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R Software Module

rwasp_multipleregression.wasp

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Multiple Regression

Date of computation

Sun, 13 Dec 2015 13:34:37 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/13/t1450013799hn1upnfrkexongz.htm/, Retrieved Thu, 16 May 2024 11:53:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286176, Retrieved Thu, 16 May 2024 11:53:38 +0000

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Estimated Impact

101

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-     [Multiple Regression] [] [2015-11-25 14:21:14] [32b17a345b130fdf5cc88718ed94a974]
- RMPD    [Multiple Regression] [Hurricanes ] [2015-12-13 13:34:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286176&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286176&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286176&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Multiple Linear Regression - Estimated Regression Equation
(1-B12)Temperatuur[t] = + 0.305616 -0.00384852`(1-B12)Orkanen`[t] + 0.169909`(1-B12)Temperatuur(t-1)`[t] + 0.0491005`(1-B12)Temperatuur(t-2)`[t] -0.0245547`(1-B12)Temperatuur(t-3)`[t] + 0.00863072`(1-B12)Temperatuur(t-4)`[t] + 0.104247`(1-B12)Temperatuur(t-5)`[t] + 0.00753965`(1-B12)Temperatuur(t-6)`[t] -0.113292`(1-B12)Temperatuur(t-7)`[t] + 0.0749275`(1-B12)Temperatuur(t-8)`[t] -0.0509971`(1-B12)Temperatuur(t-9)`[t] + 0.0834595`(1-B12)Temperatuur(t-10)`[t] -1.02015`(1-B12)Temperatuur(t-1s)`[t] -1.1736`(1-B12)Temperatuur(t-2s)`[t] -1.2048`(1-B12)Temperatuur(t-3s)`[t] -0.995677`(1-B12)Temperatuur(t-4s)`[t] -1.07152`(1-B12)Temperatuur(t-5s)`[t] -1.18596`(1-B12)Temperatuur(t-6s)`[t] -0.940894`(1-B12)Temperatuur(t-7s)`[t] -0.978839`(1-B12)Temperatuur(t-8s)`[t] -0.914199`(1-B12)Temperatuur(t-9s)`[t] -0.921269`(1-B12)Temperatuur(t-10s)`[t] -0.939714`(1-B12)Temperatuur(t-11s)`[t] -0.816606`(1-B12)Temperatuur(t-12s)`[t] -1.04136`(1-B12)Temperatuur(t-13s)`[t] -1.12161`(1-B12)Temperatuur(t-14s)`[t] -1.04018`(1-B12)Temperatuur(t-15s)`[t] -0.972831`(1-B12)Temperatuur(t-16s)`[t] -0.817974`(1-B12)Temperatuur(t-17s)`[t] -0.469664`(1-B12)Temperatuur(t-18s)`[t] -0.301952`(1-B12)Temperatuur(t-19s)`[t] -0.388461`(1-B12)Temperatuur(t-20s)`[t] -0.324464`(1-B12)Temperatuur(t-21s)`[t] -0.256314`(1-B12)Temperatuur(t-22s)`[t] -0.221499`(1-B12)Temperatuur(t-23s)`[t] -0.213155`(1-B12)Temperatuur(t-24s)`[t] -0.153667`(1-B12)Temperatuur(t-25s)`[t] -0.251192`(1-B12)Temperatuur(t-26s)`[t] -0.186151`(1-B12)Temperatuur(t-27s)`[t] -0.0192929`(1-B12)Temperatuur(t-28s)`[t] -0.158552`(1-B12)Temperatuur(t-29s)`[t] -0.31427`(1-B12)Temperatuur(t-30s)`[t] -0.315163`(1-B12)Temperatuur(t-31s)`[t] -0.26506`(1-B12)Temperatuur(t-32s)`[t] -0.300214`(1-B12)Temperatuur(t-33s)`[t] -0.369546`(1-B12)Temperatuur(t-34s)`[t] -0.305064`(1-B12)Temperatuur(t-35s)`[t] -0.281397`(1-B12)Temperatuur(t-36s)`[t] -0.309294`(1-B12)Temperatuur(t-37s)`[t] -0.225042`(1-B12)Temperatuur(t-38s)`[t] -0.0124545`(1-B12)Temperatuur(t-39s)`[t] + 0.0275597`(1-B12)Temperatuur(t-40s)`[t] -0.0159474M1[t] -0.0276143M2[t] -0.0149765M3[t] + 0.0954911M4[t] + 0.0443135M5[t] -0.00887982M6[t] -0.0645825M7[t] -0.00791915M8[t] -0.0230877M9[t] -0.0264727M10[t] -0.071352M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
(1-B12)Temperatuur[t] =  +  0.305616 -0.00384852`(1-B12)Orkanen`[t] +  0.169909`(1-B12)Temperatuur(t-1)`[t] +  0.0491005`(1-B12)Temperatuur(t-2)`[t] -0.0245547`(1-B12)Temperatuur(t-3)`[t] +  0.00863072`(1-B12)Temperatuur(t-4)`[t] +  0.104247`(1-B12)Temperatuur(t-5)`[t] +  0.00753965`(1-B12)Temperatuur(t-6)`[t] -0.113292`(1-B12)Temperatuur(t-7)`[t] +  0.0749275`(1-B12)Temperatuur(t-8)`[t] -0.0509971`(1-B12)Temperatuur(t-9)`[t] +  0.0834595`(1-B12)Temperatuur(t-10)`[t] -1.02015`(1-B12)Temperatuur(t-1s)`[t] -1.1736`(1-B12)Temperatuur(t-2s)`[t] -1.2048`(1-B12)Temperatuur(t-3s)`[t] -0.995677`(1-B12)Temperatuur(t-4s)`[t] -1.07152`(1-B12)Temperatuur(t-5s)`[t] -1.18596`(1-B12)Temperatuur(t-6s)`[t] -0.940894`(1-B12)Temperatuur(t-7s)`[t] -0.978839`(1-B12)Temperatuur(t-8s)`[t] -0.914199`(1-B12)Temperatuur(t-9s)`[t] -0.921269`(1-B12)Temperatuur(t-10s)`[t] -0.939714`(1-B12)Temperatuur(t-11s)`[t] -0.816606`(1-B12)Temperatuur(t-12s)`[t] -1.04136`(1-B12)Temperatuur(t-13s)`[t] -1.12161`(1-B12)Temperatuur(t-14s)`[t] -1.04018`(1-B12)Temperatuur(t-15s)`[t] -0.972831`(1-B12)Temperatuur(t-16s)`[t] -0.817974`(1-B12)Temperatuur(t-17s)`[t] -0.469664`(1-B12)Temperatuur(t-18s)`[t] -0.301952`(1-B12)Temperatuur(t-19s)`[t] -0.388461`(1-B12)Temperatuur(t-20s)`[t] -0.324464`(1-B12)Temperatuur(t-21s)`[t] -0.256314`(1-B12)Temperatuur(t-22s)`[t] -0.221499`(1-B12)Temperatuur(t-23s)`[t] -0.213155`(1-B12)Temperatuur(t-24s)`[t] -0.153667`(1-B12)Temperatuur(t-25s)`[t] -0.251192`(1-B12)Temperatuur(t-26s)`[t] -0.186151`(1-B12)Temperatuur(t-27s)`[t] -0.0192929`(1-B12)Temperatuur(t-28s)`[t] -0.158552`(1-B12)Temperatuur(t-29s)`[t] -0.31427`(1-B12)Temperatuur(t-30s)`[t] -0.315163`(1-B12)Temperatuur(t-31s)`[t] -0.26506`(1-B12)Temperatuur(t-32s)`[t] -0.300214`(1-B12)Temperatuur(t-33s)`[t] -0.369546`(1-B12)Temperatuur(t-34s)`[t] -0.305064`(1-B12)Temperatuur(t-35s)`[t] -0.281397`(1-B12)Temperatuur(t-36s)`[t] -0.309294`(1-B12)Temperatuur(t-37s)`[t] -0.225042`(1-B12)Temperatuur(t-38s)`[t] -0.0124545`(1-B12)Temperatuur(t-39s)`[t] +  0.0275597`(1-B12)Temperatuur(t-40s)`[t] -0.0159474M1[t] -0.0276143M2[t] -0.0149765M3[t] +  0.0954911M4[t] +  0.0443135M5[t] -0.00887982M6[t] -0.0645825M7[t] -0.00791915M8[t] -0.0230877M9[t] -0.0264727M10[t] -0.071352M11[t]  + e[t] \tabularnewline
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286176&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C](1-B12)Temperatuur[t] =  +  0.305616 -0.00384852`(1-B12)Orkanen`[t] +  0.169909`(1-B12)Temperatuur(t-1)`[t] +  0.0491005`(1-B12)Temperatuur(t-2)`[t] -0.0245547`(1-B12)Temperatuur(t-3)`[t] +  0.00863072`(1-B12)Temperatuur(t-4)`[t] +  0.104247`(1-B12)Temperatuur(t-5)`[t] +  0.00753965`(1-B12)Temperatuur(t-6)`[t] -0.113292`(1-B12)Temperatuur(t-7)`[t] +  0.0749275`(1-B12)Temperatuur(t-8)`[t] -0.0509971`(1-B12)Temperatuur(t-9)`[t] +  0.0834595`(1-B12)Temperatuur(t-10)`[t] -1.02015`(1-B12)Temperatuur(t-1s)`[t] -1.1736`(1-B12)Temperatuur(t-2s)`[t] -1.2048`(1-B12)Temperatuur(t-3s)`[t] -0.995677`(1-B12)Temperatuur(t-4s)`[t] -1.07152`(1-B12)Temperatuur(t-5s)`[t] -1.18596`(1-B12)Temperatuur(t-6s)`[t] -0.940894`(1-B12)Temperatuur(t-7s)`[t] -0.978839`(1-B12)Temperatuur(t-8s)`[t] -0.914199`(1-B12)Temperatuur(t-9s)`[t] -0.921269`(1-B12)Temperatuur(t-10s)`[t] -0.939714`(1-B12)Temperatuur(t-11s)`[t] -0.816606`(1-B12)Temperatuur(t-12s)`[t] -1.04136`(1-B12)Temperatuur(t-13s)`[t] -1.12161`(1-B12)Temperatuur(t-14s)`[t] -1.04018`(1-B12)Temperatuur(t-15s)`[t] -0.972831`(1-B12)Temperatuur(t-16s)`[t] -0.817974`(1-B12)Temperatuur(t-17s)`[t] -0.469664`(1-B12)Temperatuur(t-18s)`[t] -0.301952`(1-B12)Temperatuur(t-19s)`[t] -0.388461`(1-B12)Temperatuur(t-20s)`[t] -0.324464`(1-B12)Temperatuur(t-21s)`[t] -0.256314`(1-B12)Temperatuur(t-22s)`[t] -0.221499`(1-B12)Temperatuur(t-23s)`[t] -0.213155`(1-B12)Temperatuur(t-24s)`[t] -0.153667`(1-B12)Temperatuur(t-25s)`[t] -0.251192`(1-B12)Temperatuur(t-26s)`[t] -0.186151`(1-B12)Temperatuur(t-27s)`[t] -0.0192929`(1-B12)Temperatuur(t-28s)`[t] -0.158552`(1-B12)Temperatuur(t-29s)`[t] -0.31427`(1-B12)Temperatuur(t-30s)`[t] -0.315163`(1-B12)Temperatuur(t-31s)`[t] -0.26506`(1-B12)Temperatuur(t-32s)`[t] -0.300214`(1-B12)Temperatuur(t-33s)`[t] -0.369546`(1-B12)Temperatuur(t-34s)`[t] -0.305064`(1-B12)Temperatuur(t-35s)`[t] -0.281397`(1-B12)Temperatuur(t-36s)`[t] -0.309294`(1-B12)Temperatuur(t-37s)`[t] -0.225042`(1-B12)Temperatuur(t-38s)`[t] -0.0124545`(1-B12)Temperatuur(t-39s)`[t] +  0.0275597`(1-B12)Temperatuur(t-40s)`[t] -0.0159474M1[t] -0.0276143M2[t] -0.0149765M3[t] +  0.0954911M4[t] +  0.0443135M5[t] -0.00887982M6[t] -0.0645825M7[t] -0.00791915M8[t] -0.0230877M9[t] -0.0264727M10[t] -0.071352M11[t]  + e[t][/C][/ROW]
[ROW][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286176&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286176&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
(1-B12)Temperatuur[t] = + 0.305616 -0.00384852`(1-B12)Orkanen`[t] + 0.169909`(1-B12)Temperatuur(t-1)`[t] + 0.0491005`(1-B12)Temperatuur(t-2)`[t] -0.0245547`(1-B12)Temperatuur(t-3)`[t] + 0.00863072`(1-B12)Temperatuur(t-4)`[t] + 0.104247`(1-B12)Temperatuur(t-5)`[t] + 0.00753965`(1-B12)Temperatuur(t-6)`[t] -0.113292`(1-B12)Temperatuur(t-7)`[t] + 0.0749275`(1-B12)Temperatuur(t-8)`[t] -0.0509971`(1-B12)Temperatuur(t-9)`[t] + 0.0834595`(1-B12)Temperatuur(t-10)`[t] -1.02015`(1-B12)Temperatuur(t-1s)`[t] -1.1736`(1-B12)Temperatuur(t-2s)`[t] -1.2048`(1-B12)Temperatuur(t-3s)`[t] -0.995677`(1-B12)Temperatuur(t-4s)`[t] -1.07152`(1-B12)Temperatuur(t-5s)`[t] -1.18596`(1-B12)Temperatuur(t-6s)`[t] -0.940894`(1-B12)Temperatuur(t-7s)`[t] -0.978839`(1-B12)Temperatuur(t-8s)`[t] -0.914199`(1-B12)Temperatuur(t-9s)`[t] -0.921269`(1-B12)Temperatuur(t-10s)`[t] -0.939714`(1-B12)Temperatuur(t-11s)`[t] -0.816606`(1-B12)Temperatuur(t-12s)`[t] -1.04136`(1-B12)Temperatuur(t-13s)`[t] -1.12161`(1-B12)Temperatuur(t-14s)`[t] -1.04018`(1-B12)Temperatuur(t-15s)`[t] -0.972831`(1-B12)Temperatuur(t-16s)`[t] -0.817974`(1-B12)Temperatuur(t-17s)`[t] -0.469664`(1-B12)Temperatuur(t-18s)`[t] -0.301952`(1-B12)Temperatuur(t-19s)`[t] -0.388461`(1-B12)Temperatuur(t-20s)`[t] -0.324464`(1-B12)Temperatuur(t-21s)`[t] -0.256314`(1-B12)Temperatuur(t-22s)`[t] -0.221499`(1-B12)Temperatuur(t-23s)`[t] -0.213155`(1-B12)Temperatuur(t-24s)`[t] -0.153667`(1-B12)Temperatuur(t-25s)`[t] -0.251192`(1-B12)Temperatuur(t-26s)`[t] -0.186151`(1-B12)Temperatuur(t-27s)`[t] -0.0192929`(1-B12)Temperatuur(t-28s)`[t] -0.158552`(1-B12)Temperatuur(t-29s)`[t] -0.31427`(1-B12)Temperatuur(t-30s)`[t] -0.315163`(1-B12)Temperatuur(t-31s)`[t] -0.26506`(1-B12)Temperatuur(t-32s)`[t] -0.300214`(1-B12)Temperatuur(t-33s)`[t] -0.369546`(1-B12)Temperatuur(t-34s)`[t] -0.305064`(1-B12)Temperatuur(t-35s)`[t] -0.281397`(1-B12)Temperatuur(t-36s)`[t] -0.309294`(1-B12)Temperatuur(t-37s)`[t] -0.225042`(1-B12)Temperatuur(t-38s)`[t] -0.0124545`(1-B12)Temperatuur(t-39s)`[t] + 0.0275597`(1-B12)Temperatuur(t-40s)`[t] -0.0159474M1[t] -0.0276143M2[t] -0.0149765M3[t] + 0.0954911M4[t] + 0.0443135M5[t] -0.00887982M6[t] -0.0645825M7[t] -0.00791915M8[t] -0.0230877M9[t] -0.0264727M10[t] -0.071352M11[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	+0.3056	0.09925	+3.0790e+00	0.002714	0.001357
`(1-B12)Orkanen`	-0.003848	0.007554	-5.0950e-01	0.6116	0.3058
`(1-B12)Temperatuur(t-1)`	+0.1699	0.07661	+2.2180e+00	0.02895	0.01447
`(1-B12)Temperatuur(t-2)`	+0.0491	0.07239	+6.7830e-01	0.4993	0.2496
`(1-B12)Temperatuur(t-3)`	-0.02456	0.073	-3.3640e-01	0.7373	0.3687
`(1-B12)Temperatuur(t-4)`	+0.008631	0.07268	+1.1870e-01	0.9057	0.4529
`(1-B12)Temperatuur(t-5)`	+0.1042	0.07129	+1.4620e+00	0.147	0.07348
`(1-B12)Temperatuur(t-6)`	+0.00754	0.07247	+1.0400e-01	0.9174	0.4587
`(1-B12)Temperatuur(t-7)`	-0.1133	0.07358	-1.5400e+00	0.1269	0.06347
`(1-B12)Temperatuur(t-8)`	+0.07493	0.07284	+1.0290e+00	0.3062	0.1531
`(1-B12)Temperatuur(t-9)`	-0.051	0.07432	-6.8620e-01	0.4943	0.2471
`(1-B12)Temperatuur(t-10)`	+0.08346	0.07304	+1.1430e+00	0.2561	0.128
`(1-B12)Temperatuur(t-1s)`	-1.02	0.1031	-9.8920e+00	2.813e-16	1.406e-16
`(1-B12)Temperatuur(t-2s)`	-1.174	0.1554	-7.5520e+00	2.613e-11	1.307e-11
`(1-B12)Temperatuur(t-3s)`	-1.205	0.1993	-6.0450e+00	2.923e-08	1.461e-08
`(1-B12)Temperatuur(t-4s)`	-0.9957	0.2369	-4.2040e+00	5.939e-05	2.97e-05
`(1-B12)Temperatuur(t-5s)`	-1.071	0.2629	-4.0760e+00	9.512e-05	4.756e-05
`(1-B12)Temperatuur(t-6s)`	-1.186	0.2996	-3.9590e+00	0.0001454	7.271e-05
`(1-B12)Temperatuur(t-7s)`	-0.9409	0.3425	-2.7470e+00	0.007193	0.003597
`(1-B12)Temperatuur(t-8s)`	-0.9788	0.3912	-2.5020e+00	0.01404	0.007022
`(1-B12)Temperatuur(t-9s)`	-0.9142	0.4328	-2.1120e+00	0.0373	0.01865
`(1-B12)Temperatuur(t-10s)`	-0.9213	0.4628	-1.9910e+00	0.04938	0.02469
`(1-B12)Temperatuur(t-11s)`	-0.9397	0.484	-1.9420e+00	0.05516	0.02758
`(1-B12)Temperatuur(t-12s)`	-0.8166	0.4962	-1.6460e+00	0.1031	0.05155
`(1-B12)Temperatuur(t-13s)`	-1.041	0.5011	-2.0780e+00	0.0404	0.0202
`(1-B12)Temperatuur(t-14s)`	-1.122	0.4903	-2.2870e+00	0.02439	0.01219
`(1-B12)Temperatuur(t-15s)`	-1.04	0.4748	-2.1910e+00	0.03091	0.01545
`(1-B12)Temperatuur(t-16s)`	-0.9728	0.4651	-2.0920e+00	0.03914	0.01957
`(1-B12)Temperatuur(t-17s)`	-0.818	0.4634	-1.7650e+00	0.08078	0.04039
`(1-B12)Temperatuur(t-18s)`	-0.4697	0.4516	-1.0400e+00	0.301	0.1505
`(1-B12)Temperatuur(t-19s)`	-0.3019	0.4213	-7.1680e-01	0.4753	0.2376
`(1-B12)Temperatuur(t-20s)`	-0.3885	0.3852	-1.0080e+00	0.3158	0.1579
`(1-B12)Temperatuur(t-21s)`	-0.3245	0.3614	-8.9780e-01	0.3716	0.1858
`(1-B12)Temperatuur(t-22s)`	-0.2563	0.3634	-7.0530e-01	0.4823	0.2412
`(1-B12)Temperatuur(t-23s)`	-0.2215	0.3693	-5.9980e-01	0.5501	0.275
`(1-B12)Temperatuur(t-24s)`	-0.2132	0.3946	-5.4020e-01	0.5903	0.2952
`(1-B12)Temperatuur(t-25s)`	-0.1537	0.4373	-3.5140e-01	0.7261	0.363
`(1-B12)Temperatuur(t-26s)`	-0.2512	0.4649	-5.4030e-01	0.5903	0.2951
`(1-B12)Temperatuur(t-27s)`	-0.1862	0.4697	-3.9630e-01	0.6928	0.3464
`(1-B12)Temperatuur(t-28s)`	-0.01929	0.4654	-4.1450e-02	0.967	0.4835
`(1-B12)Temperatuur(t-29s)`	-0.1585	0.4536	-3.4950e-01	0.7275	0.3637
`(1-B12)Temperatuur(t-30s)`	-0.3143	0.4396	-7.1500e-01	0.4764	0.2382
`(1-B12)Temperatuur(t-31s)`	-0.3152	0.433	-7.2790e-01	0.4685	0.2342
`(1-B12)Temperatuur(t-32s)`	-0.2651	0.4041	-6.5600e-01	0.5134	0.2567
`(1-B12)Temperatuur(t-33s)`	-0.3002	0.3788	-7.9250e-01	0.43	0.215
`(1-B12)Temperatuur(t-34s)`	-0.3695	0.3619	-1.0210e+00	0.3098	0.1549
`(1-B12)Temperatuur(t-35s)`	-0.3051	0.355	-8.5930e-01	0.3923	0.1962
`(1-B12)Temperatuur(t-36s)`	-0.2814	0.3259	-8.6350e-01	0.39	0.195
`(1-B12)Temperatuur(t-37s)`	-0.3093	0.2816	-1.0990e+00	0.2747	0.1374
`(1-B12)Temperatuur(t-38s)`	-0.225	0.23	-9.7840e-01	0.3304	0.1652
`(1-B12)Temperatuur(t-39s)`	-0.01246	0.1691	-7.3640e-02	0.9415	0.4707
`(1-B12)Temperatuur(t-40s)`	+0.02756	0.1135	+2.4280e-01	0.8087	0.4043
M1	-0.01595	0.05174	-3.0820e-01	0.7586	0.3793
M2	-0.02761	0.04257	-6.4870e-01	0.5181	0.259
M3	-0.01498	0.04983	-3.0050e-01	0.7644	0.3822
M4	+0.09549	0.04958	+1.9260e+00	0.0571	0.02855
M5	+0.04431	0.05477	+8.0900e-01	0.4205	0.2103
M6	-0.00888	0.04389	-2.0230e-01	0.8401	0.42
M7	-0.06458	0.04568	-1.4140e+00	0.1606	0.08032
M8	-0.007919	0.04136	-1.9150e-01	0.8486	0.4243
M9	-0.02309	0.04215	-5.4780e-01	0.5851	0.2926
M10	-0.02647	0.04211	-6.2870e-01	0.531	0.2655
M11	-0.07135	0.04582	-1.5570e+00	0.1227	0.06137

