462015.69275017275-369.692750172751
6719712160.3671851066-189.367185106595
6827472439.69796983073307.302030169267
6923092355.71477413407-46.7147741340719
7016841986.62760984094-302.62760984094
7125372184.62671329188352.373286708124
72893750.43397249131142.56602750869
7321952184.6157236761610.3842763238403
7416951735.3695401267-40.3695401266988
7520612112.99838350013-51.9983835001291
7623403133.61906627219-793.619066272189
7726953003.68455304275-308.68455304275
7818092072.98584113797-263.985841137966
7922902102.16138271961187.838617280391
8017921771.9904830940620.0095169059441
8116781437.0874217597240.912578240299
8240243891.95332536501132.046674634988
8313691356.3361710680612.6638289319353
8423092646.3604456237-337.360445623699
85870864.2931822262865.70681777371428
8619661409.13185393784556.868146062162
8714591623.64310200645-164.643102006453
8838463519.89150035533326.108499644667
8927213078.50450864957-357.504508649567
9030862256.13559099838829.864409001616
9123982379.1864959924518.8135040075455
9222102608.75172005908-398.751720059077
9318291658.44575848766170.554241512341
9430872618.27176781213468.728232187869
9525592662.40054377266-103.40054377266
9616241692.86513371908-68.865133719078
9717032125.03674720465-422.036747204651
9821092747.05016433021-638.050164330208
9940273649.04838699578377.951613004217
10037063529.16213444824176.837865551759
10127152824.41305665744-109.413056657438
10223252686.99516430641-361.995164306411
10320022235.56543100114-233.565431001142
104602462.162480206467139.837519793533
10521461866.92390075823279.076099241774
10623282483.48806721412-155.488067214118
10726182391.89687840329226.103121596711
10826922940.84453818137-248.844538181368
10912221398.48255264162-176.482552641621
11031701875.509230907411294.49076909259
11118702476.33591519287-606.335915192869
11223042791.23596753591-487.235967535914
113398310.63935695470987.3606430452909
11422052128.8566893398376.1433106601727
115530640.547910005665-110.547910005665
11615961589.567485141156.43251485885477
11730933611.3116440597-518.311644059701
118387283.290656385155103.709343614845
11921372105.919094978931.0809050211044
120492432.57185937579959.4281406242012
12134742882.33703388803591.662966111973
12220892076.5343629312412.4656370687553
12316591711.94308192094-52.9430819209419
12416851374.80174133036310.198258669644
125568509.90396944828558.0960305517154
12620601832.80595919818227.194040801818
12727923076.79583297555-284.795832975546
12813951714.1565962063-319.156596206298
12935913379.34184437961211.658155620391
13023882967.1591948079-579.159194807904
13133343477.91419979059-143.914199790587
13212501625.71206225089-375.712062250892
13311211037.7981260200783.2018739799287
13428803476.0264527456-596.0264527456
13541423680.46082028784461.539179712165
13617591415.96932562019343.030674379806
13741393440.30477126348698.695228736515
13818311554.7429802806276.257019719404
13917872247.80804769822-460.80804769822
14025362580.461030425-44.4610304250028
14118161979.06102704175-163.061027041754
14239073142.27272595166764.727274048342
14323072426.12919009994-119.129190099936
14420351521.92337013852513.076629861478
14529862994.89606461116-8.89606461116402
14619151917.80659451812-2.80659451812199
14726482404.86284644599243.137153554008
14826333034.5844939935-401.584493993498
149279.4284022551017-77.4284022551017
150207221.771648065451-14.7716480654509
151584.0805525250835-79.0805525250835
152890.2433507449186-82.2433507449186
153079.4225920706794-79.4225920706794
154079.4225920706794-79.4225920706794
15521172159.78828205446-42.788282054463
15633613604.93223626743-243.932236267431
157079.4225920706794-79.4225920706794
158496.9563090324415-92.9563090324415
159151169.908947560457-18.9089475604574
160474483.758684602152-9.75868460215161
161141202.434971956758-61.4349719567582
16210471104.79002397972-57.7900239797229
1632993.2297855380901-64.2297855380901
16418221787.8793966966734.1206033033337






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.6758069812067280.6483860375865440.324193018793272
100.6289662133532180.7420675732935650.371033786646782
110.6548526339458730.6902947321082540.345147366054127
120.5371065135884220.9257869728231560.462893486411578
130.5140060523781580.9719878952436840.485993947621842
140.4495071587513380.8990143175026770.550492841248662
150.3559443531734250.711888706346850.644055646826575
160.6544695637347630.6910608725304750.345530436265237
170.6268264448227930.7463471103544130.373173555177207
180.6642917860156030.6714164279687940.335708213984397
190.6367105617066650.7265788765866690.363289438293335
200.5703382125062680.8593235749874640.429661787493732
210.5108441488236470.9783117023527070.489155851176353
220.4926973375817590.9853946751635190.507302662418241
230.4230079442413120.8460158884826240.576992055758688
240.3564532762996290.7129065525992580.643546723700371
250.3955558038575450.791111607715090.604444196142455
260.3407933119825080.6815866239650160.659206688017492
270.2817685819067660.5635371638135330.718231418093234
280.3394311532559740.6788623065119470.660568846744026
290.2985568322789920.5971136645579830.701443167721008
300.2560361094103120.5120722188206230.743963890589688
310.2180154989237250.4360309978474510.781984501076275
320.2122142237843550.4244284475687090.787785776215645
330.3214716395050040.6429432790100070.678528360494996
340.279172672353240.5583453447064790.72082732764676
350.2397638952624040.4795277905248090.760236104737596
360.4010849611825630.8021699223651260.598915038817437
370.3608500589633010.7217001179266010.639149941036699
380.3217328122213150.643465624442630.678267187778685
390.2775205877224470.5550411754448930.722479412277554
400.3041408366952520.6082816733905030.695859163304748
410.3319089903626760.6638179807253520.668091009637324
420.2859748784603070.5719497569206140.714025121539693
430.2465523369448660.4931046738897330.753447663055134
440.2159614905042260.4319229810084520.784038509495774
450.415522557410450.8310451148208990.58447744258955
460.941267745457010.1174645090859790.0587322545429896
