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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Sun, 13 Dec 2015 19:45:12 +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/t1450036140uvlrlxavb2b04uz.htm/, Retrieved Sat, 18 May 2024 14:40:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286233, Retrieved Sat, 18 May 2024 14:40:29 +0000

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Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Pearson Correlation] [] [2015-09-24 13:12:15] [32b17a345b130fdf5cc88718ed94a974]
- R  D  [Pearson Correlation] [Verband Temperatu...] [2015-11-29 15:35:01] [2fea329c6e322b1612c5dc504f90c0ef]
- RMPD      [Multiple Regression] [Orkanen] [2015-12-13 19:45:12] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- R PD        [Multiple Regression] [Orkanen] [2015-12-17 08:40:36] [74be16979710d4c4e7c6647856088456] 

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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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286233&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286233&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286233&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	'Gertrude Mary Cox' @ cox.wessa.net

Multiple Linear Regression - Estimated Regression Equation
(1-B12)Orkanen[t] = -0.0291851 + 0.499062`(1-B12)Temperatuur`[t] -6.83738e-05`(1-B12)Orkanen(t-1)`[t] -0.0732503`(1-B12)Orkanen(t-2)`[t] + 0.0596902`(1-B12)Orkanen(t-3)`[t] -0.00604279`(1-B12)Orkanen(t-4)`[t] + 0.0853961`(1-B12)Orkanen(t-5)`[t] + 0.0307353`(1-B12)Orkanen(t-6)`[t] + 0.0197191`(1-B12)Orkanen(t-7)`[t] -0.055251`(1-B12)Orkanen(t-8)`[t] + 0.0892998`(1-B12)Orkanen(t-9)`[t] -0.0762715`(1-B12)Orkanen(t-10)`[t] -0.215963`(1-B12)Orkanen(t-11)`[t] -0.694369`(1-B12)Orkanen(t-1s)`[t] -0.713467`(1-B12)Orkanen(t-2s)`[t] -1.02599`(1-B12)Orkanen(t-3s)`[t] -1.06719`(1-B12)Orkanen(t-4s)`[t] -0.933927`(1-B12)Orkanen(t-5s)`[t] -0.794294`(1-B12)Orkanen(t-6s)`[t] -0.857933`(1-B12)Orkanen(t-7s)`[t] -0.836123`(1-B12)Orkanen(t-8s)`[t] -0.591552`(1-B12)Orkanen(t-9s)`[t] -0.631642`(1-B12)Orkanen(t-10s)`[t] -0.715453`(1-B12)Orkanen(t-11s)`[t] -0.74568`(1-B12)Orkanen(t-12s)`[t] -1.60581`(1-B12)Orkanen(t-13s)`[t] -0.994833`(1-B12)Orkanen(t-14s)`[t] -1.08851`(1-B12)Orkanen(t-15s)`[t] -1.15167`(1-B12)Orkanen(t-16s)`[t] -0.548099`(1-B12)Orkanen(t-17s)`[t] -0.766823`(1-B12)Orkanen(t-18s)`[t] -0.665087`(1-B12)Orkanen(t-19s)`[t] -0.233681`(1-B12)Orkanen(t-20s)`[t] -0.111125`(1-B12)Orkanen(t-21s)`[t] + 0.350918`(1-B12)Orkanen(t-22s)`[t] + 0.248532`(1-B12)Orkanen(t-23s)`[t] + 0.234795`(1-B12)Orkanen(t-24s)`[t] + 0.184271`(1-B12)Orkanen(t-25s)`[t] + 0.303686`(1-B12)Orkanen(t-26s)`[t] + 0.318165`(1-B12)Orkanen(t-27s)`[t] + 0.165039`(1-B12)Orkanen(t-28s)`[t] + 0.345182`(1-B12)Orkanen(t-29s)`[t] + 0.261451`(1-B12)Orkanen(t-30s)`[t] + 0.506132`(1-B12)Orkanen(t-31s)`[t] + 0.651642`(1-B12)Orkanen(t-32s)`[t] + 0.395417`(1-B12)Orkanen(t-33s)`[t] + 0.477226`(1-B12)Orkanen(t-34s)`[t] + 0.350592`(1-B12)Orkanen(t-35s)`[t] + 0.356152`(1-B12)Orkanen(t-36s)`[t] + 0.522564`(1-B12)Orkanen(t-37s)`[t] + 0.347655`(1-B12)Orkanen(t-38s)`[t] + 0.45088`(1-B12)Orkanen(t-39s)`[t] + 0.207965`(1-B12)Orkanen(t-40s)`[t] + 0.260469`(1-B12)Orkanen(t-41s)`[t] -0.123536M1[t] -0.096958M2[t] + 0.0200826M3[t] -0.0223232M4[t] + 0.0698393M5[t] -0.171164M6[t] + 0.372537M7[t] + 0.153392M8[t] + 0.273484M9[t] + 0.915855M10[t] + 0.749511M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
(1-B12)Orkanen[t] =  -0.0291851 +  0.499062`(1-B12)Temperatuur`[t] -6.83738e-05`(1-B12)Orkanen(t-1)`[t] -0.0732503`(1-B12)Orkanen(t-2)`[t] +  0.0596902`(1-B12)Orkanen(t-3)`[t] -0.00604279`(1-B12)Orkanen(t-4)`[t] +  0.0853961`(1-B12)Orkanen(t-5)`[t] +  0.0307353`(1-B12)Orkanen(t-6)`[t] +  0.0197191`(1-B12)Orkanen(t-7)`[t] -0.055251`(1-B12)Orkanen(t-8)`[t] +  0.0892998`(1-B12)Orkanen(t-9)`[t] -0.0762715`(1-B12)Orkanen(t-10)`[t] -0.215963`(1-B12)Orkanen(t-11)`[t] -0.694369`(1-B12)Orkanen(t-1s)`[t] -0.713467`(1-B12)Orkanen(t-2s)`[t] -1.02599`(1-B12)Orkanen(t-3s)`[t] -1.06719`(1-B12)Orkanen(t-4s)`[t] -0.933927`(1-B12)Orkanen(t-5s)`[t] -0.794294`(1-B12)Orkanen(t-6s)`[t] -0.857933`(1-B12)Orkanen(t-7s)`[t] -0.836123`(1-B12)Orkanen(t-8s)`[t] -0.591552`(1-B12)Orkanen(t-9s)`[t] -0.631642`(1-B12)Orkanen(t-10s)`[t] -0.715453`(1-B12)Orkanen(t-11s)`[t] -0.74568`(1-B12)Orkanen(t-12s)`[t] -1.60581`(1-B12)Orkanen(t-13s)`[t] -0.994833`(1-B12)Orkanen(t-14s)`[t] -1.08851`(1-B12)Orkanen(t-15s)`[t] -1.15167`(1-B12)Orkanen(t-16s)`[t] -0.548099`(1-B12)Orkanen(t-17s)`[t] -0.766823`(1-B12)Orkanen(t-18s)`[t] -0.665087`(1-B12)Orkanen(t-19s)`[t] -0.233681`(1-B12)Orkanen(t-20s)`[t] -0.111125`(1-B12)Orkanen(t-21s)`[t] +  0.350918`(1-B12)Orkanen(t-22s)`[t] +  0.248532`(1-B12)Orkanen(t-23s)`[t] +  0.234795`(1-B12)Orkanen(t-24s)`[t] +  0.184271`(1-B12)Orkanen(t-25s)`[t] +  0.303686`(1-B12)Orkanen(t-26s)`[t] +  