\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) & +0.3056 &  0.09925 & +3.0790e+00 &  0.002714 &  0.001357 \tabularnewline
`(1-B12)Orkanen` & -0.003848 &  0.007554 & -5.0950e-01 &  0.6116 &  0.3058 \tabularnewline
`(1-B12)Temperatuur(t-1)` & +0.1699 &  0.07661 & +2.2180e+00 &  0.02895 &  0.01447 \tabularnewline
`(1-B12)Temperatuur(t-2)` & +0.0491 &  0.07239 & +6.7830e-01 &  0.4993 &  0.2496 \tabularnewline
`(1-B12)Temperatuur(t-3)` & -0.02456 &  0.073 & -3.3640e-01 &  0.7373 &  0.3687 \tabularnewline
`(1-B12)Temperatuur(t-4)` & +0.008631 &  0.07268 & +1.1870e-01 &  0.9057 &  0.4529 \tabularnewline
`(1-B12)Temperatuur(t-5)` & +0.1042 &  0.07129 & +1.4620e+00 &  0.147 &  0.07348 \tabularnewline
`(1-B12)Temperatuur(t-6)` & +0.00754 &  0.07247 & +1.0400e-01 &  0.9174 &  0.4587 \tabularnewline
`(1-B12)Temperatuur(t-7)` & -0.1133 &  0.07358 & -1.5400e+00 &  0.1269 &  0.06347 \tabularnewline
`(1-B12)Temperatuur(t-8)` & +0.07493 &  0.07284 & +1.0290e+00 &  0.3062 &  0.1531 \tabularnewline
`(1-B12)Temperatuur(t-9)` & -0.051 &  0.07432 & -6.8620e-01 &  0.4943 &  0.2471 \tabularnewline
`(1-B12)Temperatuur(t-10)` & +0.08346 &  0.07304 & +1.1430e+00 &  0.2561 &  0.128 \tabularnewline
`(1-B12)Temperatuur(t-1s)` & -1.02 &  0.1031 & -9.8920e+00 &  2.813e-16 &  1.406e-16 \tabularnewline
`(1-B12)Temperatuur(t-2s)` & -1.174 &  0.1554 & -7.5520e+00 &  2.613e-11 &  1.307e-11 \tabularnewline
`(1-B12)Temperatuur(t-3s)` & -1.205 &  0.1993 & -6.0450e+00 &  2.923e-08 &  1.461e-08 \tabularnewline
`(1-B12)Temperatuur(t-4s)` & -0.9957 &  0.2369 & -4.2040e+00 &  5.939e-05 &  2.97e-05 \tabularnewline
`(1-B12)Temperatuur(t-5s)` & -1.071 &  0.2629 & -4.0760e+00 &  9.512e-05 &  4.756e-05 \tabularnewline
`(1-B12)Temperatuur(t-6s)` & -1.186 &  0.2996 & -3.9590e+00 &  0.0001454 &  7.271e-05 \tabularnewline
`(1-B12)Temperatuur(t-7s)` & -0.9409 &  0.3425 & -2.7470e+00 &  0.007193 &  0.003597 \tabularnewline
`(1-B12)Temperatuur(t-8s)` & -0.9788 &  0.3912 & -2.5020e+00 &  0.01404 &  0.007022 \tabularnewline
`(1-B12)Temperatuur(t-9s)` & -0.9142 &  0.4328 & -2.1120e+00 &  0.0373 &  0.01865 \tabularnewline
`(1-B12)Temperatuur(t-10s)` & -0.9213 &  0.4628 & -1.9910e+00 &  0.04938 &  0.02469 \tabularnewline
`(1-B12)Temperatuur(t-11s)` & -0.9397 &  0.484 & -1.9420e+00 &  0.05516 &  0.02758 \tabularnewline
`(1-B12)Temperatuur(t-12s)` & -0.8166 &  0.4962 & -1.6460e+00 &  0.1031 &  0.05155 \tabularnewline
`(1-B12)Temperatuur(t-13s)` & -1.041 &  0.5011 & -2.0780e+00 &  0.0404 &  0.0202 \tabularnewline
`(1-B12)Temperatuur(t-14s)` & -1.122 &  0.4903 & -2.2870e+00 &  0.02439 &  0.01219 \tabularnewline
`(1-B12)Temperatuur(t-15s)` & -1.04 &  0.4748 & -2.1910e+00 &  0.03091 &  0.01545 \tabularnewline
`(1-B12)Temperatuur(t-16s)` & -0.9728 &  0.4651 & -2.0920e+00 &  0.03914 &  0.01957 \tabularnewline
`(1-B12)Temperatuur(t-17s)` & -0.818 &  0.4634 & -1.7650e+00 &  0.08078 &  0.04039 \tabularnewline
`(1-B12)Temperatuur(t-18s)` & -0.4697 &  0.4516 & -1.0400e+00 &  0.301 &  0.1505 \tabularnewline
`(1-B12)Temperatuur(t-19s)` & -0.3019 &  0.4213 & -7.1680e-01 &  0.4753 &  0.2376 \tabularnewline
`(1-B12)Temperatuur(t-20s)` & -0.3885 &  0.3852 & -1.0080e+00 &  0.3158 &  0.1579 \tabularnewline
`(1-B12)Temperatuur(t-21s)` & -0.3245 &  0.3614 & -8.9780e-01 &  0.3716 &  0.1858 \tabularnewline
`(1-B12)Temperatuur(t-22s)` & -0.2563 &  0.3634 & -7.0530e-01 &  0.4823 &  0.2412 \tabularnewline
`(1-B12)Temperatuur(t-23s)` & -0.2215 &  0.3693 & -5.9980e-01 &  0.5501 &  0.275 \tabularnewline
`(1-B12)Temperatuur(t-24s)` & -0.2132 &  0.3946 & -5.4020e-01 &  0.5903 &  0.2952 \tabularnewline
`(1-B12)Temperatuur(t-25s)` & -0.1537 &  0.4373 & -3.5140e-01 &  0.7261 &  0.363 \tabularnewline
`(1-B12)Temperatuur(t-26s)` & -0.2512 &  0.4649 & -5.4030e-01 &  0.5903 &  0.2951 \tabularnewline
`(1-B12)Temperatuur(t-27s)` & -0.1862 &  0.4697 & -3.9630e-01 &  0.6928 &  0.3464 \tabularnewline
`(1-B12)Temperatuur(t-28s)` & -0.01929 &  0.4654 & -4.1450e-02 &  0.967 &  0.4835 \tabularnewline
`(1-B12)Temperatuur(t-29s)` & -0.1585 &  0.4536 & -3.4950e-01 &  0.7275 &  0.3637 \tabularnewline
`(1-B12)Temperatuur(t-30s)` & -0.3143 &  0.4396 & -7.1500e-01 &  0.4764 &  0.2382 \tabularnewline
`(1-B12)Temperatuur(t-31s)` & -0.3152 &  0.433 & -7.2790e-01 &  0.4685 &  0.2342 \tabularnewline
`(1-B12)Temperatuur(t-32s)` & -0.2651 &  0.4041 & -6.5600e-01 &  0.5134 &  0.2567 \tabularnewline
`(1-B12)Temperatuur(t-33s)` & -0.3002 &  0.3788 & -7.9250e-01 &  0.43 &  0.215 \tabularnewline
`(1-B12)Temperatuur(t-34s)` & -0.3695 &  0.3619 & -1.0210e+00 &  0.3098 &  0.1549 \tabularnewline
`(1-B12)Temperatuur(t-35s)` & -0.3051 &  0.355 & -8.5930e-01 &  0.3923 &  0.1962 \tabularnewline
`(1-B12)Temperatuur(t-36s)` & -0.2814 &  0.3259 & -8.6350e-01 &  0.39 &  0.195 \tabularnewline
`(1-B12)Temperatuur(t-37s)` & -0.3093 &  0.2816 & -1.0990e+00 &  0.2747 &  0.1374 \tabularnewline
`(1-B12)Temperatuur(t-38s)` & -0.225 &  0.23 & -9.7840e-01 &  0.3304 &  0.1652 \tabularnewline
`(1-B12)Temperatuur(t-39s)` & -0.01246 &  0.1691 & -7.3640e-02 &  0.9415 &  0.4707 \tabularnewline
`(1-B12)Temperatuur(t-40s)` & +0.02756 &  0.1135 & +2.4280e-01 &  0.8087 &  0.4043 \tabularnewline
M1 & -0.01595 &  0.05174 & -3.0820e-01 &  0.7586 &  0.3793 \tabularnewline
M2 & -0.02761 &  0.04257 & -6.4870e-01 &  0.5181 &  0.259 \tabularnewline
M3 & -0.01498 &  0.04983 & -3.0050e-01 &  0.7644 &  0.3822 \tabularnewline
M4 & +0.09549 &  0.04958 & +1.9260e+00 &  0.0571 &  0.02855 \tabularnewline
M5 & +0.04431 &  0.05477 & +8.0900e-01 &  0.4205 &  0.2103 \tabularnewline
M6 & -0.00888 &  0.04389 & -2.0230e-01 &  0.8401 &  0.42 \tabularnewline
M7 & -0.06458 &  0.04568 & -1.4140e+00 &  0.1606 &  0.08032 \tabularnewline
M8 & -0.007919 &  0.04136 & -1.9150e-01 &  0.8486 &  0.4243 \tabularnewline
M9 & -0.02309 &  0.04215 & -5.4780e-01 &  0.5851 &  0.2926 \tabularnewline
M10 & -0.02647 &  0.04211 & -6.2870e-01 &  0.531 &  0.2655 \tabularnewline
M11 & -0.07135 &  0.04582 & -1.5570e+00 &  0.1227 &  0.06137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286176&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]+0.3056[/C][C] 0.09925[/C][C]+3.0790e+00[/C][C] 0.002714[/C][C] 0.001357[/C][/ROW]
[ROW][C]`(1-B12)Orkanen`[/C][C]-0.003848[/C][C] 0.007554[/C][C]-5.0950e-01[/C][C] 0.6116[/C][C] 0.3058[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-1)`[/C][C]+0.1699[/C][C] 0.07661[/C][C]+2.2180e+00[/C][C] 0.02895[/C][C] 0.01447[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-2)`[/C][C]+0.0491[/C][C] 0.07239[/C][C]+6.7830e-01[/C][C] 0.4993[/C][C] 0.2496[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-3)`[/C][C]-0.02456[/C][C] 0.073[/C][C]-3.3640e-01[/C][C] 0.7373[/C][C] 0.3687[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-4)`[/C][C]+0.008631[/C][C] 0.07268[/C][C]+1.1870e-01[/C][C] 0.9057[/C][C] 0.4529[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-5)`[/C][C]+0.1042[/C][C] 0.07129[/C][C]+1.4620e+00[/C][C] 0.147[/C][C] 0.07348[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-6)`[/C][C]+0.00754[/C][C] 0.07247[/C][C]+1.0400e-01[/C][C] 0.9174[/C][C] 0.4587[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-7)`[/C][C]-0.1133[/C][C] 0.07358[/C][C]-1.5400e+00[/C][C] 0.1269[/C][C] 0.06347[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-8)`[/C][C]+0.07493[/C][C] 0.07284[/C][C]+1.0290e+00[/C][C] 0.3062[/C][C] 0.1531[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-9)`[/C][C]-0.051[/C][C] 0.07432[/C][C]-6.8620e-01[/C][C] 0.4943[/C][C] 0.2471[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-10)`[/C][C]+0.08346[/C][C] 0.07304[/C][C]+1.1430e+00[/C][C] 0.2561[/C][C] 0.128[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-1s)`[/C][C]-1.02[/C][C] 0.1031[/C][C]-9.8920e+00[/C][C] 2.813e-16[/C][C] 1.406e-16[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-2s)`[/C][C]-1.174[/C][C] 0.1554[/C][C]-7.5520e+00[/C][C] 2.613e-11[/C][C] 1.307e-11[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-3s)`[/C][C]-1.205[/C][C] 0.1993[/C][C]-6.0450e+00[/C][C] 2.923e-08[/C][C] 1.461e-08[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-4s)`[/C][C]-0.9957[/C][C] 0.2369[/C][C]-4.2040e+00[/C][C] 5.939e-05[/C][C] 2.97e-05[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-5s)`[/C][C]-1.071[/C][C] 0.2629[/C][C]-4.0760e+00[/C][C] 9.512e-05[/C][C] 4.756e-05[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-6s)`[/C][C]-1.186[/C][C] 0.2996[/C][C]-3.9590e+00[/C][C] 0.0001454[/C][C] 7.271e-05[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-7s)`[/C][C]-0.9409[/C][C] 0.3425[/C][C]-2.7470e+00[/C][C] 0.007193[/C][C] 0.003597[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-8s)`[/C][C]-0.9788[/C][C] 0.3912[/C][C]-2.5020e+00[/C][C] 0.01404[/C][C] 0.007022[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-9s)`[/C][C]-0.9142[/C][C] 0.4328[/C][C]-2.1120e+00[/C][C] 0.0373[/C][C] 0.01865[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-10s)`[/C][C]-0.9213[/C][C] 0.4628[/C][C]-1.9910e+00[/C][C] 0.04938[/C][C] 0.02469[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-11s)`[/C][C]-0.9397[/C][C] 0.484[/C][C]-1.9420e+00[/C][C] 0.05516[/C][C] 0.02758[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-12s)`[/C][C]-0.8166[/C][C] 