470.9263319813872390.1473360372255220.0736680186127612
480.9115057532940830.1769884934118350.0884942467059175
490.9537699853247170.09246002935056540.0462300146752827
500.9539435933091270.09211281338174650.0460564066908732
510.9443259390056050.1113481219887890.0556740609943947
520.933899969227990.132200061544020.0661000307720101
530.9993690923551970.001261815289605250.000630907644802627
540.9990550956100070.001889808779986460.000944904389993232
550.9985988406728070.002802318654386150.00140115932719308
560.9989439313003270.002112137399345920.00105606869967296
570.9990371842890830.001925631421834580.000962815710917291
580.9987918632077230.002416273584553820.00120813679227691
590.9996590073210150.0006819853579701820.000340992678985091
600.9994939941300250.001012011739949060.000506005869974532
610.9995176262468090.0009647475063826280.000482373753191314
620.9993660798584770.001267840283046360.000633920141523179
630.9993191495557890.001361700888422460.000680850444211229
640.9990820159932150.001835968013570440.000917984006785218
650.9992612948633150.001477410273369230.000738705136684615
660.9992394520055610.00152109598887750.000760547994438748
670.9989667208490250.002066558301950030.00103327915097501
680.9987792511963530.002441497607294840.00122074880364742
690.9982614074546620.003477185090676070.00173859254533804
700.997996466491850.004007067016298990.00200353350814949
710.9977777642358460.004444471528307160.00222223576415358
720.9969813720755010.006037255848997250.00301862792449863
730.9957409846404530.008518030719093710.00425901535954685
740.994086249111620.01182750177676060.00591375088838029
750.991934438835180.01613112232964030.00806556116482013
760.9969334700695390.006133059860922330.00306652993046116
770.9964267727267090.007146454546581680.00357322727329084
780.9956655584887240.008668883022551780.00433444151127589
790.9943683201653530.01126335966929450.00563167983464726
800.9922211300182980.01555773996340330.00777886998170165
810.9905367694302560.01892646113948750.00946323056974377
820.9876370552266640.02472588954667220.0123629447733361
830.9834485043538570.03310299129228610.0165514956461431
840.9819721535944310.03605569281113840.0180278464055692
850.9761817241521390.04763655169572240.0238182758478612
860.9817606988199240.03647860236015150.0182393011800758
870.9768922956604570.04621540867908580.0231077043395429
880.975203892020440.049592215959120.02479610797956
890.97358556227820.05282887544360020.0264144377218001
900.9908919907955630.01821601840887420.00910800920443712
910.9875919848570440.02481603028591110.0124080151429556
920.986975616192290.02604876761542090.0130243838077104
930.9835284597718060.03294308045638780.0164715402281939
940.9870345271789880.02593094564202480.0129654728210124
950.9827333825775750.03453323484485050.0172666174224253
960.9770178861563260.04596422768734850.0229821138436742
970.9768956886713370.04620862265732630.0231043113286631
980.9844714841182170.03105703176356650.0155285158817833
990.9844785381605510.03104292367889870.0155214618394493
1000.98106897735630.03786204528740080.0189310226437004
1010.9749525645332840.05009487093343110.0250474354667156
1020.9727471663440710.05450566731185750.0272528336559288
1030.9666997487717380.06660050245652340.0333002512282617
1040.9576479706781050.084704058643790.042352029321895
1050.9539310082909310.09213798341813870.0460689917090694
1060.9415728995165740.1168542009668530.0584271004834265
1070.9370410499160610.1259179001678770.0629589500839386
1080.9222429741542320.1555140516915360.077757025845768
1090.9030629515197430.1938740969605140.0969370484802571
1100.9979258705890180.004148258821964070.00207412941098203
1110.9995244170280570.0009511659438858230.000475582971942911
1120.9995863427366960.00082731452660830.00041365726330415
1130.999358129283030.001283741433940170.000641870716970085
1140.9993637176391070.001272564721785360.000636282360892679
1150.9990184856544580.001963028691084630.000981514345542317
1160.9985023296980760.002995340603848010.00149767030192401
1170.9994650867991790.001069826401641190.000534913200820595
1180.999159865981840.001680268036319370.000840134018159685
1190.9987474398301690.002505120339662190.00125256016983109
1200.9981059145820690.003788170835862330.00189408541793117
1210.9990172328206160.001965534358768350.000982767179384173
1220.9984221497062730.003155700587453810.0015778502937269
1230.9974787231200490.005042553759902880.00252127687995144
1240.9970540548566240.005891890286752840.00294594514337642
1250.9956400031713140.008719993657371960.00435999682868598
1260.9939787320507640.01204253589847160.00602126794923578
1270.9942567950140750.01148640997184970.00574320498592486
1280.9952103542793240.009579291441351580.00478964572067579
1290.9928648171023890.01427036579522180.00713518289761088
1300.9959590112152120.008081977569575610.00404098878478781
1310.9961662222410860.007667555517828830.00383377775891442
1320.9981598377265810.00368032454683740.0018401622734187
1330.9969485565319320.006102886936136890.00305144346806845
1340.9964130758119540.007173848376091210.00358692418804561
1350.9948154499562470.01036910008750550.00518455004375275
1360.9956243152130540.008751369573891590.00437568478694579
1370.998185690034470.003628619931060630.00181430996553032
1380.9982355599575460.003528880084907170.00176444004245358
1390.999953814486879.23710262598958e-054.61855131299479e-05
1400.9999178490819210.0001643018361582628.2150918079131e-05
1410.9998286911312620.000342617737475990.000171308868737995
1420.9999353635520470.0001292728959051646.46364479525822e-05
1430.9998340085440950.0003319829118102690.000165991455905134
1440.9999981622417213.67551655718731e-061.83775827859365e-06
1450.9999934492247321.31015505351094e-056.5507752675547e-06
1460.9999916178868251.67642263508239e-058.38211317541194e-06
1470.9999999998222523.55496655662768e-101.77748327831384e-10
1480.9999999989420512.11589742433775e-091.05794871216887e-09
1490.9999999885422382.29155243617077e-081.14577621808539e-08
1500.9999999402479831.19504033051527e-075.97520165257635e-08
1510.9999993751558451.24968831083702e-066.24844155418509e-07