0.318165`(1-B12)Orkanen(t-27s)`[t] +  0.165039`(1-B12)Orkanen(t-28s)`[t] +  0.345182`(1-B12)Orkanen(t-29s)`[t] +  0.261451`(1-B12)Orkanen(t-30s)`[t] +  0.506132`(1-B12)Orkanen(t-31s)`[t] +  0.651642`(1-B12)Orkanen(t-32s)`[t] +  0.395417`(1-B12)Orkanen(t-33s)`[t] +  0.477226`(1-B12)Orkanen(t-34s)`[t] +  0.350592`(1-B12)Orkanen(t-35s)`[t] +  0.356152`(1-B12)Orkanen(t-36s)`[t] +  0.522564`(1-B12)Orkanen(t-37s)`[t] +  0.347655`(1-B12)Orkanen(t-38s)`[t] +  0.45088`(1-B12)Orkanen(t-39s)`[t] +  0.207965`(1-B12)Orkanen(t-40s)`[t] +  0.260469`(1-B12)Orkanen(t-41s)`[t] -0.123536M1[t] -0.096958M2[t] +  0.0200826M3[t] -0.0223232M4[t] +  0.0698393M5[t] -0.171164M6[t] +  0.372537M7[t] +  0.153392M8[t] +  0.273484M9[t] +  0.915855M10[t] +  0.749511M11[t]  + e[t] \tabularnewline
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286233&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C](1-B12)Orkanen[t] =  -0.0291851 +  0.499062`(1-B12)Temperatuur`[t] -6.83738e-05`(1-B12)Orkanen(t-1)`[t] -0.0732503`(1-B12)Orkanen(t-2)`[t] +  0.0596902`(1-B12)Orkanen(t-3)`[t] -0.00604279`(1-B12)Orkanen(t-4)`[t] +  0.0853961`(1-B12)Orkanen(t-5)`[t] +  0.0307353`(1-B12)Orkanen(t-6)`[t] +  0.0197191`(1-B12)Orkanen(t-7)`[t] -0.055251`(1-B12)Orkanen(t-8)`[t] +  0.0892998`(1-B12)Orkanen(t-9)`[t] -0.0762715`(1-B12)Orkanen(t-10)`[t] -0.215963`(1-B12)Orkanen(t-11)`[t] -0.694369`(1-B12)Orkanen(t-1s)`[t] -0.713467`(1-B12)Orkanen(t-2s)`[t] -1.02599`(1-B12)Orkanen(t-3s)`[t] -1.06719`(1-B12)Orkanen(t-4s)`[t] -0.933927`(1-B12)Orkanen(t-5s)`[t] -0.794294`(1-B12)Orkanen(t-6s)`[t] -0.857933`(1-B12)Orkanen(t-7s)`[t] -0.836123`(1-B12)Orkanen(t-8s)`[t] -0.591552`(1-B12)Orkanen(t-9s)`[t] -0.631642`(1-B12)Orkanen(t-10s)`[t] -0.715453`(1-B12)Orkanen(t-11s)`[t] -0.74568`(1-B12)Orkanen(t-12s)`[t] -1.60581`(1-B12)Orkanen(t-13s)`[t] -0.994833`(1-B12)Orkanen(t-14s)`[t] -1.08851`(1-B12)Orkanen(t-15s)`[t] -1.15167`(1-B12)Orkanen(t-16s)`[t] -0.548099`(1-B12)Orkanen(t-17s)`[t] -0.766823`(1-B12)Orkanen(t-18s)`[t] -0.665087`(1-B12)Orkanen(t-19s)`[t] -0.233681`(1-B12)Orkanen(t-20s)`[t] -0.111125`(1-B12)Orkanen(t-21s)`[t] +  0.350918`(1-B12)Orkanen(t-22s)`[t] +  0.248532`(1-B12)Orkanen(t-23s)`[t] +  0.234795`(1-B12)Orkanen(t-24s)`[t] +  0.184271`(1-B12)Orkanen(t-25s)`[t] +  0.303686`(1-B12)Orkanen(t-26s)`[t] +  0.318165`(1-B12)Orkanen(t-27s)`[t] +  0.165039`(1-B12)Orkanen(t-28s)`[t] +  0.345182`(1-B12)Orkanen(t-29s)`[t] +  0.261451`(1-B12)Orkanen(t-30s)`[t] +  0.506132`(1-B12)Orkanen(t-31s)`[t] +  0.651642`(1-B12)Orkanen(t-32s)`[t] +  0.395417`(1-B12)Orkanen(t-33s)`[t] +  0.477226`(1-B12)Orkanen(t-34s)`[t] +  0.350592`(1-B12)Orkanen(t-35s)`[t] +  0.356152`(1-B12)Orkanen(t-36s)`[t] +  0.522564`(1-B12)Orkanen(t-37s)`[t] +  0.347655`(1-B12)Orkanen(t-38s)`[t] +  0.45088`(1-B12)Orkanen(t-39s)`[t] +  0.207965`(1-B12)Orkanen(t-40s)`[t] +  0.260469`(1-B12)Orkanen(t-41s)`[t] -0.123536M1[t] -0.096958M2[t] +  0.0200826M3[t] -0.0223232M4[t] +  0.0698393M5[t] -0.171164M6[t] +  0.372537M7[t] +  0.153392M8[t] +  0.273484M9[t] +  0.915855M10[t] +  0.749511M11[t]  + e[t][/C][/ROW]
[ROW][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286233&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286233&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)Orkanen[t] = -0.0291851 + 0.499062`(1-B12)Temperatuur`[t] -6.83738e-05`(1-B12)Orkanen(t-1)`[t] -0.0732503`(1-B12)Orkanen(t-2)`[t] + 0.0596902`(1-B12)Orkanen(t-3)`[t] -0.00604279`(1-B12)Orkanen(t-4)`[t] + 0.0853961`(1-B12)Orkanen(t-5)`[t] + 0.0307353`(1-B12)Orkanen(t-6)`[t] + 0.0197191`(1-B12)Orkanen(t-7)`[t] -0.055251`(1-B12)Orkanen(t-8)`[t] + 0.0892998`(1-B12)Orkanen(t-9)`[t] -0.0762715`(1-B12)Orkanen(t-10)`[t] -0.215963`(1-B12)Orkanen(t-11)`[t] -0.694369`(1-B12)Orkanen(t-1s)`[t] -0.713467`(1-B12)Orkanen(t-2s)`[t] -1.02599`(1-B12)Orkanen(t-3s)`[t] -1.06719`(1-B12)Orkanen(t-4s)`[t] -0.933927`(1-B12)Orkanen(t-5s)`[t] -0.794294`(1-B12)Orkanen(t-6s)`[t] -0.857933`(1-B12)Orkanen(t-7s)`[t] -0.836123`(1-B12)Orkanen(t-8s)`[t] -0.591552`(1-B12)Orkanen(t-9s)`[t] -0.631642`(1-B12)Orkanen(t-10s)`[t] -0.715453`(1-B12)Orkanen(t-11s)`[t] -0.74568`(1-B12)Orkanen(t-12s)`[t] -1.60581`(1-B12)Orkanen(t-13s)`[t] -0.994833`(1-B12)Orkanen(t-14s)`[t] -1.08851`(1-B12)Orkanen(t-15s)`[t] -1.15167`(1-B12)Orkanen(t-16s)`[t] -0.548099`(1-B12)Orkanen(t-17s)`[t] -0.766823`(1-B12)Orkanen(t-18s)`[t] -0.665087`(1-B12)Orkanen(t-19s)`[t] -0.233681`(1-B12)Orkanen(t-20s)`[t] -0.111125`(1-B12)Orkanen(t-21s)`[t] + 0.350918`(1-B12)Orkanen(t-22s)`[t] + 0.248532`(1-B12)Orkanen(t-23s)`[t] + 0.234795`(1-B12)Orkanen(t-24s)`[t] + 0.184271`(1-B12)Orkanen(t-25s)`[t] + 0.303686`(1-B12)Orkanen(t-26s)`[t] + 0.318165`(1-B12)Orkanen(t-27s)`[t] + 0.165039`(1-B12)Orkanen(t-28s)`[t] + 0.345182`(1-B12)Orkanen(t-29s)`[t] + 0.261451`(1-B12)Orkanen(t-30s)`[t] + 0.506132`(1-B12)Orkanen(t-31s)`[t] + 0.651642`(1-B12)Orkanen(t-32s)`[t] + 0.395417`(1-B12)Orkanen(t-33s)`[t] + 0.477226`(1-B12)Orkanen(t-34s)`[t] + 0.350592`(1-B12)Orkanen(t-35s)`[t] + 0.356152`(1-B12)Orkanen(t-36s)`[t] + 0.522564`(1-B12)Orkanen(t-37s)`[t] + 0.347655`(1-B12)Orkanen(t-38s)`[t] + 0.45088`(1-B12)Orkanen(t-39s)`[t] + 0.207965`(1-B12)Orkanen(t-40s)`[t] + 0.260469`(1-B12)Orkanen(t-41s)`[t] -0.123536M1[t] -0.096958M2[t] + 0.0200826M3[t] -0.0223232M4[t] + 0.0698393M5[t] -0.171164M6[t] + 0.372537M7[t] + 0.153392M8[t] + 0.273484M9[t] + 0.915855M10[t] + 0.749511M11[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)	-0.02918	1.06	-2.7520e-02	0.9781	0.4891