0.4962[/C][C]-1.6460e+00[/C][C] 0.1031[/C][C] 0.05155[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-13s)`[/C][C]-1.041[/C][C] 0.5011[/C][C]-2.0780e+00[/C][C] 0.0404[/C][C] 0.0202[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-14s)`[/C][C]-1.122[/C][C] 0.4903[/C][C]-2.2870e+00[/C][C] 0.02439[/C][C] 0.01219[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-15s)`[/C][C]-1.04[/C][C] 0.4748[/C][C]-2.1910e+00[/C][C] 0.03091[/C][C] 0.01545[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-16s)`[/C][C]-0.9728[/C][C] 0.4651[/C][C]-2.0920e+00[/C][C] 0.03914[/C][C] 0.01957[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-17s)`[/C][C]-0.818[/C][C] 0.4634[/C][C]-1.7650e+00[/C][C] 0.08078[/C][C] 0.04039[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-18s)`[/C][C]-0.4697[/C][C] 0.4516[/C][C]-1.0400e+00[/C][C] 0.301[/C][C] 0.1505[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-19s)`[/C][C]-0.3019[/C][C] 0.4213[/C][C]-7.1680e-01[/C][C] 0.4753[/C][C] 0.2376[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-20s)`[/C][C]-0.3885[/C][C] 0.3852[/C][C]-1.0080e+00[/C][C] 0.3158[/C][C] 0.1579[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-21s)`[/C][C]-0.3245[/C][C] 0.3614[/C][C]-8.9780e-01[/C][C] 0.3716[/C][C] 0.1858[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-22s)`[/C][C]-0.2563[/C][C] 0.3634[/C][C]-7.0530e-01[/C][C] 0.4823[/C][C] 0.2412[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-23s)`[/C][C]-0.2215[/C][C] 0.3693[/C][C]-5.9980e-01[/C][C] 0.5501[/C][C] 0.275[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-24s)`[/C][C]-0.2132[/C][C] 0.3946[/C][C]-5.4020e-01[/C][C] 0.5903[/C][C] 0.2952[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-25s)`[/C][C]-0.1537[/C][C] 0.4373[/C][C]-3.5140e-01[/C][C] 0.7261[/C][C] 0.363[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-26s)`[/C][C]-0.2512[/C][C] 0.4649[/C][C]-5.4030e-01[/C][C] 0.5903[/C][C] 0.2951[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-27s)`[/C][C]-0.1862[/C][C] 0.4697[/C][C]-3.9630e-01[/C][C] 0.6928[/C][C] 0.3464[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-28s)`[/C][C]-0.01929[/C][C] 0.4654[/C][C]-4.1450e-02[/C][C] 0.967[/C][C] 0.4835[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-29s)`[/C][C]-0.1585[/C][C] 0.4536[/C][C]-3.4950e-01[/C][C] 0.7275[/C][C] 0.3637[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-30s)`[/C][C]-0.3143[/C][C] 0.4396[/C][C]-7.1500e-01[/C][C] 0.4764[/C][C] 0.2382[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-31s)`[/C][C]-0.3152[/C][C] 0.433[/C][C]-7.2790e-01[/C][C] 0.4685[/C][C] 0.2342[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-32s)`[/C][C]-0.2651[/C][C] 0.4041[/C][C]-6.5600e-01[/C][C] 0.5134[/C][C] 0.2567[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-33s)`[/C][C]-0.3002[/C][C] 0.3788[/C][C]-7.9250e-01[/C][C] 0.43[/C][C] 0.215[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-34s)`[/C][C]-0.3695[/C][C] 0.3619[/C][C]-1.0210e+00[/C][C] 0.3098[/C][C] 0.1549[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-35s)`[/C][C]-0.3051[/C][C] 0.355[/C][C]-8.5930e-01[/C][C] 0.3923[/C][C] 0.1962[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-36s)`[/C][C]-0.2814[/C][C] 0.3259[/C][C]-8.6350e-01[/C][C] 0.39[/C][C] 0.195[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-37s)`[/C][C]-0.3093[/C][C] 0.2816[/C][C]-1.0990e+00[/C][C] 0.2747[/C][C] 0.1374[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-38s)`[/C][C]-0.225[/C][C] 0.23[/C][C]-9.7840e-01[/C][C] 0.3304[/C][C] 0.1652[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-39s)`[/C][C]-0.01246[/C][C] 0.1691[/C][C]-7.3640e-02[/C][C] 0.9415[/C][C] 0.4707[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur(t-40s)`[/C][C]+0.02756[/C][C] 0.1135[/C][C]+2.4280e-01[/C][C] 0.8087[/C][C] 0.4043[/C][/ROW]
[ROW][C]M1[/C][C]-0.01595[/C][C] 0.05174[/C][C]-3.0820e-01[/C][C] 0.7586[/C][C] 0.3793[/C][/ROW]
[ROW][C]M2[/C][C]-0.02761[/C][C] 0.04257[/C][C]-6.4870e-01[/C][C] 0.5181[/C][C] 0.259[/C][/ROW]
[ROW][C]M3[/C][C]-0.01498[/C][C] 0.04983[/C][C]-3.0050e-01[/C][C] 0.7644[/C][C] 0.3822[/C][/ROW]
[ROW][C]M4[/C][C]+0.09549[/C][C] 0.04958[/C][C]+1.9260e+00[/C][C] 0.0571[/C][C] 0.02855[/C][/ROW]
[ROW][C]M5[/C][C]+0.04431[/C][C] 0.05477[/C][C]+8.0900e-01[/C][C] 0.4205[/C][C] 0.2103[/C][/ROW]
[ROW][C]M6[/C][C]-0.00888[/C][C] 0.04389[/C][C]-2.0230e-01[/C][C] 0.8401[/C][C] 0.42[/C][/ROW]
[ROW][C]M7[/C][C]-0.06458[/C][C] 0.04568[/C][C]-1.4140e+00[/C][C] 0.1606[/C][C] 0.08032[/C][/ROW]
[ROW][C]M8[/C][C]-0.007919[/C][C] 0.04136[/C][C]-1.9150e-01[/C][C] 0.8486[/C][C] 0.4243[/C][/ROW]
[ROW][C]M9[/C][C]-0.02309[/C][C] 0.04215[/C][C]-5.4780e-01[/C][C] 0.5851[/C][C] 0.2926[/C][/ROW]
[ROW][C]M10[/C][C]-0.02647[/C][C] 0.04211[/C][C]-6.2870e-01[/C][C] 0.531[/C][C] 0.2655[/C][/ROW]
[ROW][C]M11[/C][C]-0.07135[/C][C] 0.04582[/C][C]-1.5570e+00[/C][C] 0.1227[/C][C] 0.06137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286176&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286176&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	+0.3056	0.09925	+3.0790e+00	0.002714	0.001357
`(1-B12)Orkanen`	-0.003848	0.007554	-5.0950e-01	0.6116	0.3058
`(1-B12)Temperatuur(t-1)`	+0.1699	0.07661	+2.2180e+00	0.02895	0.01447
`(1-B12)Temperatuur(t-2)`	+0.0491	0.07239	+6.7830e-01	0.4993	0.2496
`(1-B12)Temperatuur(t-3)`	-0.02456	0.073	-3.3640e-01	0.7373	0.3687
`(1-B12)Temperatuur(t-4)`	+0.008631	0.07268	+1.1870e-01	0.9057	0.4529
`(1-B12)Temperatuur(t-5)`	+0.1042	0.07129	+1.4620e+00	0.147	0.07348
`(1-B12)Temperatuur(t-6)`	+0.00754	0.07247	+1.0400e-01	0.9174	0.4587
`(1-B12)Temperatuur(t-7)`	-0.1133	0.07358	-1.5400e+00	0.1269	0.06347
`(1-B12)Temperatuur(t-8)`	+0.07493	0.07284	+1.0290e+00	0.3062	0.1531
`(1-B12)Temperatuur(t-9)`	-0.051	0.07432	-6.8620e-01	0.4943	0.2471
`(1-B12)Temperatuur(t-10)`	+0.08346	0.07304	+1.1430e+00	0.2561	0.128
`(1-B12)Temperatuur(t-1s)`	-1.02	0.1031	-9.8920e+00	2.813e-16	1.406e-16
`(1-B12)Temperatuur(t-2s)`	-1.174	0.1554	-7.5520e+00	2.613e-11	1.307e-11
`(1-B12)Temperatuur(t-3s)`	-1.205	0.1993	-6.0450e+00	2.923e-08	1.461e-08
`(1-B12)Temperatuur(t-4s)`	-0.9957	0.2369	-4.2040e+00	5.939e-05	2.97e-05
`(1-B12)Temperatuur(t-5s)`	-1.071	0.2629	-4.0760e+00	9.512e-05	4.756e-05
`(1-B12)Temperatuur(t-6s)`	-1.186	0.2996	-3.9590e+00	0.0001454	7.271e-05
`(1-B12)Temperatuur(t-7s)`	-0.9409	0.3425	-2.7470e+00	0.007193	0.003597
`(1-B12)Temperatuur(t-8s)`	-0.9788	0.3912	-2.5020e+00	0.01404	0.007022
`(1-B12)Temperatuur(t-9s)`	-0.9142	0.4328	-2.1120e+00	0.0373	0.01865
`(1-B12)Temperatuur(t-10s)`	-0.9213	0.4628	-1.9910e+00	0.04938	0.02469
`(1-B12)Temperatuur(t-11s)`	-0.9397	0.484	-1.9420e+00	0.05516	0.02758
`(1-B12)Temperatuur(t-12s)`	-0.8166	0.4962	-1.6460e+00	0.1031	0.05155
`(1-B12)Temperatuur(t-13s)`	-1.041	0.5011	-2.0780e+00	0.0404	0.0202
`(1-B12)Temperatuur(t-14s)`	-1.122	0.4903	-2.2870e+00	0.02439	0.01219
`(1-B12)Temperatuur(t-15s)`	-1.04	0.4748	-2.1910e+00	0.03091	0.01545
`(1-B12)Temperatuur(t-16s)`	-0.9728	0.4651	-2.0920e+00	0.03914	0.01957
`(1-B12)Temperatuur(t-17s)`	-0.818	0.4634	-1.7650e+00	0.08078	0.04039
`(1-B12)Temperatuur(t-18s)`	-0.4697	0.4516	-1.0400e+00	0.301	0.1505
`(1-B12)Temperatuur(t-19s)`	-0.3019	0.4213	-7.1680e-01	0.4753	0.2376
`(1-B12)Temperatuur(t-20s)`	-0.3885	0.3852	-1.0080e+00	0.3158	0.1579
`(1-B12)Temperatuur(t-21s)`	-0.3245	0.3614	-8.9780e-01	0.3716	0.1858
`(1-B12)Temperatuur(t-22s)`	-0.2563	0.3634	-7.0530e-01	0.4823	0.2412
`(1-B12)Temperatuur(t-23s)`	-0.2215	0.3693	-5.9980e-01	0.5501	0.275
`(1-B12)Temperatuur(t-24s)`	-0.2132	0.3946	-5.4020e-01	0.5903	0.2952
`(1-B12)Temperatuur(t-25s)`	-0.1537	0.4373	-3.5140e-01	0.7261	0.363
`(1-B12)Temperatuur(t-26s)`	-0.2512	0.4649	-5.4030e-01	0.5903	0.2951
`(1-B12)Temperatuur(t-27s)`	-0.1862	0.4697	-3.9630e-01	0.6928	0.3464
`(1-B12)Temperatuur(t-28s)`	-0.01929	0.4654	-4.1450e-02	0.967	0.4835
`(1-B12)Temperatuur(t-29s)`	-0.1585	0.4536	-3.4950e-01	0.7275	0.3637
`(1-B12)Temperatuur(t-30s)`	-0.3143	0.4396	-7.1500e-01	0.4764	0.2382
`(1-B12)Temperatuur(t-31s)`	-0.3152	0.433	-7.2790e-01	0.4685	0.2342
`(1-B12)Temperatuur(t-32s)`	-0.2651	0.4041	-6.5600e-01	0.5134	0.2567
`(1-B12)Temperatuur(t-33s)`	-0.3002	0.3788	-7.9250e-01	0.43	0.215
`(1-B12)Temperatuur(t-34s)`	-0.3695	0.3619	-1.0210e+00	0.3098	0.1549
`(1-B12)Temperatuur(t-35s)`	-0.3051	0.355	-8.5930e-01	0.3923	0.1962
`(1-B12)Temperatuur(t-36s)`	-0.2814	0.3259	-8.6350e-01	0.39	0.195
`(1-B12)Temperatuur(t-37s)`	-0.3093	0.2816	-1.0990e+00	0.2747	0.1374
`(1-B12)Temperatuur(t-38s)`	-0.225	0.23	-9.7840e-01	0.3304	0.1652
`(1-B12)Temperatuur(t-39s)`	-0.01246	0.1691	-7.3640e-02	0.9415	0.4707
`(1-B12)Temperatuur(t-40s)`	+0.02756	0.1135	+2.4280e-01	0.8087	0.4043
M1	-0.01595	0.05174	-3.0820e-01	0.7586	0.3793
M2	-0.02761	0.04257	-6.4870e-01	0.5181	0.259
M3	-0.01498	0.04983	-3.0050e-01	0.7644	0.3822
M4	+0.09549	0.04958	+1.9260e+00	0.0571	0.02855
M5	+0.04431	0.05477	+8.0900e-01	0.4205	0.2103
M6	-0.00888	0.04389	-2.0230e-01	0.8401	0.42
M7	-0.06458	0.04568	-1.4140e+00	0.1606	0.08032
M8	-0.007919	0.04136	-1.9150e-01	0.8486	0.4243
M9	-0.02309	0.04215	-5.4780e-01	0.5851	0.2926
M10	-0.02647	0.04211	-6.2870e-01	0.531	0.2655
M11	-0.07135	0.04582	-1.5570e+00	0.1227	0.06137