1520.9999939215615881.2156876824526e-056.07843841226302e-06
1530.999946337748260.0001073245034803145.3662251740157e-05
1540.9995748737274990.0008502525450028090.000425126272501404
1550.9965747030025360.006850593994927320.00342529699746366

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.675806981206728 & 0.648386037586544 & 0.324193018793272 \tabularnewline
10 & 0.628966213353218 & 0.742067573293565 & 0.371033786646782 \tabularnewline
11 & 0.654852633945873 & 0.690294732108254 & 0.345147366054127 \tabularnewline
12 & 0.537106513588422 & 0.925786972823156 & 0.462893486411578 \tabularnewline
13 & 0.514006052378158 & 0.971987895243684 & 0.485993947621842 \tabularnewline
14 & 0.449507158751338 & 0.899014317502677 & 0.550492841248662 \tabularnewline
15 & 0.355944353173425 & 0.71188870634685 & 0.644055646826575 \tabularnewline
16 & 0.654469563734763 & 0.691060872530475 & 0.345530436265237 \tabularnewline
17 & 0.626826444822793 & 0.746347110354413 & 0.373173555177207 \tabularnewline
18 & 0.664291786015603 & 0.671416427968794 & 0.335708213984397 \tabularnewline
19 & 0.636710561706665 & 0.726578876586669 & 0.363289438293335 \tabularnewline
20 & 0.570338212506268 & 0.859323574987464 & 0.429661787493732 \tabularnewline
21 & 0.510844148823647 & 0.978311702352707 & 0.489155851176353 \tabularnewline
22 & 0.492697337581759 & 0.985394675163519 & 0.507302662418241 \tabularnewline
23 & 0.423007944241312 & 0.846015888482624 & 0.576992055758688 \tabularnewline
24 & 0.356453276299629 & 0.712906552599258 & 0.643546723700371 \tabularnewline
25 & 0.395555803857545 & 0.79111160771509 & 0.604444196142455 \tabularnewline
26 & 0.340793311982508 & 0.681586623965016 & 0.659206688017492 \tabularnewline
27 & 0.281768581906766 & 0.563537163813533 & 0.718231418093234 \tabularnewline
28 & 0.339431153255974 & 0.678862306511947 & 0.660568846744026 \tabularnewline
29 & 0.298556832278992 & 0.597113664557983 & 0.701443167721008 \tabularnewline
30 & 0.256036109410312 & 0.512072218820623 & 0.743963890589688 \tabularnewline
31 & 0.218015498923725 & 0.436030997847451 & 0.781984501076275 \tabularnewline
32 & 0.212214223784355 & 0.424428447568709 & 0.787785776215645 \tabularnewline
33 & 0.321471639505004 & 0.642943279010007 & 0.678528360494996 \tabularnewline
34 & 0.27917267235324 & 0.558345344706479 & 0.72082732764676 \tabularnewline
35 & 0.239763895262404 & 0.479527790524809 & 0.760236104737596 \tabularnewline
36 & 0.401084961182563 & 0.802169922365126 & 0.598915038817437 \tabularnewline
37 & 0.360850058963301 & 0.721700117926601 & 0.639149941036699 \tabularnewline
38 & 0.321732812221315 & 0.64346562444263 & 0.678267187778685 \tabularnewline
39 & 0.277520587722447 & 0.555041175444893 & 0.722479412277554 \tabularnewline
40 & 0.304140836695252 & 0.608281673390503 & 0.695859163304748 \tabularnewline
41 & 0.331908990362676 & 0.663817980725352 & 0.668091009637324 \tabularnewline
42 & 0.285974878460307 & 0.571949756920614 & 0.714025121539693 \tabularnewline
43 & 0.246552336944866 & 0.493104673889733 & 0.753447663055134 \tabularnewline
44 & 0.215961490504226 & 0.431922981008452 & 0.784038509495774 \tabularnewline
45 & 0.41552255741045 & 0.831045114820899 & 0.58447744258955 \tabularnewline
46 & 0.94126774545701 & 0.117464509085979 & 0.0587322545429896 \tabularnewline
47 & 0.926331981387239 & 0.147336037225522 & 0.0736680186127612 \tabularnewline
48 & 0.911505753294083 & 0.176988493411835 & 0.0884942467059175 \tabularnewline
49 & 0.953769985324717 & 0.0924600293505654 & 0.0462300146752827 \tabularnewline
50 & 0.953943593309127 & 0.0921128133817465 & 0.0460564066908732 \tabularnewline
51 & 0.944325939005605 & 0.111348121988789 & 0.0556740609943947 \tabularnewline
52 & 0.93389996922799 & 0.13220006154402 & 0.0661000307720101 \tabularnewline
53 & 0.999369092355197 & 0.00126181528960525 & 0.000630907644802627 \tabularnewline
54 & 0.999055095610007 & 0.00188980877998646 & 0.000944904389993232 \tabularnewline
55 & 0.998598840672807 & 0.00280231865438615 & 0.00140115932719308 \tabularnewline
56 & 0.998943931300327 & 0.00211213739934592 & 0.00105606869967296 \tabularnewline
57 & 0.999037184289083 & 0.00192563142183458 & 0.000962815710917291 \tabularnewline
58 & 0.998791863207723 & 0.00241627358455382 & 0.00120813679227691 \tabularnewline
59 & 0.999659007321015 & 0.000681985357970182 & 0.000340992678985091 \tabularnewline
60 & 0.999493994130025 & 0.00101201173994906 & 0.000506005869974532 \tabularnewline
61 & 0.999517626246809 & 0.000964747506382628 & 0.000482373753191314 \tabularnewline
62 & 0.999366079858477 & 0.00126784028304636 & 0.000633920141523179 \tabularnewline
63 & 0.999319149555789 & 0.00136170088842246 & 0.000680850444211229 \tabularnewline
64 & 0.999082015993215 & 0.00183596801357044 & 0.000917984006785218 \tabularnewline
65 & 0.999261294863315 & 0.00147741027336923 & 0.000738705136684615 \tabularnewline
66 & 0.999239452005561 & 0.0015210959888775 & 0.000760547994438748 \tabularnewline
67 & 0.998966720849025 & 0.00206655830195003 & 0.00103327915097501 \tabularnewline
68 & 0.998779251196353 & 0.00244149760729484 & 0.00122074880364742 \tabularnewline
69 & 0.998261407454662 & 0.00347718509067607 & 0.00173859254533804 \tabularnewline
70 & 0.99799646649185 & 0.00400706701629899 & 0.00200353350814949 \tabularnewline
71 & 0.997777764235846 & 0.00444447152830716 & 0.00222223576415358 \tabularnewline
72 & 0.996981372075501 & 0.00603725584899725 & 0.00301862792449863 \tabularnewline
73 & 0.995740984640453 & 0.00851803071909371 & 0.00425901535954685 \tabularnewline
74 & 0.99408624911162 & 0.0118275017767606 & 0.00591375088838029 \tabularnewline
75 & 0.99193443883518 & 0.0161311223296403 & 0.00806556116482013 \tabularnewline
76 & 0.996933470069539 & 0.00613305986092233 & 0.00306652993046116 \tabularnewline
77 & 0.996426772726709 & 0.00714645454658168 & 0.00357322727329084 \tabularnewline
78 & 0.995665558488724 & 0.00866888302255178 & 0.00433444151127589 \tabularnewline
79 & 0.994368320165353 & 0.0112633596692945 & 0.00563167983464726 \tabularnewline