`(1-B12)Temperatuur`	+0.4991	0.4554	+1.0960e+00	0.2764	0.1382
`(1-B12)Orkanen(t-1)`	-6.837e-05	0.07665	-8.9210e-04	0.9993	0.4996
`(1-B12)Orkanen(t-2)`	-0.07325	0.07121	-1.0290e+00	0.3067	0.1534
`(1-B12)Orkanen(t-3)`	+0.05969	0.06255	+9.5420e-01	0.3428	0.1714
`(1-B12)Orkanen(t-4)`	-0.006043	0.06052	-9.9840e-02	0.9207	0.4604
`(1-B12)Orkanen(t-5)`	+0.0854	0.05498	+1.5530e+00	0.1243	0.06216
`(1-B12)Orkanen(t-6)`	+0.03073	0.05473	+5.6160e-01	0.5759	0.288
`(1-B12)Orkanen(t-7)`	+0.01972	0.0542	+3.6380e-01	0.717	0.3585
`(1-B12)Orkanen(t-8)`	-0.05525	0.05786	-9.5490e-01	0.3425	0.1712
`(1-B12)Orkanen(t-9)`	+0.0893	0.06358	+1.4040e+00	0.164	0.08202
`(1-B12)Orkanen(t-10)`	-0.07627	0.06884	-1.1080e+00	0.2712	0.1356
`(1-B12)Orkanen(t-11)`	-0.216	0.07644	-2.8250e+00	0.005966	0.002983
`(1-B12)Orkanen(t-1s)`	-0.6944	0.1197	-5.8010e+00	1.266e-07	6.33e-08
`(1-B12)Orkanen(t-2s)`	-0.7135	0.1618	-4.4080e+00	3.21e-05	1.605e-05
`(1-B12)Orkanen(t-3s)`	-1.026	0.2358	-4.3510e+00	3.966e-05	1.983e-05
`(1-B12)Orkanen(t-4s)`	-1.067	0.3293	-3.2400e+00	0.00174	0.0008702
`(1-B12)Orkanen(t-5s)`	-0.9339	0.4093	-2.2820e+00	0.02516	0.01258
`(1-B12)Orkanen(t-6s)`	-0.7943	0.5003	-1.5870e+00	0.1163	0.05817
`(1-B12)Orkanen(t-7s)`	-0.8579	0.5361	-1.6000e+00	0.1135	0.05674
`(1-B12)Orkanen(t-8s)`	-0.8361	0.5797	-1.4420e+00	0.1531	0.07655
`(1-B12)Orkanen(t-9s)`	-0.5916	0.5904	-1.0020e+00	0.3194	0.1597
`(1-B12)Orkanen(t-10s)`	-0.6316	0.5932	-1.0650e+00	0.2902	0.1451
`(1-B12)Orkanen(t-11s)`	-0.7155	0.5904	-1.2120e+00	0.2292	0.1146
`(1-B12)Orkanen(t-12s)`	-0.7457	0.6068	-1.2290e+00	0.2227	0.1114
`(1-B12)Orkanen(t-13s)`	-1.606	0.6779	-2.3690e+00	0.02025	0.01013
`(1-B12)Orkanen(t-14s)`	-0.9948	0.7869	-1.2640e+00	0.2098	0.1049
`(1-B12)Orkanen(t-15s)`	-1.089	0.8565	-1.2710e+00	0.2075	0.1037
`(1-B12)Orkanen(t-16s)`	-1.152	0.9199	-1.2520e+00	0.2143	0.1071
`(1-B12)Orkanen(t-17s)`	-0.5481	0.972	-5.6390e-01	0.5744	0.2872
`(1-B12)Orkanen(t-18s)`	-0.7668	0.9846	-7.7880e-01	0.4384	0.2192
`(1-B12)Orkanen(t-19s)`	-0.6651	1.017	-6.5370e-01	0.5152	0.2576
`(1-B12)Orkanen(t-20s)`	-0.2337	1.023	-2.2850e-01	0.8198	0.4099
`(1-B12)Orkanen(t-21s)`	-0.1111	1.031	-1.0780e-01	0.9144	0.4572
`(1-B12)Orkanen(t-22s)`	+0.3509	1.042	+3.3660e-01	0.7373	0.3686
`(1-B12)Orkanen(t-23s)`	+0.2485	1.021	+2.4340e-01	0.8083	0.4041
`(1-B12)Orkanen(t-24s)`	+0.2348	0.9946	+2.3610e-01	0.814	0.407
`(1-B12)Orkanen(t-25s)`	+0.1843	0.9557	+1.9280e-01	0.8476	0.4238
`(1-B12)Orkanen(t-26s)`	+0.3037	0.9118	+3.3310e-01	0.74	0.37
`(1-B12)Orkanen(t-27s)`	+0.3182	0.8601	+3.6990e-01	0.7124	0.3562
`(1-B12)Orkanen(t-28s)`	+0.165	0.7967	+2.0720e-01	0.8364	0.4182
`(1-B12)Orkanen(t-29s)`	+0.3452	0.737	+4.6840e-01	0.6408	0.3204
`(1-B12)Orkanen(t-30s)`	+0.2615	0.6817	+3.8350e-01	0.7023	0.3512
`(1-B12)Orkanen(t-31s)`	+0.5061	0.625	+8.0970e-01	0.4205	0.2102
`(1-B12)Orkanen(t-32s)`	+0.6516	0.5603	+1.1630e+00	0.2483	0.1241
`(1-B12)Orkanen(t-33s)`	+0.3954	0.5006	+7.8980e-01	0.432	0.216
`(1-B12)Orkanen(t-34s)`	+0.4772	0.4678	+1.0200e+00	0.3107	0.1554
`(1-B12)Orkanen(t-35s)`	+0.3506	0.42	+8.3470e-01	0.4064	0.2032
`(1-B12)Orkanen(t-36s)`	+0.3562	0.3842	+9.2710e-01	0.3567	0.1783
`(1-B12)Orkanen(t-37s)`	+0.5226	0.3452	+1.5140e+00	0.134	0.06699
`(1-B12)Orkanen(t-38s)`	+0.3477	0.2782	+1.2500e+00	0.215	0.1075
`(1-B12)Orkanen(t-39s)`	+0.4509	0.2409	+1.8720e+00	0.06491	0.03245
`(1-B12)Orkanen(t-40s)`	+0.208	0.192	+1.0830e+00	0.2819	0.1409
`(1-B12)Orkanen(t-41s)`	+0.2605	0.1335	+1.9510e+00	0.0545	0.02725
M1	-0.1235	0.6595	-1.8730e-01	0.8519	0.4259
M2	-0.09696	1.023	-9.4810e-02	0.9247	0.4624
M3	+0.02008	1.079	+1.8620e-02	0.9852	0.4926
M4	-0.02232	1.089	-2.0490e-02	0.9837	0.4919
M5	+0.06984	1.116	+6.2600e-02	0.9502	0.4751
M6	-0.1712	1.046	-1.6370e-01	0.8704	0.4352
M7	+0.3725	1.25	+2.9790e-01	0.7665	0.3833
M8	+0.1534	1.301	+1.1790e-01	0.9064	0.4532
M9	+0.2735	2.154	+1.2700e-01	0.8993	0.4496
M10	+0.9159	1.756	+5.2160e-01	0.6034	0.3017
M11	+0.7495	0.8328	+9.0000e-01	0.3708	0.1854

\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) & -0.02918 &  1.06 & -2.7520e-02 &  0.9781 &  0.4891 \tabularnewline
`(1-B12)Temperatuur` & +0.4991 &  0.4554 & +1.0960e+00 &  0.2764 &  0.1382 \tabularnewline
`(1-B12)Orkanen(t-1)` & -6.837e-05 &  0.07665 & -8.9210e-04 &  0.9993 &  0.4996 \tabularnewline
`(1-B12)Orkanen(t-2)` & -0.07325 &  0.07121 & -1.0290e+00 &  0.3067 &  0.1534 \tabularnewline