Multiple Linear Regression - Regression Statistics
Multiple R	0.916
R-squared	0.839
Adjusted R-squared	0.7339
F-TEST (value)	7.985
F-TEST (DF numerator)	62
F-TEST (DF denominator)	95
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.1029
Sum Squared Residuals	1.006

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R &  0.916 \tabularnewline
R-squared &  0.839 \tabularnewline
Adjusted R-squared &  0.7339 \tabularnewline
F-TEST (value) &  7.985 \tabularnewline
F-TEST (DF numerator) & 62 \tabularnewline
F-TEST (DF denominator) & 95 \tabularnewline
p-value &  0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation &  0.1029 \tabularnewline
Sum Squared Residuals &  1.006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286176&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C] 0.916[/C][/ROW]
[ROW][C]R-squared[/C][C] 0.839[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C] 0.7339[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C] 7.985[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]62[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]95[/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] 0.1029[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C] 1.006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286176&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286176&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.916
R-squared	0.839
Adjusted R-squared	0.7339
F-TEST (value)	7.985
F-TEST (DF numerator)	62
F-TEST (DF denominator)	95
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.1029
Sum Squared Residuals	1.006

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	0.09	0.1886	-0.09855
2	0.07	0.05703	0.01297
3	0.22	0.221	-0.0009508
4	0.09	0.08795	0.002049
5	0.39	0.2177	0.1723
6	0.27	0.2233	0.04673
7	0.25	0.2824	-0.03236
8	0.25	0.2491	0.0009022
9	0.12	0.1168	0.003184
10	0.04	0.1355	-0.09546
11	-0.02	0.06187	-0.08187
12	0.17	0.09178	0.07822
13	0.31	0.2663	0.04365
14	0.1	0.07585	0.02415
15	0.02	0.06839	-0.04839
16	0.09	0.06805	0.02195
17	-0.36	-0.3236	-0.03644
18	-0.02	-0.1294	0.1094
19	-0.01	-0.04757	0.03757
20	0.11	0.02361	0.08639
21	0.09	0.01867	0.07133
22	0.02	0.02846	-0.008461
23	0.13	0.05957	0.07043
24	-0.18	0.002131	-0.1821
25	-0.29	-0.2943	0.00433
26	-0.19	-0.1394	-0.05059
27	0.03	-0.1465	0.1765
28	-0.06	-0.04758	-0.01242
29	0.05	-0.05831	0.1083
30	-0.22	-0.1358	-0.08416
31	-0.09	-0.1253	0.03534
32	-0.27	-0.1769	-0.09308
33	-0.43	-0.2754	-0.1546
34	-0.29	-0.1419	-0.1481
35	-0.42	-0.3006	-0.1194
36	-0.22	-0.124	-0.09602
37	-0.23	-0.04719	-0.1828
38	-0.07	-0.2136	0.1436
39	-0.1	-0.2117	0.1117
40	-0.11	-0.1414	0.03139
41	-0.04	-0.09258	0.05258
42	-0.01	-0.07827	0.06827
43	-0.04	-0.1526	0.1126
44	-0.05	-0.08851	0.03851
45	0.09	0.06659	0.02341
46	0.02	0.1443	-0.1243
47	0.08	0.115	-0.035
48	0.16	0.1396	0.02036
49	0.07	0.2142	-0.1442
50	0.01	-0.04173	0.05173
51	0	-0.08019	0.08019
52	-0.32	-0.03643	-0.2836
53	-0.05	-0.1186	0.0686
54	0.08	0.02369	0.05631
55	0.04	0.03855	0.001445
56	0.19	0.1779	0.01206
57	0.11	0.1998	-0.08985
58	0.16	0.1665	-0.006511
59	0.23	0.3061	-0.0761
60	0.22	0.1381	0.08185
61	0.37	0.3699	5.717e-05
62	0.15	0.2325	-0.08254
63	0.16	0.1579	0.002125
64	0.76	0.5932	0.1668
65	0.19	0.2528	-0.06281
66	0.08	0.1956	-0.1156
67	-0.11	0.01086	-0.1209
68	0.04	0.06358	-0.02358
69	0.26	0.2136	0.04644
70	0.18	0.1815	-0.001514
71	-0.01	0.0685	-0.0785
72	0.04	-0.07486	0.1149
73	0	-0.047	0.047
74	-0.03	0.03105	-0.06105
75	-0.21	-0.1889	-0.02115
76	-0.27	-0.3184	0.0484
77	-0.19	-0.1371	-0.05289
78	-0.14	-0.1558	0.01576
79	0.1	0.07033	0.02967
80	-0.15	-0.1182	-0.03181
81	-0.16	-0.2429	0.0829
82	-0.05	-0.1665	0.1165
83	-0.08	-0.08202	0.002018
84	-0.27	-0.1546	-0.1154
85	-0.09	-0.2101	0.1201
86	0.05	-0.0124	0.0624
87	0.04	0.128	-0.08799
88	-0.12	-0.07284	-0.04716
89	0.21	0.2673	-0.05727
90	0.13	0.2617	-0.1317
91	0.1	0.2145	-0.1145
92	0.25	0.2351	0.0149
93	-0.02	0.04423	-0.06423
94	0.04	-0.009822	0.04982
95	0.29	0.131	0.159
96	0.35	0.2634	0.08665
97	0.27	0.2385	0.03153
98	0.22	0.3226	-0.1026
99	0.28	0.3242	-0.04418
100	0.52	0.4483	0.07167
101	0.1	0.173	-0.07296
102	0.25	0.249	0.0009514
103	0.28	0.1619	0.1181
104	0.16	0.1626	-0.002609
105	0.39	0.3218	0.06818
106	0.24	0.1093	0.1307
107	-0.02	0.04156	-0.06156
108	-0.08	-0.04662	-0.03338
109	-0.15	-0.1414	-0.008558
110	-0.02	-0.06724	0.04724
111	-0.1	-0.03828	-0.06172
112	-0.19	-0.2032	0.01323
113	-0.29	-0.1711	-0.1189
114	-0.3	-0.2813	-0.01871
115	-0.36	-0.3606	0.0006072
116	-0.31	-0.326	0.01596
117	-0.41	-0.335	-0.07501
118	-0.33	-0.3222	-0.007781
119	-0.18	-0.2594	0.07938
120	-0.12	-0.1862	0.06622
121	-0.08	-0.1086	0.02864
122	-0.14	-0.1365	-0.003491
123	-0.24	-0.1255	-0.1145
124	-0.15	-0.2105	0.06047
125	0.19	0.2081	-0.01809
126	0.22	0.09612	0.1239
127	0.07	0.1338	-0.06383
128	0.03	-0.001251	0.03125
129	0.02	0.01425	0.005754
130	0.1	0.08155	0.01845
131	0.04	-0.003543	0.04354
132	-0.09	-0.008163	-0.08184
133	-0.11	-0.08601	-0.02399
134	-0.18	-0.01179	-0.1682
135	0.17	0.1978	-0.02783
136	-0.09	-0.01519	-0.07481
137	0.1	0.1393	-0.03926
138	-0.08	-0.05496	-0.02504
139	0.17	0.145	0.02496
140	0.14	0.1404	-0.0004103
141	0.18	0.0848	0.0952
142	0.08	-0.02688	0.1069
143	0.16	0.1451	0.01486
144	0.22	0.1866	0.03342
145	0.47	0.3479	0.1221
146	0.28	0.2363	0.04365
147	0.36	0.3239	0.03611
148	0.35	0.3479	0.002059
149	0.25	0.1932	0.05679
150	0.12	0.1662	-0.04615
151	0.04	0.0688	-0.0288
152	-0.02	0.02849	-0.04849
153	0.07	0.08268	-0.01268
154	-0.02	0.01018	-0.03018
155	0.01	-0.07326	0.08326
156	0.05	0.02278	0.02722
157	-0.17	-0.2307	0.06072
158	-0.14	-0.2227	0.08274