80 & 0.992221130018298 & 0.0155577399634033 & 0.00777886998170165 \tabularnewline
81 & 0.990536769430256 & 0.0189264611394875 & 0.00946323056974377 \tabularnewline
82 & 0.987637055226664 & 0.0247258895466722 & 0.0123629447733361 \tabularnewline
83 & 0.983448504353857 & 0.0331029912922861 & 0.0165514956461431 \tabularnewline
84 & 0.981972153594431 & 0.0360556928111384 & 0.0180278464055692 \tabularnewline
85 & 0.976181724152139 & 0.0476365516957224 & 0.0238182758478612 \tabularnewline
86 & 0.981760698819924 & 0.0364786023601515 & 0.0182393011800758 \tabularnewline
87 & 0.976892295660457 & 0.0462154086790858 & 0.0231077043395429 \tabularnewline
88 & 0.97520389202044 & 0.04959221595912 & 0.02479610797956 \tabularnewline
89 & 0.9735855622782 & 0.0528288754436002 & 0.0264144377218001 \tabularnewline
90 & 0.990891990795563 & 0.0182160184088742 & 0.00910800920443712 \tabularnewline
91 & 0.987591984857044 & 0.0248160302859111 & 0.0124080151429556 \tabularnewline
92 & 0.98697561619229 & 0.0260487676154209 & 0.0130243838077104 \tabularnewline
93 & 0.983528459771806 & 0.0329430804563878 & 0.0164715402281939 \tabularnewline
94 & 0.987034527178988 & 0.0259309456420248 & 0.0129654728210124 \tabularnewline
95 & 0.982733382577575 & 0.0345332348448505 & 0.0172666174224253 \tabularnewline
96 & 0.977017886156326 & 0.0459642276873485 & 0.0229821138436742 \tabularnewline
97 & 0.976895688671337 & 0.0462086226573263 & 0.0231043113286631 \tabularnewline
98 & 0.984471484118217 & 0.0310570317635665 & 0.0155285158817833 \tabularnewline
99 & 0.984478538160551 & 0.0310429236788987 & 0.0155214618394493 \tabularnewline
100 & 0.9810689773563 & 0.0378620452874008 & 0.0189310226437004 \tabularnewline
101 & 0.974952564533284 & 0.0500948709334311 & 0.0250474354667156 \tabularnewline
102 & 0.972747166344071 & 0.0545056673118575 & 0.0272528336559288 \tabularnewline
103 & 0.966699748771738 & 0.0666005024565234 & 0.0333002512282617 \tabularnewline
104 & 0.957647970678105 & 0.08470405864379 & 0.042352029321895 \tabularnewline
105 & 0.953931008290931 & 0.0921379834181387 & 0.0460689917090694 \tabularnewline
106 & 0.941572899516574 & 0.116854200966853 & 0.0584271004834265 \tabularnewline
107 & 0.937041049916061 & 0.125917900167877 & 0.0629589500839386 \tabularnewline
108 & 0.922242974154232 & 0.155514051691536 & 0.077757025845768 \tabularnewline
109 & 0.903062951519743 & 0.193874096960514 & 0.0969370484802571 \tabularnewline
110 & 0.997925870589018 & 0.00414825882196407 & 0.00207412941098203 \tabularnewline
111 & 0.999524417028057 & 0.000951165943885823 & 0.000475582971942911 \tabularnewline
112 & 0.999586342736696 & 0.0008273145266083 & 0.00041365726330415 \tabularnewline
113 & 0.99935812928303 & 0.00128374143394017 & 0.000641870716970085 \tabularnewline
114 & 0.999363717639107 & 0.00127256472178536 & 0.000636282360892679 \tabularnewline
115 & 0.999018485654458 & 0.00196302869108463 & 0.000981514345542317 \tabularnewline
116 & 0.998502329698076 & 0.00299534060384801 & 0.00149767030192401 \tabularnewline
117 & 0.999465086799179 & 0.00106982640164119 & 0.000534913200820595 \tabularnewline
118 & 0.99915986598184 & 0.00168026803631937 & 0.000840134018159685 \tabularnewline
119 & 0.998747439830169 & 0.00250512033966219 & 0.00125256016983109 \tabularnewline
120 & 0.998105914582069 & 0.00378817083586233 & 0.00189408541793117 \tabularnewline
121 & 0.999017232820616 & 0.00196553435876835 & 0.000982767179384173 \tabularnewline
122 & 0.998422149706273 & 0.00315570058745381 & 0.0015778502937269 \tabularnewline
123 & 0.997478723120049 & 0.00504255375990288 & 0.00252127687995144 \tabularnewline
124 & 0.997054054856624 & 0.00589189028675284 & 0.00294594514337642 \tabularnewline
125 & 0.995640003171314 & 0.00871999365737196 & 0.00435999682868598 \tabularnewline
126 & 0.993978732050764 & 0.0120425358984716 & 0.00602126794923578 \tabularnewline
127 & 0.994256795014075 & 0.0114864099718497 & 0.00574320498592486 \tabularnewline
128 & 0.995210354279324 & 0.00957929144135158 & 0.00478964572067579 \tabularnewline
129 & 0.992864817102389 & 0.0142703657952218 & 0.00713518289761088 \tabularnewline
130 & 0.995959011215212 & 0.00808197756957561 & 0.00404098878478781 \tabularnewline
131 & 0.996166222241086 & 0.00766755551782883 & 0.00383377775891442 \tabularnewline
132 & 0.998159837726581 & 0.0036803245468374 & 0.0018401622734187 \tabularnewline
133 & 0.996948556531932 & 0.00610288693613689 & 0.00305144346806845 \tabularnewline
134 & 0.996413075811954 & 0.00717384837609121 & 0.00358692418804561 \tabularnewline
135 & 0.994815449956247 & 0.0103691000875055 & 0.00518455004375275 \tabularnewline
136 & 0.995624315213054 & 0.00875136957389159 & 0.00437568478694579 \tabularnewline
137 & 0.99818569003447 & 0.00362861993106063 & 0.00181430996553032 \tabularnewline
138 & 0.998235559957546 & 0.00352888008490717 & 0.00176444004245358 \tabularnewline
139 & 0.99995381448687 & 9.23710262598958e-05 & 4.61855131299479e-05 \tabularnewline
140 & 0.999917849081921 & 0.000164301836158262 & 8.2150918079131e-05 \tabularnewline
141 & 0.999828691131262 & 0.00034261773747599 & 0.000171308868737995 \tabularnewline
142 & 0.999935363552047 & 0.000129272895905164 & 6.46364479525822e-05 \tabularnewline
143 & 0.999834008544095 & 0.000331982911810269 & 0.000165991455905134 \tabularnewline
144 & 0.999998162241721 & 3.67551655718731e-06 & 1.83775827859365e-06 \tabularnewline
145 & 0.999993449224732 & 1.31015505351094e-05 & 6.5507752675547e-06 \tabularnewline
146 & 0.999991617886825 & 1.67642263508239e-05 & 8.38211317541194e-06 \tabularnewline
147 & 0.999999999822252 & 3.55496655662768e-10 & 1.77748327831384e-10 \tabularnewline
148 & 0.999999998942051 & 2.11589742433775e-09 & 1.05794871216887e-09 \tabularnewline
149 & 0.999999988542238 & 2.29155243617077e-08 & 1.14577621808539e-08 \tabularnewline
150 & 0.999999940247983 & 1.19504033051527e-07 & 5.97520165257635e-08 \tabularnewline
151 & 0.999999375155845 & 1.24968831083702e-06 & 6.24844155418509e-07 \tabularnewline
152 & 0.999993921561588 & 1.2156876824526e-05 & 6.07843841226302e-06 \tabularnewline