`(1-B12)Orkanen(t-3)` & +0.05969 &  0.06255 & +9.5420e-01 &  0.3428 &  0.1714 \tabularnewline
`(1-B12)Orkanen(t-4)` & -0.006043 &  0.06052 & -9.9840e-02 &  0.9207 &  0.4604 \tabularnewline
`(1-B12)Orkanen(t-5)` & +0.0854 &  0.05498 & +1.5530e+00 &  0.1243 &  0.06216 \tabularnewline
`(1-B12)Orkanen(t-6)` & +0.03073 &  0.05473 & +5.6160e-01 &  0.5759 &  0.288 \tabularnewline
`(1-B12)Orkanen(t-7)` & +0.01972 &  0.0542 & +3.6380e-01 &  0.717 &  0.3585 \tabularnewline
`(1-B12)Orkanen(t-8)` & -0.05525 &  0.05786 & -9.5490e-01 &  0.3425 &  0.1712 \tabularnewline
`(1-B12)Orkanen(t-9)` & +0.0893 &  0.06358 & +1.4040e+00 &  0.164 &  0.08202 \tabularnewline
`(1-B12)Orkanen(t-10)` & -0.07627 &  0.06884 & -1.1080e+00 &  0.2712 &  0.1356 \tabularnewline
`(1-B12)Orkanen(t-11)` & -0.216 &  0.07644 & -2.8250e+00 &  0.005966 &  0.002983 \tabularnewline
`(1-B12)Orkanen(t-1s)` & -0.6944 &  0.1197 & -5.8010e+00 &  1.266e-07 &  6.33e-08 \tabularnewline
`(1-B12)Orkanen(t-2s)` & -0.7135 &  0.1618 & -4.4080e+00 &  3.21e-05 &  1.605e-05 \tabularnewline
`(1-B12)Orkanen(t-3s)` & -1.026 &  0.2358 & -4.3510e+00 &  3.966e-05 &  1.983e-05 \tabularnewline
`(1-B12)Orkanen(t-4s)` & -1.067 &  0.3293 & -3.2400e+00 &  0.00174 &  0.0008702 \tabularnewline
`(1-B12)Orkanen(t-5s)` & -0.9339 &  0.4093 & -2.2820e+00 &  0.02516 &  0.01258 \tabularnewline
`(1-B12)Orkanen(t-6s)` & -0.7943 &  0.5003 & -1.5870e+00 &  0.1163 &  0.05817 \tabularnewline
`(1-B12)Orkanen(t-7s)` & -0.8579 &  0.5361 & -1.6000e+00 &  0.1135 &  0.05674 \tabularnewline
`(1-B12)Orkanen(t-8s)` & -0.8361 &  0.5797 & -1.4420e+00 &  0.1531 &  0.07655 \tabularnewline
`(1-B12)Orkanen(t-9s)` & -0.5916 &  0.5904 & -1.0020e+00 &  0.3194 &  0.1597 \tabularnewline
`(1-B12)Orkanen(t-10s)` & -0.6316 &  0.5932 & -1.0650e+00 &  0.2902 &  0.1451 \tabularnewline
`(1-B12)Orkanen(t-11s)` & -0.7155 &  0.5904 & -1.2120e+00 &  0.2292 &  0.1146 \tabularnewline
`(1-B12)Orkanen(t-12s)` & -0.7457 &  0.6068 & -1.2290e+00 &  0.2227 &  0.1114 \tabularnewline
`(1-B12)Orkanen(t-13s)` & -1.606 &  0.6779 & -2.3690e+00 &  0.02025 &  0.01013 \tabularnewline
`(1-B12)Orkanen(t-14s)` & -0.9948 &  0.7869 & -1.2640e+00 &  0.2098 &  0.1049 \tabularnewline
`(1-B12)Orkanen(t-15s)` & -1.089 &  0.8565 & -1.2710e+00 &  0.2075 &  0.1037 \tabularnewline
`(1-B12)Orkanen(t-16s)` & -1.152 &  0.9199 & -1.2520e+00 &  0.2143 &  0.1071 \tabularnewline
`(1-B12)Orkanen(t-17s)` & -0.5481 &  0.972 & -5.6390e-01 &  0.5744 &  0.2872 \tabularnewline
`(1-B12)Orkanen(t-18s)` & -0.7668 &  0.9846 & -7.7880e-01 &  0.4384 &  0.2192 \tabularnewline
`(1-B12)Orkanen(t-19s)` & -0.6651 &  1.017 & -6.5370e-01 &  0.5152 &  0.2576 \tabularnewline
`(1-B12)Orkanen(t-20s)` & -0.2337 &  1.023 & -2.2850e-01 &  0.8198 &  0.4099 \tabularnewline
`(1-B12)Orkanen(t-21s)` & -0.1111 &  1.031 & -1.0780e-01 &  0.9144 &  0.4572 \tabularnewline
`(1-B12)Orkanen(t-22s)` & +0.3509 &  1.042 & +3.3660e-01 &  0.7373 &  0.3686 \tabularnewline
`(1-B12)Orkanen(t-23s)` & +0.2485 &  1.021 & +2.4340e-01 &  0.8083 &  0.4041 \tabularnewline
`(1-B12)Orkanen(t-24s)` & +0.2348 &  0.9946 & +2.3610e-01 &  0.814 &  0.407 \tabularnewline
`(1-B12)Orkanen(t-25s)` & +0.1843 &  0.9557 & +1.9280e-01 &  0.8476 &  0.4238 \tabularnewline
`(1-B12)Orkanen(t-26s)` & +0.3037 &  0.9118 & +3.3310e-01 &  0.74 &  0.37 \tabularnewline
`(1-B12)Orkanen(t-27s)` & +0.3182 &  0.8601 & +3.6990e-01 &  0.7124 &  0.3562 \tabularnewline
`(1-B12)Orkanen(t-28s)` & +0.165 &  0.7967 & +2.0720e-01 &  0.8364 &  0.4182 \tabularnewline
`(1-B12)Orkanen(t-29s)` & +0.3452 &  0.737 & +4.6840e-01 &  0.6408 &  0.3204 \tabularnewline
`(1-B12)Orkanen(t-30s)` & +0.2615 &  0.6817 & +3.8350e-01 &  0.7023 &  0.3512 \tabularnewline
`(1-B12)Orkanen(t-31s)` & +0.5061 &  0.625 & +8.0970e-01 &  0.4205 &  0.2102 \tabularnewline
`(1-B12)Orkanen(t-32s)` & +0.6516 &  0.5603 & +1.1630e+00 &  0.2483 &  0.1241 \tabularnewline
`(1-B12)Orkanen(t-33s)` & +0.3954 &  0.5006 & +7.8980e-01 &  0.432 &  0.216 \tabularnewline
`(1-B12)Orkanen(t-34s)` & +0.4772 &  0.4678 & +1.0200e+00 &  0.3107 &  0.1554 \tabularnewline
`(1-B12)Orkanen(t-35s)` & +0.3506 &  0.42 & +8.3470e-01 &  0.4064 &  0.2032 \tabularnewline
`(1-B12)Orkanen(t-36s)` & +0.3562 &  0.3842 & +9.2710e-01 &  0.3567 &  0.1783 \tabularnewline
`(1-B12)Orkanen(t-37s)` & +0.5226 &  0.3452 & +1.5140e+00 &  0.134 &  0.06699 \tabularnewline
`(1-B12)Orkanen(t-38s)` & +0.3477 &  0.2782 & +1.2500e+00 &  0.215 &  0.1075 \tabularnewline
`(1-B12)Orkanen(t-39s)` & +0.4509 &  0.2409 & +1.8720e+00 &  0.06491 &  0.03245 \tabularnewline
`(1-B12)Orkanen(t-40s)` & +0.208 &  0.192 & +1.0830e+00 &  0.2819 &  0.1409 \tabularnewline
`(1-B12)Orkanen(t-41s)` & +0.2605 &  0.1335 & +1.9510e+00 &  0.0545 &  0.02725 \tabularnewline
M1 & -0.1235 &  0.6595 & -1.8730e-01 &  0.8519 &  0.4259 \tabularnewline
M2 & -0.09696 &  1.023 & -9.4810e-02 &  0.9247 &  0.4624 \tabularnewline