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 &  0.09 &  0.1886 & -0.09855 \tabularnewline
2 &  0.07 &  0.05703 &  0.01297 \tabularnewline
3 &  0.22 &  0.221 & -0.0009508 \tabularnewline
4 &  0.09 &  0.08795 &  0.002049 \tabularnewline
5 &  0.39 &  0.2177 &  0.1723 \tabularnewline
6 &  0.27 &  0.2233 &  0.04673 \tabularnewline
7 &  0.25 &  0.2824 & -0.03236 \tabularnewline
8 &  0.25 &  0.2491 &  0.0009022 \tabularnewline
9 &  0.12 &  0.1168 &  0.003184 \tabularnewline
10 &  0.04 &  0.1355 & -0.09546 \tabularnewline
11 & -0.02 &  0.06187 & -0.08187 \tabularnewline
12 &  0.17 &  0.09178 &  0.07822 \tabularnewline
13 &  0.31 &  0.2663 &  0.04365 \tabularnewline
14 &  0.1 &  0.07585 &  0.02415 \tabularnewline
15 &  0.02 &  0.06839 & -0.04839 \tabularnewline
16 &  0.09 &  0.06805 &  0.02195 \tabularnewline
17 & -0.36 & -0.3236 & -0.03644 \tabularnewline
18 & -0.02 & -0.1294 &  0.1094 \tabularnewline
19 & -0.01 & -0.04757 &  0.03757 \tabularnewline
20 &  0.11 &  0.02361 &  0.08639 \tabularnewline
21 &  0.09 &  0.01867 &  0.07133 \tabularnewline
22 &  0.02 &  0.02846 & -0.008461 \tabularnewline
23 &  0.13 &  0.05957 &  0.07043 \tabularnewline
24 & -0.18 &  0.002131 & -0.1821 \tabularnewline
25 & -0.29 & -0.2943 &  0.00433 \tabularnewline
26 & -0.19 & -0.1394 & -0.05059 \tabularnewline
27 &  0.03 & -0.1465 &  0.1765 \tabularnewline
28 & -0.06 & -0.04758 & -0.01242 \tabularnewline
29 &  0.05 & -0.05831 &  0.1083 \tabularnewline
30 & -0.22 & -0.1358 & -0.08416 \tabularnewline
31 & -0.09 & -0.1253 &  0.03534 \tabularnewline
32 & -0.27 & -0.1769 & -0.09308 \tabularnewline
33 & -0.43 & -0.2754 & -0.1546 \tabularnewline
34 & -0.29 & -0.1419 & -0.1481 \tabularnewline
35 & -0.42 & -0.3006 & -0.1194 \tabularnewline
36 & -0.22 & -0.124 & -0.09602 \tabularnewline
37 & -0.23 & -0.04719 & -0.1828 \tabularnewline
38 & -0.07 & -0.2136 &  0.1436 \tabularnewline
39 & -0.1 & -0.2117 &  0.1117 \tabularnewline
40 & -0.11 & -0.1414 &  0.03139 \tabularnewline
41 & -0.04 & -0.09258 &  0.05258 \tabularnewline
42 & -0.01 & -0.07827 &  0.06827 \tabularnewline
43 & -0.04 & -0.1526 &  0.1126 \tabularnewline
44 & -0.05 & -0.08851 &  0.03851 \tabularnewline
45 &  0.09 &  0.06659 &  0.02341 \tabularnewline
46 &  0.02 &  0.1443 & -0.1243 \tabularnewline
47 &  0.08 &  0.115 & -0.035 \tabularnewline
48 &  0.16 &  0.1396 &  0.02036 \tabularnewline
49 &  0.07 &  0.2142 & -0.1442 \tabularnewline
50 &  0.01 & -0.04173 &  0.05173 \tabularnewline
51 &  0 & -0.08019 &  0.08019 \tabularnewline
52 & -0.32 & -0.03643 & -0.2836 \tabularnewline
53 & -0.05 & -0.1186 &  0.0686 \tabularnewline
54 &  0.08 &  0.02369 &  0.05631 \tabularnewline
55 &  0.04 &  0.03855 &  0.001445 \tabularnewline
56 &  0.19 &  0.1779 &  0.01206 \tabularnewline
57 &  0.11 &  0.1998 & -0.08985 \tabularnewline
58 &  0.16 &  0.1665 & -0.006511 \tabularnewline
59 &  0.23 &  0.3061 & -0.0761 \tabularnewline
60 &  0.22 &  0.1381 &  0.08185 \tabularnewline
61 &  0.37 &  0.3699 &  5.717e-05 \tabularnewline
62 &  0.15 &  0.2325 & -0.08254 \tabularnewline
63 &  0.16 &  0.1579 &  0.002125 \tabularnewline
64 &  0.76 &  0.5932 &  0.1668 \tabularnewline
65 &  0.19 &  0.2528 & -0.06281 \tabularnewline
66 &  0.08 &  0.1956 & -0.1156 \tabularnewline
67 & -0.11 &  0.01086 & -0.1209 \tabularnewline
68 &  0.04 &  0.06358 & -0.02358 \tabularnewline
69 &  0.26 &  0.2136 &  0.04644 \tabularnewline
70 &  0.18 &  0.1815 & -0.001514 \tabularnewline
71 & -0.01 &  0.0685 & -0.0785 \tabularnewline
72 &  0.04 & -0.07486 &  0.1149 \tabularnewline
73 &  0 & -0.047 &  0.047 \tabularnewline
74 & -0.03 &  0.03105 & -0.06105 \tabularnewline
75 & -0.21 & -0.1889 & -0.02115 \tabularnewline
76 & -0.27 & -0.3184 &  0.0484 \tabularnewline
77 & -0.19 & -0.1371 & -0.05289 \tabularnewline
78 & -0.14 & -0.1558 &  0.01576 \tabularnewline
79 &  0.1 &  0.07033 &  0.02967 \tabularnewline
80 & -0.15 & -0.1182 & -0.03181 \tabularnewline
81 & -0.16 & -0.2429 &  0.0829 \tabularnewline
82 & -0.05 & -0.1665 &  0.1165 \tabularnewline
83 & -0.08 & -0.08202 &  0.002018 \tabularnewline
84 & -0.27 & -0.1546 & -0.1154 \tabularnewline
85 & -0.09 & -0.2101 &  0.1201 \tabularnewline
86 &  0.05 & -0.0124 &  0.0624 \tabularnewline
87 &  0.04 &  0.128 & -0.08799 \tabularnewline
88 & -0.12 & -0.07284 & -0.04716 \tabularnewline
89 &  0.21 &  0.2673 & -0.05727 \tabularnewline
90 &  0.13 &  0.2617 & -0.1317 \tabularnewline
91 &  0.1 &  0.2145 & -0.1145 \tabularnewline
92 &  0.25 &  0.2351 &  0.0149 \tabularnewline
93 & -0.02 &  0.04423 & -0.06423 \tabularnewline
94 &  0.04 & -0.009822 &  0.04982 \tabularnewline
95 &  0.29 &  0.131 &  0.159 \tabularnewline
96 &  0.35 &  0.2634 &  0.08665 \tabularnewline
97 &  0.27 &  0.2385 &  0.03153 \tabularnewline
98 &  0.22 &  0.3226 & -0.1026 \tabularnewline
99 &  0.28 &  0.3242 & -0.04418 \tabularnewline
100 &  0.52 &  0.4483 &  0.07167 \tabularnewline
101 &  0.1 &  0.173 & -0.07296 \tabularnewline
102 &  0.25 &  0.249 &  0.0009514 \tabularnewline
103 &  0.28 &  0.1619 &  0.1181 \tabularnewline
104 &  0.16 &  0.1626 & -0.002609 \tabularnewline
105 &  0.39 &  0.3218 &  0.06818 \tabularnewline
106 &  0.24 &  0.1093 &  0.1307 \tabularnewline
107 & -0.02 &  0.04156 & -0.06156 \tabularnewline
108 & -0.08 & -0.04662 & -0.03338 \tabularnewline
109 & -0.15 & -0.1414 & -0.008558 \tabularnewline
110 & -0.02 & -0.06724 &  0.04724 \tabularnewline
111 & -0.1 & -0.03828 & -0.06172 \tabularnewline
112 & -0.19 & -0.2032 &  0.01323 \tabularnewline
113 & -0.29 & -0.1711 & -0.1189 \tabularnewline
114 & -0.3 & -0.2813 & -0.01871 \tabularnewline
115 & -0.36 & -0.3606 &  0.0006072 \tabularnewline
116 & -0.31 & -0.326 &  0.01596 \tabularnewline
117 & -0.41 & -0.335 & -0.07501 \tabularnewline
118 & -0.33 & -0.3222 & -0.007781 \tabularnewline
119 & -0.18 & -0.2594 &  0.07938 \tabularnewline
120 & -0.12 & -0.1862 &  0.06622 \tabularnewline
121 & -0.08 & -0.1086 &  0.02864 \tabularnewline
122 & -0.14 & -0.1365 & -0.003491 \tabularnewline
123 & -0.24 & -0.1255 & -0.1145 \tabularnewline
124 & -0.15 & -0.2105 &  0.06047 \tabularnewline
125 &  0.19 &  0.2081 & -0.01809 \tabularnewline
126 &  0.22 &  0.09612 &  0.1239 \tabularnewline
127 &  0.07 &  0.1338 & -0.06383 \tabularnewline
128 &  0.03 & -0.001251 &  0.03125 \tabularnewline
129 &  0.02 &  0.01425 &  0.005754 \tabularnewline
130 &  0.1 &  0.08155 &  0.01845 \tabularnewline
131 &  0.04 & -0.003543 &  0.04354 \tabularnewline
132 & -0.09 & -0.008163 & -0.08184 \tabularnewline
133 & -0.11 & -0.08601 & -0.02399 \tabularnewline
134 & -0.18 & -0.01179 & -0.1682 \tabularnewline
135 &  0.17 &  0.1978 & -0.02783 \tabularnewline
136 & -0.09 & -0.01519 & -0.07481 \tabularnewline
137 &  0.1 &  0.1393 & -0.03926 \tabularnewline
138 & -0.08 & -0.05496 & -0.02504 \tabularnewline
139 &  0.17 &  0.145 &  0.02496 \tabularnewline
140 &  0.14 &  0.1404 & -0.0004103 \tabularnewline
141 &  0.18 &  0.0848 &  0.0952 \tabularnewline
142 &  0.08 & -0.02688 &  0.1069 \tabularnewline
143 &  0.16 &  0.1451 &  0.01486 \tabularnewline
144 &  0.22 &  0.1866 &  0.03342 \tabularnewline
145 &  0.47 &  0.3479 &  0.1221 \tabularnewline
146 &  0.28 &  0.2363 &  0.04365 \tabularnewline
147 &  0.36 &  0.3239 &  0.03611 \tabularnewline
148 &  0.35 &  0.3479 &  0.002059 \tabularnewline
149 &  0.25 &  0.1932 &  0.05679 \tabularnewline