153 & 0.99994633774826 & 0.000107324503480314 & 5.3662251740157e-05 \tabularnewline
154 & 0.999574873727499 & 0.000850252545002809 & 0.000425126272501404 \tabularnewline
155 & 0.996574703002536 & 0.00685059399492732 & 0.00342529699746366 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157110&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]0.675806981206728[/C][C]0.648386037586544[/C][C]0.324193018793272[/C][/ROW]
[ROW][C]10[/C][C]0.628966213353218[/C][C]0.742067573293565[/C][C]0.371033786646782[/C][/ROW]
[ROW][C]11[/C][C]0.654852633945873[/C][C]0.690294732108254[/C][C]0.345147366054127[/C][/ROW]
[ROW][C]12[/C][C]0.537106513588422[/C][C]0.925786972823156[/C][C]0.462893486411578[/C][/ROW]
[ROW][C]13[/C][C]0.514006052378158[/C][C]0.971987895243684[/C][C]0.485993947621842[/C][/ROW]
[ROW][C]14[/C][C]0.449507158751338[/C][C]0.899014317502677[/C][C]0.550492841248662[/C][/ROW]
[ROW][C]15[/C][C]0.355944353173425[/C][C]0.71188870634685[/C][C]0.644055646826575[/C][/ROW]
[ROW][C]16[/C][C]0.654469563734763[/C][C]0.691060872530475[/C][C]0.345530436265237[/C][/ROW]
[ROW][C]17[/C][C]0.626826444822793[/C][C]0.746347110354413[/C][C]0.373173555177207[/C][/ROW]
[ROW][C]18[/C][C]0.664291786015603[/C][C]0.671416427968794[/C][C]0.335708213984397[/C][/ROW]
[ROW][C]19[/C][C]0.636710561706665[/C][C]0.726578876586669[/C][C]0.363289438293335[/C][/ROW]
[ROW][C]20[/C][C]0.570338212506268[/C][C]0.859323574987464[/C][C]0.429661787493732[/C][/ROW]
[ROW][C]21[/C][C]0.510844148823647[/C][C]0.978311702352707[/C][C]0.489155851176353[/C][/ROW]
[ROW][C]22[/C][C]0.492697337581759[/C][C]0.985394675163519[/C][C]0.507302662418241[/C][/ROW]
[ROW][C]23[/C][C]0.423007944241312[/C][C]0.846015888482624[/C][C]0.576992055758688[/C][/ROW]
[ROW][C]24[/C][C]0.356453276299629[/C][C]0.712906552599258[/C][C]0.643546723700371[/C][/ROW]
[ROW][C]25[/C][C]0.395555803857545[/C][C]0.79111160771509[/C][C]0.604444196142455[/C][/ROW]
[ROW][C]26[/C][C]0.340793311982508[/C][C]0.681586623965016[/C][C]0.659206688017492[/C][/ROW]
[ROW][C]27[/C][C]0.281768581906766[/C][C]0.563537163813533[/C][C]0.718231418093234[/C][/ROW]
[ROW][C]28[/C][C]0.339431153255974[/C][C]0.678862306511947[/C][C]0.660568846744026[/C][/ROW]
[ROW][C]29[/C][C]0.298556832278992[/C][C]0.597113664557983[/C][C]0.701443167721008[/C][/ROW]
[ROW][C]30[/C][C]0.256036109410312[/C][C]0.512072218820623[/C][C]0.743963890589688[/C][/ROW]
[ROW][C]31[/C][C]0.218015498923725[/C][C]0.436030997847451[/C][C]0.781984501076275[/C][/ROW]
[ROW][C]32[/C][C]0.212214223784355[/C][C]0.424428447568709[/C][C]0.787785776215645[/C][/ROW]
[ROW][C]33[/C][C]0.321471639505004[/C][C]0.642943279010007[/C][C]0.678528360494996[/C][/ROW]
[ROW][C]34[/C][C]0.27917267235324[/C][C]0.558345344706479[/C][C]0.72082732764676[/C][/ROW]
[ROW][C]35[/C][C]0.239763895262404[/C][C]0.479527790524809[/C][C]0.760236104737596[/C][/ROW]
[ROW][C]36[/C][C]0.401084961182563[/C][C]0.802169922365126[/C][C]0.598915038817437[/C][/ROW]
[ROW][C]37[/C][C]0.360850058963301[/C][C]0.721700117926601[/C][C]0.639149941036699[/C][/ROW]
[ROW][C]38[/C][C]0.321732812221315[/C][C]0.64346562444263[/C][C]0.678267187778685[/C][/ROW]
[ROW][C]39[/C][C]0.277520587722447[/C][C]0.555041175444893[/C][C]0.722479412277554[/C][/ROW]
[ROW][C]40[/C][C]0.304140836695252[/C][C]0.608281673390503[/C][C]0.695859163304748[/C][/ROW]
[ROW][C]41[/C][C]0.331908990362676[/C][C]0.663817980725352[/C][C]0.668091009637324[/C][/ROW]
[ROW][C]42[/C][C]0.285974878460307[/C][C]0.571949756920614[/C][C]0.714025121539693[/C][/ROW]
[ROW][C]43[/C][C]0.246552336944866[/C][C]0.493104673889733[/C][C]0.753447663055134[/C][/ROW]
[ROW][C]44[/C][C]0.215961490504226[/C][C]0.431922981008452[/C][C]0.784038509495774[/C][/ROW]
[ROW][C]45[/C][C]0.41552255741045[/C][C]0.831045114820899[/C][C]0.58447744258955[/C][/ROW]
[ROW][C]46[/C][C]0.94126774545701[/C][C]0.117464509085979[/C][C]0.0587322545429896[/C][/ROW]
[ROW][C]47[/C][C]0.926331981387239[/C][C]0.147336037225522[/C][C]0.0736680186127612[/C][/ROW]
[ROW][C]48[/C][C]0.911505753294083[/C][C]0.176988493411835[/C][C]0.0884942467059175[/C][/ROW]
[ROW][C]49[/C][C]0.953769985324717[/C][C]0.0924600293505654[/C][C]0.0462300146752827[/C][/ROW]
[ROW][C]50[/C][C]0.953943593309127[/C][C]0.0921128133817465[/C][C]0.0460564066908732[/C][/ROW]
[ROW][C]51[/C][C]0.944325939005605[/C][C]0.111348121988789[/C][C]0.0556740609943947[/C][/ROW]
[ROW][C]52[/C][C]0.93389996922799[/C][C]0.13220006154402[/C][C]0.0661000307720101[/C][/ROW]
[ROW][C]53[/C][C]0.999369092355197[/C][C]0.00126181528960525[/C][C]0.000630907644802627[/C][/ROW]
[ROW][C]54[/C][C]0.999055095610007[/C][C]0.00188980877998646[/C][C]0.000944904389993232[/C][/ROW]
[ROW][C]55[/C][C]0.998598840672807[/C][C]0.00280231865438615[/C][C]0.00140115932719308[/C][/ROW]
[ROW][C]56[/C][C]0.998943931300327[/C][C]0.00211213739934592[/C][C]0.00105606869967296[/C][/ROW]
[ROW][C]57[/C][C]0.999037184289083[/C][C]0.00192563142183458[/C][C]0.000962815710917291[/C][/ROW]
[ROW][C]58[/C][C]0.998791863207723[/C][C]0.00241627358455382[/C][C]0.00120813679227691[/C][/ROW]
[ROW][C]59[/C][C]0.999659007321015[/C][C]0.000681985357970182[/C][C]0.000340992678985091[/C][/ROW]
[ROW][C]60[/C][C]0.999493994130025[/C][C]0.00101201173994906[/C][C]0.000506005869974532[/C][/ROW]
[ROW][C]61[/C][C]0.999517626246809[/C][C]0.000964747506382628[/C][C]0.000482373753191314[/C][/ROW]
[ROW][C]62[/C][C]0.999366079858477[/C][C]0.00126784028304636[/C][C]0.000633920141523179[/C][/ROW]
[ROW][C]63[/C][C]0.999319149555789[/C][C]0.00136170088842246[/C][C]0.000680850444211229[/C][/ROW]
[ROW][C]64[/C][C]0.999082015993215[/C][C]0.00183596801357044[/C][C]0.000917984006785218[/C][/ROW]
[ROW][C]65[/C][C]0.999261294863315[/C][C]0.00147741027336923[/C][C]0.000738705136684615[/C][/ROW]
[ROW][C]66[/C][C]0.999239452005561[/C][C]0.0015210959888775[/C][C]0.000760547994438748[/C][/ROW]
[ROW][C]67[/C][C]0.998966720849025[/C][C]0.00206655830195003[/C][C]0.00103327915097501[/C][/ROW]
[ROW][C]68[/C][C]0.998779251196353[/C][C]0.00244149760729484[/C][C]0.00122074880364742[/C][/ROW]
[ROW][C]69[/C][C]0.998261407454662[/C][C]0.00347718509067607[/C][C]0.00173859254533804[/C][/ROW]