M3 & +0.02008 &  1.079 & +1.8620e-02 &  0.9852 &  0.4926 \tabularnewline
M4 & -0.02232 &  1.089 & -2.0490e-02 &  0.9837 &  0.4919 \tabularnewline
M5 & +0.06984 &  1.116 & +6.2600e-02 &  0.9502 &  0.4751 \tabularnewline
M6 & -0.1712 &  1.046 & -1.6370e-01 &  0.8704 &  0.4352 \tabularnewline
M7 & +0.3725 &  1.25 & +2.9790e-01 &  0.7665 &  0.3833 \tabularnewline
M8 & +0.1534 &  1.301 & +1.1790e-01 &  0.9064 &  0.4532 \tabularnewline
M9 & +0.2735 &  2.154 & +1.2700e-01 &  0.8993 &  0.4496 \tabularnewline
M10 & +0.9159 &  1.756 & +5.2160e-01 &  0.6034 &  0.3017 \tabularnewline
M11 & +0.7495 &  0.8328 & +9.0000e-01 &  0.3708 &  0.1854 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286233&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]-0.02918[/C][C] 1.06[/C][C]-2.7520e-02[/C][C] 0.9781[/C][C] 0.4891[/C][/ROW]
[ROW][C]`(1-B12)Temperatuur`[/C][C]+0.4991[/C][C] 0.4554[/C][C]+1.0960e+00[/C][C] 0.2764[/C][C] 0.1382[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-1)`[/C][C]-6.837e-05[/C][C] 0.07665[/C][C]-8.9210e-04[/C][C] 0.9993[/C][C] 0.4996[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-2)`[/C][C]-0.07325[/C][C] 0.07121[/C][C]-1.0290e+00[/C][C] 0.3067[/C][C] 0.1534[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-3)`[/C][C]+0.05969[/C][C] 0.06255[/C][C]+9.5420e-01[/C][C] 0.3428[/C][C] 0.1714[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-4)`[/C][C]-0.006043[/C][C] 0.06052[/C][C]-9.9840e-02[/C][C] 0.9207[/C][C] 0.4604[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-5)`[/C][C]+0.0854[/C][C] 0.05498[/C][C]+1.5530e+00[/C][C] 0.1243[/C][C] 0.06216[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-6)`[/C][C]+0.03073[/C][C] 0.05473[/C][C]+5.6160e-01[/C][C] 0.5759[/C][C] 0.288[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-7)`[/C][C]+0.01972[/C][C] 0.0542[/C][C]+3.6380e-01[/C][C] 0.717[/C][C] 0.3585[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-8)`[/C][C]-0.05525[/C][C] 0.05786[/C][C]-9.5490e-01[/C][C] 0.3425[/C][C] 0.1712[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-9)`[/C][C]+0.0893[/C][C] 0.06358[/C][C]+1.4040e+00[/C][C] 0.164[/C][C] 0.08202[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-10)`[/C][C]-0.07627[/C][C] 0.06884[/C][C]-1.1080e+00[/C][C] 0.2712[/C][C] 0.1356[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-11)`[/C][C]-0.216[/C][C] 0.07644[/C][C]-2.8250e+00[/C][C] 0.005966[/C][C] 0.002983[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-1s)`[/C][C]-0.6944[/C][C] 0.1197[/C][C]-5.8010e+00[/C][C] 1.266e-07[/C][C] 6.33e-08[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-2s)`[/C][C]-0.7135[/C][C] 0.1618[/C][C]-4.4080e+00[/C][C] 3.21e-05[/C][C] 1.605e-05[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-3s)`[/C][C]-1.026[/C][C] 0.2358[/C][C]-4.3510e+00[/C][C] 3.966e-05[/C][C] 1.983e-05[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-4s)`[/C][C]-1.067[/C][C] 0.3293[/C][C]-3.2400e+00[/C][C] 0.00174[/C][C] 0.0008702[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-5s)`[/C][C]-0.9339[/C][C] 0.4093[/C][C]-2.2820e+00[/C][C] 0.02516[/C][C] 0.01258[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-6s)`[/C][C]-0.7943[/C][C] 0.5003[/C][C]-1.5870e+00[/C][C] 0.1163[/C][C] 0.05817[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-7s)`[/C][C]-0.8579[/C][C] 0.5361[/C][C]-1.6000e+00[/C][C] 0.1135[/C][C] 0.05674[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-8s)`[/C][C]-0.8361[/C][C] 0.5797[/C][C]-1.4420e+00[/C][C] 0.1531[/C][C] 0.07655[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-9s)`[/C][C]-0.5916[/C][C] 0.5904[/C][C]-1.0020e+00[/C][C] 0.3194[/C][C] 0.1597[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-10s)`[/C][C]-0.6316[/C][C] 0.5932[/C][C]-1.0650e+00[/C][C] 0.2902[/C][C] 0.1451[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-11s)`[/C][C]-0.7155[/C][C] 0.5904[/C][C]-1.2120e+00[/C][C] 0.2292[/C][C] 0.1146[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-12s)`[/C][C]-0.7457[/C][C] 0.6068[/C][C]-1.2290e+00[/C][C] 0.2227[/C][C] 0.1114[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-13s)`[/C][C]-1.606[/C][C] 0.6779[/C][C]-2.3690e+00[/C][C] 0.02025[/C][C] 0.01013[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-14s)`[/C][C]-0.9948[/C][C] 0.7869[/C][C]-1.2640e+00[/C][C] 0.2098[/C][C] 0.1049[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-15s)`[/C][C]-1.089[/C][C] 0.8565[/C][C]-1.2710e+00[/C][C] 0.2075[/C][C] 0.1037[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-16s)`[/C][C]-1.152[/C][C] 0.9199[/C][C]-1.2520e+00[/C][C] 0.2143[/C][C] 0.1071[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-17s)`[/C][C]-0.5481[/C][C] 0.972[/C][C]-5.6390e-01[/C][C] 0.5744[/C][C] 0.2872[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-18s)`[/C][C]-0.7668[/C][C] 0.9846[/C][C]-7.7880e-01[/C][C] 0.4384[/C][C] 0.2192[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-19s)`[/C][C]-0.6651[/C][C] 