150 &  0.12 &  0.1662 & -0.04615 \tabularnewline
151 &  0.04 &  0.0688 & -0.0288 \tabularnewline
152 & -0.02 &  0.02849 & -0.04849 \tabularnewline
153 &  0.07 &  0.08268 & -0.01268 \tabularnewline
154 & -0.02 &  0.01018 & -0.03018 \tabularnewline
155 &  0.01 & -0.07326 &  0.08326 \tabularnewline
156 &  0.05 &  0.02278 &  0.02722 \tabularnewline
157 & -0.17 & -0.2307 &  0.06072 \tabularnewline
158 & -0.14 & -0.2227 &  0.08274 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286176&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] 0.09[/C][C] 0.1886[/C][C]-0.09855[/C][/ROW]
[ROW][C]2[/C][C] 0.07[/C][C] 0.05703[/C][C] 0.01297[/C][/ROW]
[ROW][C]3[/C][C] 0.22[/C][C] 0.221[/C][C]-0.0009508[/C][/ROW]
[ROW][C]4[/C][C] 0.09[/C][C] 0.08795[/C][C] 0.002049[/C][/ROW]
[ROW][C]5[/C][C] 0.39[/C][C] 0.2177[/C][C] 0.1723[/C][/ROW]
[ROW][C]6[/C][C] 0.27[/C][C] 0.2233[/C][C] 0.04673[/C][/ROW]
[ROW][C]7[/C][C] 0.25[/C][C] 0.2824[/C][C]-0.03236[/C][/ROW]
[ROW][C]8[/C][C] 0.25[/C][C] 0.2491[/C][C] 0.0009022[/C][/ROW]
[ROW][C]9[/C][C] 0.12[/C][C] 0.1168[/C][C] 0.003184[/C][/ROW]
[ROW][C]10[/C][C] 0.04[/C][C] 0.1355[/C][C]-0.09546[/C][/ROW]
[ROW][C]11[/C][C]-0.02[/C][C] 0.06187[/C][C]-0.08187[/C][/ROW]
[ROW][C]12[/C][C] 0.17[/C][C] 0.09178[/C][C] 0.07822[/C][/ROW]
[ROW][C]13[/C][C] 0.31[/C][C] 0.2663[/C][C] 0.04365[/C][/ROW]
[ROW][C]14[/C][C] 0.1[/C][C] 0.07585[/C][C] 0.02415[/C][/ROW]
[ROW][C]15[/C][C] 0.02[/C][C] 0.06839[/C][C]-0.04839[/C][/ROW]
[ROW][C]16[/C][C] 0.09[/C][C] 0.06805[/C][C] 0.02195[/C][/ROW]
[ROW][C]17[/C][C]-0.36[/C][C]-0.3236[/C][C]-0.03644[/C][/ROW]
[ROW][C]18[/C][C]-0.02[/C][C]-0.1294[/C][C] 0.1094[/C][/ROW]
[ROW][C]19[/C][C]-0.01[/C][C]-0.04757[/C][C] 0.03757[/C][/ROW]
[ROW][C]20[/C][C] 0.11[/C][C] 0.02361[/C][C] 0.08639[/C][/ROW]
[ROW][C]21[/C][C] 0.09[/C][C] 0.01867[/C][C] 0.07133[/C][/ROW]
[ROW][C]22[/C][C] 0.02[/C][C] 0.02846[/C][C]-0.008461[/C][/ROW]
[ROW][C]23[/C][C] 0.13[/C][C] 0.05957[/C][C] 0.07043[/C][/ROW]
[ROW][C]24[/C][C]-0.18[/C][C] 0.002131[/C][C]-0.1821[/C][/ROW]
[ROW][C]25[/C][C]-0.29[/C][C]-0.2943[/C][C] 0.00433[/C][/ROW]
[ROW][C]26[/C][C]-0.19[/C][C]-0.1394[/C][C]-0.05059[/C][/ROW]
[ROW][C]27[/C][C] 0.03[/C][C]-0.1465[/C][C] 0.1765[/C][/ROW]
[ROW][C]28[/C][C]-0.06[/C][C]-0.04758[/C][C]-0.01242[/C][/ROW]
[ROW][C]29[/C][C] 0.05[/C][C]-0.05831[/C][C] 0.1083[/C][/ROW]
[ROW][C]30[/C][C]-0.22[/C][C]-0.1358[/C][C]-0.08416[/C][/ROW]
[ROW][C]31[/C][C]-0.09[/C][C]-0.1253[/C][C] 0.03534[/C][/ROW]
[ROW][C]32[/C][C]-0.27[/C][C]-0.1769[/C][C]-0.09308[/C][/ROW]
[ROW][C]33[/C][C]-0.43[/C][C]-0.2754[/C][C]-0.1546[/C][/ROW]
[ROW][C]34[/C][C]-0.29[/C][C]-0.1419[/C][C]-0.1481[/C][/ROW]
[ROW][C]35[/C][C]-0.42[/C][C]-0.3006[/C][C]-0.1194[/C][/ROW]
[ROW][C]36[/C][C]-0.22[/C][C]-0.124[/C][C]-0.09602[/C][/ROW]
[ROW][C]37[/C][C]-0.23[/C][C]-0.04719[/C][C]-0.1828[/C][/ROW]
[ROW][C]38[/C][C]-0.07[/C][C]-0.2136[/C][C] 0.1436[/C][/ROW]
[ROW][C]39[/C][C]-0.1[/C][C]-0.2117[/C][C] 0.1117[/C][/ROW]
[ROW][C]40[/C][C]-0.11[/C][C]-0.1414[/C][C] 0.03139[/C][/ROW]
[ROW][C]41[/C][C]-0.04[/C][C]-0.09258[/C][C] 0.05258[/C][/ROW]
[ROW][C]42[/C][C]-0.01[/C][C]-0.07827[/C][C] 0.06827[/C][/ROW]
[ROW][C]43[/C][C]-0.04[/C][C]-0.1526[/C][C] 0.1126[/C][/ROW]
[ROW][C]44[/C][C]-0.05[/C][C]-0.08851[/C][C] 0.03851[/C][/ROW]
[ROW][C]45[/C][C] 0.09[/C][C] 0.06659[/C][C] 0.02341[/C][/ROW]
[ROW][C]46[/C][C] 0.02[/C][C] 0.1443[/C][C]-0.1243[/C][/ROW]
[ROW][C]47[/C][C] 0.08[/C][C] 0.115[/C][C]-0.035[/C][/ROW]
[ROW][C]48[/C][C] 0.16[/C][C] 0.1396[/C][C] 0.02036[/C][/ROW]
[ROW][C]49[/C][C] 0.07[/C][C] 0.2142[/C][C]-0.1442[/C][/ROW]
[ROW][C]50[/C][C] 0.01[/C][C]-0.04173[/C][C] 0.05173[/C][/ROW]
[ROW][C]51[/C][C] 0[/C][C]-0.08019[/C][C] 0.08019[/C][/ROW]
[ROW][C]52[/C][C]-0.32[/C][C]-0.03643[/C][C]-0.2836[/C][/ROW]
[ROW][C]53[/C][C]-0.05[/C][C]-0.1186[/C][C] 0.0686[/C][/ROW]
[ROW][C]54[/C][C] 0.08[/C][C] 0.02369[/C][C] 0.05631[/C][/ROW]
[ROW][C]55[/C][C] 0.04[/C][C] 0.03855[/C][C] 0.001445[/C][/ROW]
[ROW][C]56[/C][C] 0.19[/C][C] 0.1779[/C][C] 0.01206[/C][/ROW]
[ROW][C]57[/C][C] 0.11[/C][C] 0.1998[/C][C]-0.08985[/C][/ROW]
[ROW][C]58[/C][C] 0.16[/C][C] 0.1665[/C][C]-0.006511[/C][/ROW]
[ROW][C]59[/C][C] 0.23[/C][C] 0.3061[/C][C]-0.0761[/C][/ROW]
[ROW][C]60[/C][C] 0.22[/C][C] 0.1381[/C][C] 0.08185[/C][/ROW]
[ROW][C]61[/C][C] 0.37[/C][C] 0.3699[/C][C] 5.717e-05[/C][/ROW]
[ROW][C]62[/C][C] 0.15[/C][C] 0.2325[/C][C]-0.08254[/C][/ROW]
[ROW][C]63[/C][C] 0.16[/C][C] 0.1579[/C][C] 0.002125[/C][/ROW]
[ROW][C]64[/C][C] 0.76[/C][C] 0.5932[/C][C] 0.1668[/C][/ROW]
[ROW][C]65[/C][C] 0.19[/C][C] 0.2528[/C][C]-0.06281[/C][/ROW]
[ROW][C]66[/C][C] 0.08[/C][C] 0.1956[/C][C]-0.1156[/C][/ROW]
[ROW][C]67[/C][C]-0.11[/C][C] 0.01086[/C][C]-0.1209[/C][/ROW]
[ROW][C]68[/C][C] 0.04[/C][C] 0.06358[/C][C]-0.02358[/C][/ROW]
[ROW][C]69[/C][C] 0.26[/C][C] 0.2136[/C][C] 0.04644[/C][/ROW]
[ROW][C]70[/C][C] 0.18[/C][C] 0.1815[/C][C]-0.001514[/C][/ROW]
[ROW][C]71[/C][C]-0.01[/C][C] 0.0685[/C][C]-0.0785[/C][/ROW]
[ROW][C]72[/C][C] 0.04[/C][C]-0.07486[/C][C] 0.1149[/C][/ROW]
[ROW][C]73[/C][C] 0[/C][C]-0.047[/C][C] 0.047[/C][/ROW]
[ROW][C]74[/C][C]-0.03[/C][C] 0.03105[/C][C]-0.06105[/C][/ROW]
[ROW][C]75[/C][C]-0.21[/C][C]-0.1889[/C][C]-0.02115[/C][/ROW]
[ROW][C]76[/C][C]-0.27[/C][C]-0.3184[/C][C] 0.0484[/C][/ROW]
[ROW][C]77[/C][C]-0.19[/C][C]-0.1371[/C][C]-0.05289[/C][/ROW]
[ROW][C]78[/C][C]-0.14[/C][C]-0.1558[/C][C] 0.01576[/C][/ROW]
[ROW][C]79[/C][C] 0.1[/C][C] 0.07033[/C][C] 0.02967[/C][/ROW]
[ROW][C]80[/C][C]-0.15[/C][C]-0.1182[/C][C]-0.03181[/C][/ROW]
[ROW][C]81[/C][C]-0.16[/C][C]-0.2429[/C][C] 0.0829[/C][/ROW]
[ROW][C]82[/C][C]-0.05[/C][C]-0.1665[/C][C] 0.1165[/C][/ROW]
[ROW][C]83[/C][C]-0.08[/C][C]-0.08202[/C][C] 0.002018[/C][/ROW]
[ROW][C]84[/C][C]-0.27[/C][C]-0.1546[/C][C]-0.1154[/C][/ROW]
[ROW][C]85[/C][C]-0.09[/C][C]-0.2101[/C][C] 0.1201[/C][/ROW]
[ROW][C]86[/C][C] 0.05[/C][C]-0.0124[/C][C] 0.0624[/C][/ROW]
[ROW][C]87[/C][C] 0.04[/C][C] 0.128[/C][C]-0.08799[/C][/ROW]
[ROW][C]88[/C][C]-0.12[/C][C]-0.07284[/C][C]-0.04716[/C][/ROW]
[ROW][C]89[/C][C] 0.21[/C][C] 0.2673[/C][C]-0.05727[/C][/ROW]
[ROW][C]90[/C][C] 0.13[/C][C] 0.2617[/C][C]-0.1317[/C][/ROW]
[ROW][C]91[/C][C] 0.1[/C][C] 0.2145[/C][C]-0.1145[/C][/ROW]
[ROW][C]92[/C][C] 0.25[/C][C] 0.2351[/C][C] 0.0149[/C][/ROW]
[ROW][C]93[/C][C]-0.02[/C][C] 0.04423[/C][C]-0.06423[/C][/ROW]
[ROW][C]94[/C][C] 0.04[/C][C]-0.009822[/C][C] 0.04982[/C][/ROW]
[ROW][C]95[/C][C] 0.29[/C][C] 0.131[/C][C] 0.159[/C][/ROW]
[ROW][C]96[/C][C] 0.35[/C][C] 0.2634[/C][C] 0.08665[/C][/ROW]
[ROW][C]97[/C][C] 0.27[/C][C] 0.2385[/C][C] 0.03153[/C][/ROW]
[ROW][C]98[/C][C] 0.22[/C][C] 0.3226[/C][C]-0.1026[/C][/ROW]
[ROW][C]99[/C][C] 0.28[/C][C] 0.3242[/C][C]-0.04418[/C][/ROW]
[ROW][C]100[/C][C] 0.52[/C][C] 0.4483[/C][C] 0.07167[/C][/ROW]
[ROW][C]101[/C][C] 0.1[/C][C] 0.173[/C][C]-0.07296[/C][/ROW]
[ROW][C]102[/C][C] 0.25[/C][C] 0.249[/C][C] 0.0009514[/C][/ROW]
[ROW][C]103[/C][C] 0.28[/C][C] 0.1619[/C][C] 0.1181[/C][/ROW]
[ROW][C]104[/C][C] 0.16[/C][C] 0.1626[/C][C]-0.002609[/C][/ROW]
[ROW][C]105[/C][C] 0.39[/C][C] 0.3218[/C][C] 0.06818[/C][/ROW]
[ROW][C]106[/C][C] 0.24[/C][C] 0.1093[/C][C] 0.1307[/C][/ROW]
[ROW][C]107[/C][C]-0.02[/C][C] 0.04156[/C][C]-0.06156[/C][/ROW]
[ROW][C]108[/C][C]-0.08[/C][C]-0.04662[/C][C]-0.03338[/C][/ROW]