[ROW][C]70[/C][C]0.99799646649185[/C][C]0.00400706701629899[/C][C]0.00200353350814949[/C][/ROW]
[ROW][C]71[/C][C]0.997777764235846[/C][C]0.00444447152830716[/C][C]0.00222223576415358[/C][/ROW]
[ROW][C]72[/C][C]0.996981372075501[/C][C]0.00603725584899725[/C][C]0.00301862792449863[/C][/ROW]
[ROW][C]73[/C][C]0.995740984640453[/C][C]0.00851803071909371[/C][C]0.00425901535954685[/C][/ROW]
[ROW][C]74[/C][C]0.99408624911162[/C][C]0.0118275017767606[/C][C]0.00591375088838029[/C][/ROW]
[ROW][C]75[/C][C]0.99193443883518[/C][C]0.0161311223296403[/C][C]0.00806556116482013[/C][/ROW]
[ROW][C]76[/C][C]0.996933470069539[/C][C]0.00613305986092233[/C][C]0.00306652993046116[/C][/ROW]
[ROW][C]77[/C][C]0.996426772726709[/C][C]0.00714645454658168[/C][C]0.00357322727329084[/C][/ROW]
[ROW][C]78[/C][C]0.995665558488724[/C][C]0.00866888302255178[/C][C]0.00433444151127589[/C][/ROW]
[ROW][C]79[/C][C]0.994368320165353[/C][C]0.0112633596692945[/C][C]0.00563167983464726[/C][/ROW]
[ROW][C]80[/C][C]0.992221130018298[/C][C]0.0155577399634033[/C][C]0.00777886998170165[/C][/ROW]
[ROW][C]81[/C][C]0.990536769430256[/C][C]0.0189264611394875[/C][C]0.00946323056974377[/C][/ROW]
[ROW][C]82[/C][C]0.987637055226664[/C][C]0.0247258895466722[/C][C]0.0123629447733361[/C][/ROW]
[ROW][C]83[/C][C]0.983448504353857[/C][C]0.0331029912922861[/C][C]0.0165514956461431[/C][/ROW]
[ROW][C]84[/C][C]0.981972153594431[/C][C]0.0360556928111384[/C][C]0.0180278464055692[/C][/ROW]
[ROW][C]85[/C][C]0.976181724152139[/C][C]0.0476365516957224[/C][C]0.0238182758478612[/C][/ROW]
[ROW][C]86[/C][C]0.981760698819924[/C][C]0.0364786023601515[/C][C]0.0182393011800758[/C][/ROW]
[ROW][C]87[/C][C]0.976892295660457[/C][C]0.0462154086790858[/C][C]0.0231077043395429[/C][/ROW]
[ROW][C]88[/C][C]0.97520389202044[/C][C]0.04959221595912[/C][C]0.02479610797956[/C][/ROW]
[ROW][C]89[/C][C]0.9735855622782[/C][C]0.0528288754436002[/C][C]0.0264144377218001[/C][/ROW]
[ROW][C]90[/C][C]0.990891990795563[/C][C]0.0182160184088742[/C][C]0.00910800920443712[/C][/ROW]
[ROW][C]91[/C][C]0.987591984857044[/C][C]0.0248160302859111[/C][C]0.0124080151429556[/C][/ROW]
[ROW][C]92[/C][C]0.98697561619229[/C][C]0.0260487676154209[/C][C]0.0130243838077104[/C][/ROW]
[ROW][C]93[/C][C]0.983528459771806[/C][C]0.0329430804563878[/C][C]0.0164715402281939[/C][/ROW]
[ROW][C]94[/C][C]0.987034527178988[/C][C]0.0259309456420248[/C][C]0.0129654728210124[/C][/ROW]
[ROW][C]95[/C][C]0.982733382577575[/C][C]0.0345332348448505[/C][C]0.0172666174224253[/C][/ROW]
[ROW][C]96[/C][C]0.977017886156326[/C][C]0.0459642276873485[/C][C]0.0229821138436742[/C][/ROW]
[ROW][C]97[/C][C]0.976895688671337[/C][C]0.0462086226573263[/C][C]0.0231043113286631[/C][/ROW]
[ROW][C]98[/C][C]0.984471484118217[/C][C]0.0310570317635665[/C][C]0.0155285158817833[/C][/ROW]
[ROW][C]99[/C][C]0.984478538160551[/C][C]0.0310429236788987[/C][C]0.0155214618394493[/C][/ROW]
[ROW][C]100[/C][C]0.9810689773563[/C][C]0.0378620452874008[/C][C]0.0189310226437004[/C][/ROW]
[ROW][C]101[/C][C]0.974952564533284[/C][C]0.0500948709334311[/C][C]0.0250474354667156[/C][/ROW]
[ROW][C]102[/C][C]0.972747166344071[/C][C]0.0545056673118575[/C][C]0.0272528336559288[/C][/ROW]
[ROW][C]103[/C][C]0.966699748771738[/C][C]0.0666005024565234[/C][C]0.0333002512282617[/C][/ROW]
[ROW][C]104[/C][C]0.957647970678105[/C][C]0.08470405864379[/C][C]0.042352029321895[/C][/ROW]
[ROW][C]105[/C][C]0.953931008290931[/C][C]0.0921379834181387[/C][C]0.0460689917090694[/C][/ROW]
[ROW][C]106[/C][C]0.941572899516574[/C][C]0.116854200966853[/C][C]0.0584271004834265[/C][/ROW]
[ROW][C]107[/C][C]0.937041049916061[/C][C]0.125917900167877[/C][C]0.0629589500839386[/C][/ROW]
[ROW][C]108[/C][C]0.922242974154232[/C][C]0.155514051691536[/C][C]0.077757025845768[/C][/ROW]
[ROW][C]109[/C][C]0.903062951519743[/C][C]0.193874096960514[/C][C]0.0969370484802571[/C][/ROW]
[ROW][C]110[/C][C]0.997925870589018[/C][C]0.00414825882196407[/C][C]0.00207412941098203[/C][/ROW]
[ROW][C]111[/C][C]0.999524417028057[/C][C]0.000951165943885823[/C][C]0.000475582971942911[/C][/ROW]
[ROW][C]112[/C][C]0.999586342736696[/C][C]0.0008273145266083[/C][C]0.00041365726330415[/C][/ROW]
[ROW][C]113[/C][C]0.99935812928303[/C][C]0.00128374143394017[/C][C]0.000641870716970085[/C][/ROW]
[ROW][C]114[/C][C]0.999363717639107[/C][C]0.00127256472178536[/C][C]0.000636282360892679[/C][/ROW]
[ROW][C]115[/C][C]0.999018485654458[/C][C]0.00196302869108463[/C][C]0.000981514345542317[/C][/ROW]
[ROW][C]116[/C][C]0.998502329698076[/C][C]0.00299534060384801[/C][C]0.00149767030192401[/C][/ROW]
[ROW][C]117[/C][C]0.999465086799179[/C][C]0.00106982640164119[/C][C]0.000534913200820595[/C][/ROW]
[ROW][C]118[/C][C]0.99915986598184[/C][C]0.00168026803631937[/C][C]0.000840134018159685[/C][/ROW]
[ROW][C]119[/C][C]0.998747439830169[/C][C]0.00250512033966219[/C][C]0.00125256016983109[/C][/ROW]
[ROW][C]120[/C][C]0.998105914582069[/C][C]0.00378817083586233[/C][C]0.00189408541793117[/C][/ROW]
[ROW][C]121[/C][C]0.999017232820616[/C][C]0.00196553435876835[/C][C]0.000982767179384173[/C][/ROW]
[ROW][C]122[/C][C]0.998422149706273[/C][C]0.00315570058745381[/C][C]0.0015778502937269[/C][/ROW]
[ROW][C]123[/C][C]0.997478723120049[/C][C]0.00504255375990288[/C][C]0.00252127687995144[/C][/ROW]
[ROW][C]124[/C][C]0.997054054856624[/C][C]0.00589189028675284[/C][C]0.00294594514337642[/C][/ROW]
[ROW][C]125[/C][C]0.995640003171314[/C][C]0.00871999365737196[/C][C]0.00435999682868598[/C][/ROW]
[ROW][C]126[/C][C]0.993978732050764[/C][C]0.0120425358984716[/C][C]0.00602126794923578[/C][/ROW]
[ROW][C]127[/C][C]0.994256795014075[/C][C]0.0114864099718497[/C][C]0.00574320498592486[/C][/ROW]
[ROW][C]128[/C][C]0.995210354279324[/C][C]0.00957929144135158[/C][C]0.00478964572067579[/C][/ROW]
[ROW][C]129[/C][C]0.992864817102389[/C][C]0.0142703657952218[/C][C]0.00713518289761088[/C][/ROW]
[ROW][C]130[/C][C]0.995959011215212[/C][C]0.00808197756957561[/C][C]0.00404098878478781[/C][/ROW]
[ROW][C]131[/C][C]0.996166222241086[/C][C]0.00766755551782883[/C][C]0.00383377775891442[/C][/ROW]