1.017[/C][C]-6.5370e-01[/C][C] 0.5152[/C][C] 0.2576[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-20s)`[/C][C]-0.2337[/C][C] 1.023[/C][C]-2.2850e-01[/C][C] 0.8198[/C][C] 0.4099[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-21s)`[/C][C]-0.1111[/C][C] 1.031[/C][C]-1.0780e-01[/C][C] 0.9144[/C][C] 0.4572[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-22s)`[/C][C]+0.3509[/C][C] 1.042[/C][C]+3.3660e-01[/C][C] 0.7373[/C][C] 0.3686[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-23s)`[/C][C]+0.2485[/C][C] 1.021[/C][C]+2.4340e-01[/C][C] 0.8083[/C][C] 0.4041[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-24s)`[/C][C]+0.2348[/C][C] 0.9946[/C][C]+2.3610e-01[/C][C] 0.814[/C][C] 0.407[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-25s)`[/C][C]+0.1843[/C][C] 0.9557[/C][C]+1.9280e-01[/C][C] 0.8476[/C][C] 0.4238[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-26s)`[/C][C]+0.3037[/C][C] 0.9118[/C][C]+3.3310e-01[/C][C] 0.74[/C][C] 0.37[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-27s)`[/C][C]+0.3182[/C][C] 0.8601[/C][C]+3.6990e-01[/C][C] 0.7124[/C][C] 0.3562[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-28s)`[/C][C]+0.165[/C][C] 0.7967[/C][C]+2.0720e-01[/C][C] 0.8364[/C][C] 0.4182[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-29s)`[/C][C]+0.3452[/C][C] 0.737[/C][C]+4.6840e-01[/C][C] 0.6408[/C][C] 0.3204[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-30s)`[/C][C]+0.2615[/C][C] 0.6817[/C][C]+3.8350e-01[/C][C] 0.7023[/C][C] 0.3512[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-31s)`[/C][C]+0.5061[/C][C] 0.625[/C][C]+8.0970e-01[/C][C] 0.4205[/C][C] 0.2102[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-32s)`[/C][C]+0.6516[/C][C] 0.5603[/C][C]+1.1630e+00[/C][C] 0.2483[/C][C] 0.1241[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-33s)`[/C][C]+0.3954[/C][C] 0.5006[/C][C]+7.8980e-01[/C][C] 0.432[/C][C] 0.216[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-34s)`[/C][C]+0.4772[/C][C] 0.4678[/C][C]+1.0200e+00[/C][C] 0.3107[/C][C] 0.1554[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-35s)`[/C][C]+0.3506[/C][C] 0.42[/C][C]+8.3470e-01[/C][C] 0.4064[/C][C] 0.2032[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-36s)`[/C][C]+0.3562[/C][C] 0.3842[/C][C]+9.2710e-01[/C][C] 0.3567[/C][C] 0.1783[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-37s)`[/C][C]+0.5226[/C][C] 0.3452[/C][C]+1.5140e+00[/C][C] 0.134[/C][C] 0.06699[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-38s)`[/C][C]+0.3477[/C][C] 0.2782[/C][C]+1.2500e+00[/C][C] 0.215[/C][C] 0.1075[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-39s)`[/C][C]+0.4509[/C][C] 0.2409[/C][C]+1.8720e+00[/C][C] 0.06491[/C][C] 0.03245[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-40s)`[/C][C]+0.208[/C][C] 0.192[/C][C]+1.0830e+00[/C][C] 0.2819[/C][C] 0.1409[/C][/ROW]
[ROW][C]`(1-B12)Orkanen(t-41s)`[/C][C]+0.2605[/C][C] 0.1335[/C][C]+1.9510e+00[/C][C] 0.0545[/C][C] 0.02725[/C][/ROW]
[ROW][C]M1[/C][C]-0.1235[/C][C] 0.6595[/C][C]-1.8730e-01[/C][C] 0.8519[/C][C] 0.4259[/C][/ROW]
[ROW][C]M2[/C][C]-0.09696[/C][C] 1.023[/C][C]-9.4810e-02[/C][C] 0.9247[/C][C] 0.4624[/C][/ROW]
[ROW][C]M3[/C][C]+0.02008[/C][C] 1.079[/C][C]+1.8620e-02[/C][C] 0.9852[/C][C] 0.4926[/C][/ROW]
[ROW][C]M4[/C][C]-0.02232[/C][C] 1.089[/C][C]-2.0490e-02[/C][C] 0.9837[/C][C] 0.4919[/C][/ROW]
[ROW][C]M5[/C][C]+0.06984[/C][C] 1.116[/C][C]+6.2600e-02[/C][C] 0.9502[/C][C] 0.4751[/C][/ROW]
[ROW][C]M6[/C][C]-0.1712[/C][C] 1.046[/C][C]-1.6370e-01[/C][C] 0.8704[/C][C] 0.4352[/C][/ROW]
[ROW][C]M7[/C][C]+0.3725[/C][C] 1.25[/C][C]+2.9790e-01[/C][C] 0.7665[/C][C] 0.3833[/C][/ROW]
[ROW][C]M8[/C][C]+0.1534[/C][C] 1.301[/C][C]+1.1790e-01[/C][C] 0.9064[/C][C] 0.4532[/C][/ROW]
[ROW][C]M9[/C][C]+0.2735[/C][C] 2.154[/C][C]+1.2700e-01[/C][C] 0.8993[/C][C] 0.4496[/C][/ROW]
[ROW][C]M10[/C][C]+0.9159[/C][C] 1.756[/C][C]+5.2160e-01[/C][C] 0.6034[/C][C] 0.3017[/C][/ROW]
[ROW][C]M11[/C][C]+0.7495[/C][C] 0.8328[/C][C]+9.0000e-01[/C][C] 0.3708[/C][C] 0.1854[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286233&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286233&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)	-0.02918	1.06	-2.7520e-02	0.9781	0.4891
`(1-B12)Temperatuur`	+0.4991	0.4554	+1.0960e+00	0.2764	0.1382
`(1-B12)Orkanen(t-1)`	-6.837e-05	0.07665	-8.9210e-04	0.9993	0.4996
`(1-B12)Orkanen(t-2)`	-0.07325	0.07121	-1.0290e+00	0.3067	0.1534
`(1-B12)Orkanen(t-3)`	+0.05969	0.06255	+9.5420e-01	0.3428	0.1714
`(1-B12)Orkanen(t-4)`	-0.006043	0.06052	-9.9840e-02	0.9207	0.4604
`(1-B12)Orkanen(t-5)`	+0.0854	0.05498	+1.5530e+00	0.1243	0.06216
`(1-B12)Orkanen(t-6)`	+0.03073	0.05473	+5.6160e-01	0.5759	0.288
`(1-B12)Orkanen(t-7)`	+0.01972	0.0542	+3.6380e-01	0.717	0.3585
`(1-B12)Orkanen(t-8)`	-0.05525	0.05786	-9.5490e-01	0.3425	0.1712
`(1-B12)Orkanen(t-9)`	+0.0893	0.06358	+1.4040e+00	0.164	0.08202