[ROW][C]109[/C][C]-0.15[/C][C]-0.1414[/C][C]-0.008558[/C][/ROW]
[ROW][C]110[/C][C]-0.02[/C][C]-0.06724[/C][C] 0.04724[/C][/ROW]
[ROW][C]111[/C][C]-0.1[/C][C]-0.03828[/C][C]-0.06172[/C][/ROW]
[ROW][C]112[/C][C]-0.19[/C][C]-0.2032[/C][C] 0.01323[/C][/ROW]
[ROW][C]113[/C][C]-0.29[/C][C]-0.1711[/C][C]-0.1189[/C][/ROW]
[ROW][C]114[/C][C]-0.3[/C][C]-0.2813[/C][C]-0.01871[/C][/ROW]
[ROW][C]115[/C][C]-0.36[/C][C]-0.3606[/C][C] 0.0006072[/C][/ROW]
[ROW][C]116[/C][C]-0.31[/C][C]-0.326[/C][C] 0.01596[/C][/ROW]
[ROW][C]117[/C][C]-0.41[/C][C]-0.335[/C][C]-0.07501[/C][/ROW]
[ROW][C]118[/C][C]-0.33[/C][C]-0.3222[/C][C]-0.007781[/C][/ROW]
[ROW][C]119[/C][C]-0.18[/C][C]-0.2594[/C][C] 0.07938[/C][/ROW]
[ROW][C]120[/C][C]-0.12[/C][C]-0.1862[/C][C] 0.06622[/C][/ROW]
[ROW][C]121[/C][C]-0.08[/C][C]-0.1086[/C][C] 0.02864[/C][/ROW]
[ROW][C]122[/C][C]-0.14[/C][C]-0.1365[/C][C]-0.003491[/C][/ROW]
[ROW][C]123[/C][C]-0.24[/C][C]-0.1255[/C][C]-0.1145[/C][/ROW]
[ROW][C]124[/C][C]-0.15[/C][C]-0.2105[/C][C] 0.06047[/C][/ROW]
[ROW][C]125[/C][C] 0.19[/C][C] 0.2081[/C][C]-0.01809[/C][/ROW]
[ROW][C]126[/C][C] 0.22[/C][C] 0.09612[/C][C] 0.1239[/C][/ROW]
[ROW][C]127[/C][C] 0.07[/C][C] 0.1338[/C][C]-0.06383[/C][/ROW]
[ROW][C]128[/C][C] 0.03[/C][C]-0.001251[/C][C] 0.03125[/C][/ROW]
[ROW][C]129[/C][C] 0.02[/C][C] 0.01425[/C][C] 0.005754[/C][/ROW]
[ROW][C]130[/C][C] 0.1[/C][C] 0.08155[/C][C] 0.01845[/C][/ROW]
[ROW][C]131[/C][C] 0.04[/C][C]-0.003543[/C][C] 0.04354[/C][/ROW]
[ROW][C]132[/C][C]-0.09[/C][C]-0.008163[/C][C]-0.08184[/C][/ROW]
[ROW][C]133[/C][C]-0.11[/C][C]-0.08601[/C][C]-0.02399[/C][/ROW]
[ROW][C]134[/C][C]-0.18[/C][C]-0.01179[/C][C]-0.1682[/C][/ROW]
[ROW][C]135[/C][C] 0.17[/C][C] 0.1978[/C][C]-0.02783[/C][/ROW]
[ROW][C]136[/C][C]-0.09[/C][C]-0.01519[/C][C]-0.07481[/C][/ROW]
[ROW][C]137[/C][C] 0.1[/C][C] 0.1393[/C][C]-0.03926[/C][/ROW]
[ROW][C]138[/C][C]-0.08[/C][C]-0.05496[/C][C]-0.02504[/C][/ROW]
[ROW][C]139[/C][C] 0.17[/C][C] 0.145[/C][C] 0.02496[/C][/ROW]
[ROW][C]140[/C][C] 0.14[/C][C] 0.1404[/C][C]-0.0004103[/C][/ROW]
[ROW][C]141[/C][C] 0.18[/C][C] 0.0848[/C][C] 0.0952[/C][/ROW]
[ROW][C]142[/C][C] 0.08[/C][C]-0.02688[/C][C] 0.1069[/C][/ROW]
[ROW][C]143[/C][C] 0.16[/C][C] 0.1451[/C][C] 0.01486[/C][/ROW]
[ROW][C]144[/C][C] 0.22[/C][C] 0.1866[/C][C] 0.03342[/C][/ROW]
[ROW][C]145[/C][C] 0.47[/C][C] 0.3479[/C][C] 0.1221[/C][/ROW]
[ROW][C]146[/C][C] 0.28[/C][C] 0.2363[/C][C] 0.04365[/C][/ROW]
[ROW][C]147[/C][C] 0.36[/C][C] 0.3239[/C][C] 0.03611[/C][/ROW]
[ROW][C]148[/C][C] 0.35[/C][C] 0.3479[/C][C] 0.002059[/C][/ROW]
[ROW][C]149[/C][C] 0.25[/C][C] 0.1932[/C][C] 0.05679[/C][/ROW]
[ROW][C]150[/C][C] 0.12[/C][C] 0.1662[/C][C]-0.04615[/C][/ROW]
[ROW][C]151[/C][C] 0.04[/C][C] 0.0688[/C][C]-0.0288[/C][/ROW]
[ROW][C]152[/C][C]-0.02[/C][C] 0.02849[/C][C]-0.04849[/C][/ROW]
[ROW][C]153[/C][C] 0.07[/C][C] 0.08268[/C][C]-0.01268[/C][/ROW]
[ROW][C]154[/C][C]-0.02[/C][C] 0.01018[/C][C]-0.03018[/C][/ROW]
[ROW][C]155[/C][C] 0.01[/C][C]-0.07326[/C][C] 0.08326[/C][/ROW]
[ROW][C]156[/C][C] 0.05[/C][C] 0.02278[/C][C] 0.02722[/C][/ROW]
[ROW][C]157[/C][C]-0.17[/C][C]-0.2307[/C][C] 0.06072[/C][/ROW]
[ROW][C]158[/C][C]-0.14[/C][C]-0.2227[/C][C] 0.08274[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286176&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286176&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	0.09	0.1886	-0.09855
2	0.07	0.05703	0.01297
3	0.22	0.221	-0.0009508
4	0.09	0.08795	0.002049
5	0.39	0.2177	0.1723
6	0.27	0.2233	0.04673
7	0.25	0.2824	-0.03236
8	0.25	0.2491	0.0009022
9	0.12	0.1168	0.003184
10	0.04	0.1355	-0.09546
11	-0.02	0.06187	-0.08187
12	0.17	0.09178	0.07822
13	0.31	0.2663	0.04365
14	0.1	0.07585	0.02415
15	0.02	0.06839	-0.04839
16	0.09	0.06805	0.02195
17	-0.36	-0.3236	-0.03644
18	-0.02	-0.1294	0.1094
19	-0.01	-0.04757	0.03757
20	0.11	0.02361	0.08639
21	0.09	0.01867	0.07133
22	0.02	0.02846	-0.008461
23	0.13	0.05957	0.07043
24	-0.18	0.002131	-0.1821
25	-0.29	-0.2943	0.00433
26	-0.19	-0.1394	-0.05059
27	0.03	-0.1465	0.1765
28	-0.06	-0.04758	-0.01242
29	0.05	-0.05831	0.1083
30	-0.22	-0.1358	-0.08416
31	-0.09	-0.1253	0.03534
32	-0.27	-0.1769	-0.09308
33	-0.43	-0.2754	-0.1546
34	-0.29	-0.1419	-0.1481
35	-0.42	-0.3006	-0.1194
36	-0.22	-0.124	-0.09602
37	-0.23	-0.04719	-0.1828
38	-0.07	-0.2136	0.1436
39	-0.1	-0.2117	0.1117
40	-0.11	-0.1414	0.03139
41	-0.04	-0.09258	0.05258
42	-0.01	-0.07827	0.06827
43	-0.04	-0.1526	0.1126
44	-0.05	-0.08851	0.03851
45	0.09	0.06659	0.02341
46	0.02	0.1443	-0.1243
47	0.08	0.115	-0.035
48	0.16	0.1396	0.02036
49	0.07	0.2142	-0.1442
50	0.01	-0.04173	0.05173
51	0	-0.08019	0.08019
52	-0.32	-0.03643	-0.2836
53	-0.05	-0.1186	0.0686
54	0.08	0.02369	0.05631
55	0.04	0.03855	0.001445
56	0.19	0.1779	0.01206
57	0.11	0.1998	-0.08985
58	0.16	0.1665	-0.006511
59	0.23	0.3061	-0.0761
60	0.22	0.1381	0.08185
61	0.37	0.3699	5.717e-05
62	0.15	0.2325	-0.08254
63	0.16	0.1579	0.002125
64	0.76	0.5932	0.1668
65	0.19	0.2528	-0.06281
66	0.08	0.1956	-0.1156
67	-0.11	0.01086	-0.1209
68	0.04	0.06358	-0.02358
69	0.26	0.2136	0.04644
70	0.18	0.1815	-0.001514
71	-0.01	0.0685	-0.0785
72	0.04	-0.07486	0.1149
73	0	-0.047	0.047
74	-0.03	0.03105	-0.06105
75	-0.21	-0.1889	-0.02115
76	-0.27	-0.3184	0.0484
77	-0.19	-0.1371	-0.05289
78	-0.14	-0.1558	0.01576
79	0.1	0.07033	0.02967
80	-0.15	-0.1182	-0.03181
81	-0.16	-0.2429	0.0829
82	-0.05	-0.1665	0.1165
83	-0.08	-0.08202	0.002018
84	-0.27	-0.1546	-0.1154
85	-0.09	-0.2101	0.1201
86	0.05	-0.0124	0.0624
87	0.04	0.128	-0.08799
88	-0.12	-0.07284	-0.04716
89	0.21	0.2673	-0.05727
90	0.13	0.2617	-0.1317
91	0.1	0.2145	-0.1145
92	0.25	0.2351	0.0149
93	-0.02	0.04423	-0.06423
94	0.04	-0.009822	0.04982
95	0.29	0.131	0.159
96	0.35	0.2634	0.08665
97	0.27	0.2385	0.03153
98	0.22	0.3226	-0.1026
99	0.28	0.3242	-0.04418
100	0.52	0.4483	0.07167
101	0.1	0.173	-0.07296
102	0.25	0.249	0.0009514
103	0.28	0.1619	0.1181
104	0.16	0.1626	-0.002609
105	0.39	0.3218	0.06818
106	0.24	0.1093	0.1307
107	-0.02	0.04156	-0.06156
108	-0.08	-0.04662	-0.03338
109	-0.15	-0.1414	-0.008558
110	-0.02	-0.06724	0.04724
111	-0.1	-0.03828	-0.06172
112	-0.19	-0.2032	0.01323
113	-0.29	-0.1711	-0.1189
114	-0.3	-0.2813	-0.01871
115	-0.36	-0.3606	0.0006072
116	-0.31	-0.326	0.01596
117	-0.41	-0.335	-0.07501
118	-0.33	-0.3222	-0.007781
119	-0.18	-0.2594	0.07938
120	-0.12	-0.1862	0.06622
121	-0.08	-0.1086	0.02864
122	-0.14	-0.1365	-0.003491
123	-0.24	-0.1255	-0.1145
124	-0.15	-0.2105	0.06047
125	0.19	0.2081	-0.01809
126	0.22	0.09612	0.1239
127	0.07	0.1338	-0.06383
128	0.03	-0.001251	0.03125
129	0.02	0.01425	0.005754
130	0.1	0.08155	0.01845
131	0.04	-0.003543	0.04354
132	-0.09	-0.008163	-0.08184
133	-0.11	-0.08601	-0.02399
134	-0.18	-0.01179	-0.1682
135	0.17	0.1978	-0.02783
136	-0.09	-0.01519	-0.07481
137	0.1	0.1393	-0.03926
138	-0.08	-0.05496	-0.02504
139	0.17	0.145	0.02496
140	0.14	0.1404	-0.0004103
141	0.18	0.0848	0.0952
142	0.08	-0.02688	0.1069
143	0.16	0.1451	0.01486
144	0.22	0.1866	0.03342
145	0.47	0.3479	0.1221
146	0.28	0.2363	0.04365
147	0.36	0.3239	0.03611
148	0.35	0.3479	0.002059
149	0.25	0.1932	0.05679
150	0.12	0.1662	-0.04615
151	0.04	0.0688	-0.0288
152	-0.02	0.02849	-0.04849
153	0.07	0.08268	-0.01268
154	-0.02	0.01018	-0.03018
155	0.01	-0.07326	0.08326
156	0.05	0.02278	0.02722
157	-0.17	-0.2307	0.06072
158	-0.14	-0.2227	0.08274