[ROW][C]132[/C][C]0.998159837726581[/C][C]0.0036803245468374[/C][C]0.0018401622734187[/C][/ROW]
[ROW][C]133[/C][C]0.996948556531932[/C][C]0.00610288693613689[/C][C]0.00305144346806845[/C][/ROW]
[ROW][C]134[/C][C]0.996413075811954[/C][C]0.00717384837609121[/C][C]0.00358692418804561[/C][/ROW]
[ROW][C]135[/C][C]0.994815449956247[/C][C]0.0103691000875055[/C][C]0.00518455004375275[/C][/ROW]
[ROW][C]136[/C][C]0.995624315213054[/C][C]0.00875136957389159[/C][C]0.00437568478694579[/C][/ROW]
[ROW][C]137[/C][C]0.99818569003447[/C][C]0.00362861993106063[/C][C]0.00181430996553032[/C][/ROW]
[ROW][C]138[/C][C]0.998235559957546[/C][C]0.00352888008490717[/C][C]0.00176444004245358[/C][/ROW]
[ROW][C]139[/C][C]0.99995381448687[/C][C]9.23710262598958e-05[/C][C]4.61855131299479e-05[/C][/ROW]
[ROW][C]140[/C][C]0.999917849081921[/C][C]0.000164301836158262[/C][C]8.2150918079131e-05[/C][/ROW]
[ROW][C]141[/C][C]0.999828691131262[/C][C]0.00034261773747599[/C][C]0.000171308868737995[/C][/ROW]
[ROW][C]142[/C][C]0.999935363552047[/C][C]0.000129272895905164[/C][C]6.46364479525822e-05[/C][/ROW]
[ROW][C]143[/C][C]0.999834008544095[/C][C]0.000331982911810269[/C][C]0.000165991455905134[/C][/ROW]
[ROW][C]144[/C][C]0.999998162241721[/C][C]3.67551655718731e-06[/C][C]1.83775827859365e-06[/C][/ROW]
[ROW][C]145[/C][C]0.999993449224732[/C][C]1.31015505351094e-05[/C][C]6.5507752675547e-06[/C][/ROW]
[ROW][C]146[/C][C]0.999991617886825[/C][C]1.67642263508239e-05[/C][C]8.38211317541194e-06[/C][/ROW]
[ROW][C]147[/C][C]0.999999999822252[/C][C]3.55496655662768e-10[/C][C]1.77748327831384e-10[/C][/ROW]
[ROW][C]148[/C][C]0.999999998942051[/C][C]2.11589742433775e-09[/C][C]1.05794871216887e-09[/C][/ROW]
[ROW][C]149[/C][C]0.999999988542238[/C][C]2.29155243617077e-08[/C][C]1.14577621808539e-08[/C][/ROW]
[ROW][C]150[/C][C]0.999999940247983[/C][C]1.19504033051527e-07[/C][C]5.97520165257635e-08[/C][/ROW]
[ROW][C]151[/C][C]0.999999375155845[/C][C]1.24968831083702e-06[/C][C]6.24844155418509e-07[/C][/ROW]
[ROW][C]152[/C][C]0.999993921561588[/C][C]1.2156876824526e-05[/C][C]6.07843841226302e-06[/C][/ROW]
[ROW][C]153[/C][C]0.99994633774826[/C][C]0.000107324503480314[/C][C]5.3662251740157e-05[/C][/ROW]
[ROW][C]154[/C][C]0.999574873727499[/C][C]0.000850252545002809[/C][C]0.000425126272501404[/C][/ROW]
[ROW][C]155[/C][C]0.996574703002536[/C][C]0.00685059399492732[/C][C]0.00342529699746366[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157110&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157110&T=5

As an alternative you can also use a QR Code:  
QR Code


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.6758069812067280.6483860375865440.324193018793272
100.6289662133532180.7420675732935650.371033786646782
110.6548526339458730.6902947321082540.345147366054127
120.5371065135884220.9257869728231560.462893486411578
130.5140060523781580.9719878952436840.485993947621842
140.4495071587513380.8990143175026770.550492841248662
150.3559443531734250.711888706346850.644055646826575
160.6544695637347630.6910608725304750.345530436265237
170.6268264448227930.7463471103544130.373173555177207
180.6642917860156030.6714164279687940.335708213984397
190.6367105617066650.7265788765866690.363289438293335
200.5703382125062680.8593235749874640.429661787493732
210.5108441488236470.9783117023527070.489155851176353
220.4926973375817590.9853946751635190.507302662418241
230.4230079442413120.8460158884826240.576992055758688
240.3564532762996290.7129065525992580.643546723700371
250.3955558038575450.791111607715090.604444196142455
260.3407933119825080.6815866239650160.659206688017492
270.2817685819067660.5635371638135330.718231418093234
280.3394311532559740.6788623065119470.660568846744026
290.2985568322789920.5971136645579830.701443167721008
300.2560361094103120.5120722188206230.743963890589688
310.2180154989237250.4360309978474510.781984501076275
320.2122142237843550.4244284475687090.787785776215645
330.3214716395050040.6429432790100070.678528360494996
340.279172672353240.5583453447064790.72082732764676
350.2397638952624040.4795277905248090.760236104737596
360.4010849611825630.8021699223651260.598915038817437
370.3608500589633010.7217001179266010.639149941036699
380.3217328122213150.643465624442630.678267187778685
390.2775205877224470.5550411754448930.722479412277554
400.3041408366952520.6082816733905030.695859163304748
410.3319089903626760.6638179807253520.668091009637324
420.2859748784603070.5719497569206140.714025121539693
430.2465523369448660.4931046738897330.753447663055134
440.2159614905042260.4319229810084520.784038509495774
450.415522557410450.8310451148208990.58447744258955
460.941267745457010.1174645090859790.0587322545429896
470.9263319813872390.1473360372255220.0736680186127612
480.9115057532940830.1769884934118350.0884942467059175
490.9537699853247170.09246002935056540.0462300146752827
500.9539435933091270.09211281338174650.0460564066908732
510.9443259390056050.1113481219887890.0556740609943947
520.933899969227990.132200061544020.0661000307720101
530.9993690923551970.001261815289605250.000630907644802627
540.9990550956100070.001889808779986460.000944904389993232
550.9985988406728070.002802318654386150.00140115932719308
560.9989439313003270.002112137399345920.00105606869967296
570.9990371842890830.001925631421834580.000962815710917291
580.9987918632077230.002416273584553820.00120813679227691
590.9996590073210150.0006819853579701820.000340992678985091
600.9994939941300250.001012011739949060.000506005869974532
610.9995176262468090.0009647475063826280.000482373753191314
620.9993660798584770.001267840283046360.000633920141523179
630.9993191495557890.001361700888422460.000680850444211229
640.9990820159932150.001835968013570440.000917984006785218
650.9992612948633150.001477410273369230.000738705136684615
660.9992394520055610.00152109598887750.000760547994438748
670.9989667208490250.002066558301950030.00103327915097501
680.9987792511963530.002441497607294840.00122074880364742
690.9982614074546620.003477185090676070.00173859254533804
700.997996466491850.004007067016298990.00200353350814949
710.9977777642358460.004444471528307160.00222223576415358