`(1-B12)Orkanen(t-10)`	-0.07627	0.06884	-1.1080e+00	0.2712	0.1356
`(1-B12)Orkanen(t-11)`	-0.216	0.07644	-2.8250e+00	0.005966	0.002983
`(1-B12)Orkanen(t-1s)`	-0.6944	0.1197	-5.8010e+00	1.266e-07	6.33e-08
`(1-B12)Orkanen(t-2s)`	-0.7135	0.1618	-4.4080e+00	3.21e-05	1.605e-05
`(1-B12)Orkanen(t-3s)`	-1.026	0.2358	-4.3510e+00	3.966e-05	1.983e-05
`(1-B12)Orkanen(t-4s)`	-1.067	0.3293	-3.2400e+00	0.00174	0.0008702
`(1-B12)Orkanen(t-5s)`	-0.9339	0.4093	-2.2820e+00	0.02516	0.01258
`(1-B12)Orkanen(t-6s)`	-0.7943	0.5003	-1.5870e+00	0.1163	0.05817
`(1-B12)Orkanen(t-7s)`	-0.8579	0.5361	-1.6000e+00	0.1135	0.05674
`(1-B12)Orkanen(t-8s)`	-0.8361	0.5797	-1.4420e+00	0.1531	0.07655
`(1-B12)Orkanen(t-9s)`	-0.5916	0.5904	-1.0020e+00	0.3194	0.1597
`(1-B12)Orkanen(t-10s)`	-0.6316	0.5932	-1.0650e+00	0.2902	0.1451
`(1-B12)Orkanen(t-11s)`	-0.7155	0.5904	-1.2120e+00	0.2292	0.1146
`(1-B12)Orkanen(t-12s)`	-0.7457	0.6068	-1.2290e+00	0.2227	0.1114
`(1-B12)Orkanen(t-13s)`	-1.606	0.6779	-2.3690e+00	0.02025	0.01013
`(1-B12)Orkanen(t-14s)`	-0.9948	0.7869	-1.2640e+00	0.2098	0.1049
`(1-B12)Orkanen(t-15s)`	-1.089	0.8565	-1.2710e+00	0.2075	0.1037
`(1-B12)Orkanen(t-16s)`	-1.152	0.9199	-1.2520e+00	0.2143	0.1071
`(1-B12)Orkanen(t-17s)`	-0.5481	0.972	-5.6390e-01	0.5744	0.2872
`(1-B12)Orkanen(t-18s)`	-0.7668	0.9846	-7.7880e-01	0.4384	0.2192
`(1-B12)Orkanen(t-19s)`	-0.6651	1.017	-6.5370e-01	0.5152	0.2576
`(1-B12)Orkanen(t-20s)`	-0.2337	1.023	-2.2850e-01	0.8198	0.4099
`(1-B12)Orkanen(t-21s)`	-0.1111	1.031	-1.0780e-01	0.9144	0.4572
`(1-B12)Orkanen(t-22s)`	+0.3509	1.042	+3.3660e-01	0.7373	0.3686
`(1-B12)Orkanen(t-23s)`	+0.2485	1.021	+2.4340e-01	0.8083	0.4041
`(1-B12)Orkanen(t-24s)`	+0.2348	0.9946	+2.3610e-01	0.814	0.407
`(1-B12)Orkanen(t-25s)`	+0.1843	0.9557	+1.9280e-01	0.8476	0.4238
`(1-B12)Orkanen(t-26s)`	+0.3037	0.9118	+3.3310e-01	0.74	0.37
`(1-B12)Orkanen(t-27s)`	+0.3182	0.8601	+3.6990e-01	0.7124	0.3562
`(1-B12)Orkanen(t-28s)`	+0.165	0.7967	+2.0720e-01	0.8364	0.4182
`(1-B12)Orkanen(t-29s)`	+0.3452	0.737	+4.6840e-01	0.6408	0.3204
`(1-B12)Orkanen(t-30s)`	+0.2615	0.6817	+3.8350e-01	0.7023	0.3512
`(1-B12)Orkanen(t-31s)`	+0.5061	0.625	+8.0970e-01	0.4205	0.2102
`(1-B12)Orkanen(t-32s)`	+0.6516	0.5603	+1.1630e+00	0.2483	0.1241
`(1-B12)Orkanen(t-33s)`	+0.3954	0.5006	+7.8980e-01	0.432	0.216
`(1-B12)Orkanen(t-34s)`	+0.4772	0.4678	+1.0200e+00	0.3107	0.1554
`(1-B12)Orkanen(t-35s)`	+0.3506	0.42	+8.3470e-01	0.4064	0.2032
`(1-B12)Orkanen(t-36s)`	+0.3562	0.3842	+9.2710e-01	0.3567	0.1783
`(1-B12)Orkanen(t-37s)`	+0.5226	0.3452	+1.5140e+00	0.134	0.06699
`(1-B12)Orkanen(t-38s)`	+0.3477	0.2782	+1.2500e+00	0.215	0.1075
`(1-B12)Orkanen(t-39s)`	+0.4509	0.2409	+1.8720e+00	0.06491	0.03245
`(1-B12)Orkanen(t-40s)`	+0.208	0.192	+1.0830e+00	0.2819	0.1409
`(1-B12)Orkanen(t-41s)`	+0.2605	0.1335	+1.9510e+00	0.0545	0.02725
M1	-0.1235	0.6595	-1.8730e-01	0.8519	0.4259
M2	-0.09696	1.023	-9.4810e-02	0.9247	0.4624
M3	+0.02008	1.079	+1.8620e-02	0.9852	0.4926
M4	-0.02232	1.089	-2.0490e-02	0.9837	0.4919
M5	+0.06984	1.116	+6.2600e-02	0.9502	0.4751
M6	-0.1712	1.046	-1.6370e-01	0.8704	0.4352
M7	+0.3725	1.25	+2.9790e-01	0.7665	0.3833
M8	+0.1534	1.301	+1.1790e-01	0.9064	0.4532
M9	+0.2735	2.154	+1.2700e-01	0.8993	0.4496
M10	+0.9159	1.756	+5.2160e-01	0.6034	0.3017
M11	+0.7495	0.8328	+9.0000e-01	0.3708	0.1854

Multiple Linear Regression - Regression Statistics
Multiple R	0.9017
R-squared	0.8131
Adjusted R-squared	0.6636
F-TEST (value)	5.439
F-TEST (DF numerator)	64
F-TEST (DF denominator)	80
p-value	1.828e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.8399
Sum Squared Residuals	56.43

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R &  0.9017 \tabularnewline
R-squared &  0.8131 \tabularnewline
Adjusted R-squared &  0.6636 \tabularnewline
F-TEST (value) &  5.439 \tabularnewline
F-TEST (DF numerator) & 64 \tabularnewline
F-TEST (DF denominator) & 80 \tabularnewline
p-value &  1.828e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation &  0.8399 \tabularnewline
Sum Squared Residuals &  56.43 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286233&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C] 0.9017[/C][/ROW]
[ROW][C]R-squared[/C][C] 0.8131[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C] 0.6636[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C] 5.439[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]64[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]80[/C][/ROW]
[ROW][C]p-value[/C][C] 1.828e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C] 0.8399[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C] 56.43[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286233&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286233&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	0.9017
R-squared	0.8131
Adjusted R-squared	0.6636
F-TEST (value)	5.439
F-TEST (DF numerator)	64
F-TEST (DF denominator)	80