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
66	0.7152	0.5697	0.2848
67	0.7778	0.4444	0.2222
68	0.6778	0.6445	0.3222
69	0.7476	0.5048	0.2524
70	0.8102	0.3797	0.1898
71	0.777	0.4459	0.223
72	0.7122	0.5756	0.2878
73	0.6185	0.763	0.3815
74	0.7841	0.4319	0.2159
75	0.7161	0.5678	0.2839
76	0.6574	0.6853	0.3426
77	0.7481	0.5038	0.2519
78	0.8518	0.2963	0.1482
79	0.8214	0.3573	0.1786
80	0.8495	0.301	0.1505
81	0.8934	0.2132	0.1066
82	0.9618	0.07649	0.03825
83	0.9906	0.01876	0.009382
84	0.9905	0.01899	0.009497
85	0.9928	0.01439	0.007198
86	0.9886	0.02289	0.01145
87	0.9898	0.02048	0.01024
88	0.9779	0.0442	0.0221
89	0.9814	0.03725	0.01863
90	0.9546	0.09089	0.04545
91	0.9309	0.1381	0.06905
92	0.8599	0.2801	0.1401

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
66 &  0.7152 &  0.5697 &  0.2848 \tabularnewline
67 &  0.7778 &  0.4444 &  0.2222 \tabularnewline
68 &  0.6778 &  0.6445 &  0.3222 \tabularnewline
69 &  0.7476 &  0.5048 &  0.2524 \tabularnewline
70 &  0.8102 &  0.3797 &  0.1898 \tabularnewline
71 &  0.777 &  0.4459 &  0.223 \tabularnewline
72 &  0.7122 &  0.5756 &  0.2878 \tabularnewline
73 &  0.6185 &  0.763 &  0.3815 \tabularnewline
74 &  0.7841 &  0.4319 &  0.2159 \tabularnewline
75 &  0.7161 &  0.5678 &  0.2839 \tabularnewline
76 &  0.6574 &  0.6853 &  0.3426 \tabularnewline
77 &  0.7481 &  0.5038 &  0.2519 \tabularnewline
78 &  0.8518 &  0.2963 &  0.1482 \tabularnewline
79 &  0.8214 &  0.3573 &  0.1786 \tabularnewline
80 &  0.8495 &  0.301 &  0.1505 \tabularnewline
81 &  0.8934 &  0.2132 &  0.1066 \tabularnewline
82 &  0.9618 &  0.07649 &  0.03825 \tabularnewline
83 &  0.9906 &  0.01876 &  0.009382 \tabularnewline
84 &  0.9905 &  0.01899 &  0.009497 \tabularnewline
85 &  0.9928 &  0.01439 &  0.007198 \tabularnewline
86 &  0.9886 &  0.02289 &  0.01145 \tabularnewline
87 &  0.9898 &  0.02048 &  0.01024 \tabularnewline
88 &  0.9779 &  0.0442 &  0.0221 \tabularnewline
89 &  0.9814 &  0.03725 &  0.01863 \tabularnewline
90 &  0.9546 &  0.09089 &  0.04545 \tabularnewline
91 &  0.9309 &  0.1381 &  0.06905 \tabularnewline
92 &  0.8599 &  0.2801 &  0.1401 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286176&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]66[/C][C] 0.7152[/C][C] 0.5697[/C][C] 0.2848[/C][/ROW]
[ROW][C]67[/C][C] 0.7778[/C][C] 0.4444[/C][C] 0.2222[/C][/ROW]
[ROW][C]68[/C][C] 0.6778[/C][C] 0.6445[/C][C] 0.3222[/C][/ROW]
[ROW][C]69[/C][C] 0.7476[/C][C] 0.5048[/C][C] 0.2524[/C][/ROW]
[ROW][C]70[/C][C] 0.8102[/C][C] 0.3797[/C][C] 0.1898[/C][/ROW]
[ROW][C]71[/C][C] 0.777[/C][C] 0.4459[/C][C] 0.223[/C][/ROW]
[ROW][C]72[/C][C] 0.7122[/C][C] 0.5756[/C][C] 0.2878[/C][/ROW]
[ROW][C]73[/C][C] 0.6185[/C][C] 0.763[/C][C] 0.3815[/C][/ROW]
[ROW][C]74[/C][C] 0.7841[/C][C] 0.4319[/C][C] 0.2159[/C][/ROW]
[ROW][C]75[/C][C] 0.7161[/C][C] 0.5678[/C][C] 0.2839[/C][/ROW]
[ROW][C]76[/C][C] 0.6574[/C][C] 0.6853[/C][C] 0.3426[/C][/ROW]
[ROW][C]77[/C][C] 0.7481[/C][C] 0.5038[/C][C] 0.2519[/C][/ROW]
[ROW][C]78[/C][C] 0.8518[/C][C] 0.2963[/C][C] 0.1482[/C][/ROW]
[ROW][C]79[/C][C] 0.8214[/C][C] 0.3573[/C][C] 0.1786[/C][/ROW]
[ROW][C]80[/C][C] 0.8495[/C][C] 0.301[/C][C] 0.1505[/C][/ROW]
[ROW][C]81[/C][C] 0.8934[/C][C] 0.2132[/C][C] 0.1066[/C][/ROW]
[ROW][C]82[/C][C] 0.9618[/C][C] 0.07649[/C][C] 0.03825[/C][/ROW]
[ROW][C]83[/C][C] 0.9906[/C][C] 0.01876[/C][C] 0.009382[/C][/ROW]
[ROW][C]84[/C][C] 0.9905[/C][C] 0.01899[/C][C] 0.009497[/C][/ROW]
[ROW][C]85[/C][C] 0.9928[/C][C] 0.01439[/C][C] 0.007198[/C][/ROW]
[ROW][C]86[/C][C] 0.9886[/C][C] 0.02289[/C][C] 0.01145[/C][/ROW]
[ROW][C]87[/C][C] 0.9898[/C][C] 0.02048[/C][C] 0.01024[/C][/ROW]
[ROW][C]88[/C][C] 0.9779[/C][C] 0.0442[/C][C] 0.0221[/C][/ROW]
[ROW][C]89[/C][C] 0.9814[/C][C] 0.03725[/C][C] 0.01863[/C][/ROW]
[ROW][C]90[/C][C] 0.9546[/C][C] 0.09089[/C][C] 0.04545[/C][/ROW]
[ROW][C]91[/C][C] 0.9309[/C][C] 0.1381[/C][C] 0.06905[/C][/ROW]
[ROW][C]92[/C][C] 0.8599[/C][C] 0.2801[/C][C] 0.1401[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286176&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286176&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
66	0.7152	0.5697	0.2848
67	0.7778	0.4444	0.2222
68	0.6778	0.6445	0.3222
69	0.7476	0.5048	0.2524
70	0.8102	0.3797	0.1898
71	0.777	0.4459	0.223
72	0.7122	0.5756	0.2878
73	0.6185	0.763	0.3815
74	0.7841	0.4319	0.2159
75	0.7161	0.5678	0.2839
76	0.6574	0.6853	0.3426
77	0.7481	0.5038	0.2519
78	0.8518	0.2963	0.1482
79	0.8214	0.3573	0.1786
80	0.8495	0.301	0.1505
81	0.8934	0.2132	0.1066
82	0.9618	0.07649	0.03825
83	0.9906	0.01876	0.009382
84	0.9905	0.01899	0.009497
85	0.9928	0.01439	0.007198
86	0.9886	0.02289	0.01145
87	0.9898	0.02048	0.01024
88	0.9779	0.0442	0.0221
89	0.9814	0.03725	0.01863
90	0.9546	0.09089	0.04545
91	0.9309	0.1381	0.06905
92	0.8599	0.2801	0.1401

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	7	0.259259	NOK
10% type I error level	9	0.333333	NOK

\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 & 0 &  0 & OK \tabularnewline
5% type I error level & 7 & 0.259259 & NOK \tabularnewline
10% type I error level & 9 & 0.333333 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286176&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]0[/C][C] 0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]7[/C][C]0.259259[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]9[/C][C]0.333333[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286176&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286176&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	7	0.259259	NOK
10% type I error level	9	0.333333	NOK

Figure 1

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Figure 2

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Figure 3

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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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Postscript link

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Figure 8

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Figure 9

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Figure 10

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Seasonal Differences (s=12) ; par4 = 1 ; par5 = 36 ;

Parameters (R input):

par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Seasonal Differences (s=12) ; par4 = 10 ; par5 = 40 ;

R code (references can be found in the software module):

par5 <- '42'
par4 <- '10'
par3 <- 'Seasonal Differences (s=12)'
par2 <- 'Include Monthly Dummies'
par1 <- '1'
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
mywarning <- ''
par1 <- as.numeric(par1)
if(is.na(par1)) {
par1 <- 1
mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
}
if (par4=='') par4 <- 0
par4 <- as.numeric(par4)
if (par5=='') par5 <- 0
par5 <- as.numeric(par5)
x <- na.omit(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'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'Seasonal Differences (s=12)'){
(n <- n - 12)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+12,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'First and Seasonal Differences (s=12)'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
(n <- n - 12)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+12,j] - x[i,j]
}
}
x <- x2
}
if(par4 > 0) {
x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
for (i in 1:(n-par4)) {
for (j in 1:par4) {
x2[i,j] <- x[i+par4-j,par1]
}
}
x <- cbind(x[(par4+1):n,], x2)
n <- n - par4
}
if(par5 > 0) {
x2 <- array(0, dim=c(n-par5*12,par5), dimnames=list(1:(n-par5*12), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
for (i in 1:(n-par5*12)) {
for (j in 1:par5) {
x2[i,j] <- x[i+par5*12-j*12,par1]
}
}
x <- cbind(x[(par5*12+1):n,], x2)
n <- n - par5*12
}
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[n,]))
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
(k <- length(x[n,]))
head(x)
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, mywarning)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
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,formatC(signif(mysum$sigma,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
if(n < 200) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
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,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code