720.9969813720755010.006037255848997250.00301862792449863
730.9957409846404530.008518030719093710.00425901535954685
740.994086249111620.01182750177676060.00591375088838029
750.991934438835180.01613112232964030.00806556116482013
760.9969334700695390.006133059860922330.00306652993046116
770.9964267727267090.007146454546581680.00357322727329084
780.9956655584887240.008668883022551780.00433444151127589
790.9943683201653530.01126335966929450.00563167983464726
800.9922211300182980.01555773996340330.00777886998170165
810.9905367694302560.01892646113948750.00946323056974377
820.9876370552266640.02472588954667220.0123629447733361
830.9834485043538570.03310299129228610.0165514956461431
840.9819721535944310.03605569281113840.0180278464055692
850.9761817241521390.04763655169572240.0238182758478612
860.9817606988199240.03647860236015150.0182393011800758
870.9768922956604570.04621540867908580.0231077043395429
880.975203892020440.049592215959120.02479610797956
890.97358556227820.05282887544360020.0264144377218001
900.9908919907955630.01821601840887420.00910800920443712
910.9875919848570440.02481603028591110.0124080151429556
920.986975616192290.02604876761542090.0130243838077104
930.9835284597718060.03294308045638780.0164715402281939
940.9870345271789880.02593094564202480.0129654728210124
950.9827333825775750.03453323484485050.0172666174224253
960.9770178861563260.04596422768734850.0229821138436742
970.9768956886713370.04620862265732630.0231043113286631
980.9844714841182170.03105703176356650.0155285158817833
990.9844785381605510.03104292367889870.0155214618394493
1000.98106897735630.03786204528740080.0189310226437004
1010.9749525645332840.05009487093343110.0250474354667156
1020.9727471663440710.05450566731185750.0272528336559288
1030.9666997487717380.06660050245652340.0333002512282617
1040.9576479706781050.084704058643790.042352029321895
1050.9539310082909310.09213798341813870.0460689917090694
1060.9415728995165740.1168542009668530.0584271004834265
1070.9370410499160610.1259179001678770.0629589500839386
1080.9222429741542320.1555140516915360.077757025845768
1090.9030629515197430.1938740969605140.0969370484802571
1100.9979258705890180.004148258821964070.00207412941098203
1110.9995244170280570.0009511659438858230.000475582971942911
1120.9995863427366960.00082731452660830.00041365726330415
1130.999358129283030.001283741433940170.000641870716970085
1140.9993637176391070.001272564721785360.000636282360892679
1150.9990184856544580.001963028691084630.000981514345542317
1160.9985023296980760.002995340603848010.00149767030192401
1170.9994650867991790.001069826401641190.000534913200820595
1180.999159865981840.001680268036319370.000840134018159685
1190.9987474398301690.002505120339662190.00125256016983109
1200.9981059145820690.003788170835862330.00189408541793117
1210.9990172328206160.001965534358768350.000982767179384173
1220.9984221497062730.003155700587453810.0015778502937269
1230.9974787231200490.005042553759902880.00252127687995144
1240.9970540548566240.005891890286752840.00294594514337642
1250.9956400031713140.008719993657371960.00435999682868598
1260.9939787320507640.01204253589847160.00602126794923578
1270.9942567950140750.01148640997184970.00574320498592486
1280.9952103542793240.009579291441351580.00478964572067579
1290.9928648171023890.01427036579522180.00713518289761088
1300.9959590112152120.008081977569575610.00404098878478781
1310.9961662222410860.007667555517828830.00383377775891442
1320.9981598377265810.00368032454683740.0018401622734187
1330.9969485565319320.006102886936136890.00305144346806845
1340.9964130758119540.007173848376091210.00358692418804561
1350.9948154499562470.01036910008750550.00518455004375275
1360.9956243152130540.008751369573891590.00437568478694579
1370.998185690034470.003628619931060630.00181430996553032
1380.9982355599575460.003528880084907170.00176444004245358
1390.999953814486879.23710262598958e-054.61855131299479e-05
1400.9999178490819210.0001643018361582628.2150918079131e-05
1410.9998286911312620.000342617737475990.000171308868737995
1420.9999353635520470.0001292728959051646.46364479525822e-05
1430.9998340085440950.0003319829118102690.000165991455905134
1440.9999981622417213.67551655718731e-061.83775827859365e-06
1450.9999934492247321.31015505351094e-056.5507752675547e-06
1460.9999916178868251.67642263508239e-058.38211317541194e-06
1470.9999999998222523.55496655662768e-101.77748327831384e-10
1480.9999999989420512.11589742433775e-091.05794871216887e-09
1490.9999999885422382.29155243617077e-081.14577621808539e-08
1500.9999999402479831.19504033051527e-075.97520165257635e-08
1510.9999993751558451.24968831083702e-066.24844155418509e-07
1520.9999939215615881.2156876824526e-056.07843841226302e-06
1530.999946337748260.0001073245034803145.3662251740157e-05
1540.9995748737274990.0008502525450028090.000425126272501404
1550.9965747030025360.006850593994927320.00342529699746366






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level660.448979591836735NOK
5% type I error level930.63265306122449NOK
10% type I error level1010.687074829931973NOK

\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 & 66 & 0.448979591836735 & NOK \tabularnewline
5% type I error level & 93 & 0.63265306122449 & NOK \tabularnewline
10% type I error level & 101 & 0.687074829931973 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157110&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]66[/C][C]0.448979591836735[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]93[/C][C]0.63265306122449[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]101[/C][C]0.687074829931973[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157110&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157110&T=6

As an alternative you can also use a QR Code:  
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 level660.448979591836735NOK
5% type I error level930.63265306122449NOK
10% type I error level1010.687074829931973NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 2 ; 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')
}