p-value	1.828e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.8399
Sum Squared Residuals	56.43

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	0	-0.411	0.411
2	0	-0.6739	0.6739
3	0	0.1779	-0.1779
4	0	-0.0188	0.0188
5	0	0.003252	-0.003252
6	0	0.03585	-0.03585
7	1	1.852	-0.8515
8	-3	-1.214	-1.786
9	-4	-3.801	-0.1986
10	1	1.34	-0.3404
11	-1	-1.303	0.3026
12	0	0.5594	-0.5594
13	0	-0.5002	0.5002
14	0	0.2588	-0.2588
15	0	-0.4279	0.4279
16	0	0.09496	-0.09496
17	1	-0.2033	1.203
18	0	-0.01866	0.01866
19	-1	-0.4104	-0.5896
20	0	0.3321	-0.3321
21	0	0.005535	-0.005535
22	1	1.805	-0.8047
23	-2	-1.829	-0.1715
24	0	0.3195	-0.3195
25	0	1.055	-1.055
26	0	-0.2966	0.2966
27	0	0.06497	-0.06497
28	0	-0.5168	0.5168
29	-1	-0.6242	-0.3758
30	0	0.07297	-0.07297
31	1	0.8841	0.1159
32	0	0.4239	-0.4239
33	3	2.893	0.107
34	-1	-0.4583	-0.5417
35	-1	0.132	-1.132
36	0	0.5007	-0.5007
37	0	-0.01037	0.01037
38	0	-0.3626	0.3626
39	0	-0.3954	0.3954
40	0	0.1718	-0.1718
41	0	-0.231	0.231
42	0	-0.7976	0.7976
43	0	-0.9247	0.9247
44	0	0.734	-0.734
45	-2	-1.441	-0.5587
46	-1	-0.1024	-0.8976
47	0	0.7363	-0.7363
48	2	1.456	0.5441
49	0	0.3604	-0.3604
50	0	0.6063	-0.6063
51	0	0.3427	-0.3427
52	0	-0.03895	0.03895
53	0	0.02963	-0.02963
54	0	-0.01223	0.01223
55	0	-0.524	0.524
56	5	3.251	1.749
57	5	4.442	0.5583
58	1	0.5222	0.4778
59	4	2.787	1.213
60	-2	-0.9579	-1.042
61	0	-0.04144	0.04144
62	0	0.3427	-0.3427
63	0	0.05027	-0.05027
64	0	0.06042	-0.06042
65	0	0.07169	-0.07169
66	0	0.4867	-0.4867
67	0	-0.2311	0.2311
68	-3	-2.772	-0.2276
69	-3	-2.953	-0.04742
70	-1	-0.5392	-0.4608
71	-1	0.09985	-1.1
72	1	0.6512	0.3488
73	0	-0.3118	0.3118
74	0	0.009624	-0.009624
75	0	-0.24	0.24
76	0	0.03772	-0.03772
77	0	0.1716	-0.1716
78	0	-0.2748	0.2748
79	0	-0.4165	0.4165
80	1	-0.2212	1.221
81	-4	-3.302	-0.6977
82	-1	-0.3057	-0.6943
83	-1	-1.495	0.4954
84	-1	-0.9096	-0.09036
85	0	0.09296	-0.09296
86	0	0.4448	-0.4448
87	0	0.008144	-0.008144
88	0	-0.2458	0.2458
89	0	0.4795	-0.4795
90	0	0.6458	-0.6458
91	-1	-0.1394	-0.8606
92	-2	-3.298	1.298
93	4	4.07	-0.07026
94	5	4.858	0.1421
95	-1	0.3202	-1.32
96	1	0.8848	0.1152
97	0	0.533	-0.533
98	0	-0.4687	0.4687
99	0	0.5275	-0.5275
100	0	-0.03392	0.03392
101	0	-0.3428	0.3428
102	0	-0.2889	0.2889
103	1	-0.4825	1.483
104	-1	-0.1407	-0.8593
105	0	-1.933	1.933
106	-3	-3.047	0.04725
107	2	1.217	0.7829
108	0	-0.8112	0.8112
109	0	-0.5092	0.5092
110	0	0.5062	-0.5062
111	0	-0.4272	0.4272
112	0	0.2665	-0.2665
113	0	0.009	-0.009
114	0	-0.1963	0.1963
115	-1	0.044	-1.044
116	0	0.9262	-0.9262
117	0	0.8893	-0.8893
118	4	2.631	1.369
119	1	0.4729	0.5271
120	-1	-1.017	0.01678
121	0	-0.6442	0.6442
122	0	-0.3079	0.3079
123	0	0.2771	-0.2771
124	0	0.1235	-0.1235
125	0	0.3458	-0.3458
126	0	0.4137	-0.4137
127	1	1.551	-0.5511
128	1	0.8128	0.1872
129	-1	-0.6295	-0.3705
130	-2	-2.74	0.7397
131	1	-0.3833	1.383
132	2	0.6334	1.367
133	0	0.198	-0.198
134	0	-0.05876	0.05876
135	0	0.04185	-0.04185
136	0	0.09943	-0.09943
137	0	0.2908	-0.2908
138	0	-0.06648	0.06648
139	-1	-1.202	0.2021
140	0	-0.8333	0.8333
141	0	-0.2396	0.2396
142	3	2.036	0.964
143	-5	-4.755	-0.2448
144	-2	-1.309	-0.6906
145	0	0.189	-0.189

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 &  0 & -0.411 &  0.411 \tabularnewline
2 &  0 & -0.6739 &  0.6739 \tabularnewline
3 &  0 &  0.1779 & -0.1779 \tabularnewline
4 &  0 & -0.0188 &  0.0188 \tabularnewline
5 &  0 &  0.003252 & -0.003252 \tabularnewline
6 &  0 &  0.03585 & -0.03585 \tabularnewline
7 &  1 &  1.852 & -0.8515 \tabularnewline
8 & -3 & -1.214 & -1.786 \tabularnewline
9 & -4 & -3.801 & -0.1986 \tabularnewline
10 &  1 &  1.34 & -0.3404 \tabularnewline
11 & -1 & -1.303 &  0.3026 \tabularnewline
12 &  0 &  0.5594 & -0.5594 \tabularnewline
13 &  0 & -0.5002 &  0.5002 \tabularnewline
14 &  0 &  0.2588 & -0.2588 \tabularnewline
15 &  0 & -0.4279 &  0.4279 \tabularnewline
16 &  0 &  0.09496 & -0.09496 \tabularnewline
17 &  1 & -0.2033 &  1.203 \tabularnewline
18 &  0 & -0.01866 &  0.01866 \tabularnewline
19 & -1 & -0.4104 & -0.5896 \tabularnewline
20 &  0 &  0.3321 & -0.3321 \tabularnewline
21 &  0 &  0.005535 & -0.005535 \tabularnewline
22 &  1 &  1.805 & -0.8047 \tabularnewline
23 & -2 & -1.829 & -0.1715 \tabularnewline
24 &  0 &  0.3195 & -0.3195 \tabularnewline
25 &  0 &  1.055 & -1.055 \tabularnewline
26 &  0 & -0.2966 &  0.2966 \tabularnewline
27 &  0 &  0.06497 & -0.06497 \tabularnewline
28 &  0 & -0.5168 &  0.5168 \tabularnewline
29 & -1 & -0.6242 & -0.3758 \tabularnewline
30 &  0 &  0.07297 & -0.07297 \tabularnewline
31 &  1 &  0.8841 &  0.1159 \tabularnewline
32 &  0 &  0.4239 & -0.4239 \tabularnewline
33 &  3 &  2.893 &  0.107 \tabularnewline
34 & -1 & -0.4583 & -0.5417 \tabularnewline
35 & -1 &  0.132 & -1.132 \tabularnewline
36 &  0 &  0.5007 & -0.5007 \tabularnewline
37 &  0 & -0.01037 &  0.01037 \tabularnewline
38 &  0 & -0.3626 &  0.3626 \tabularnewline
39 &  0 & -0.3954 &  0.3954 \tabularnewline
40 &  0 &  0.1718 & -0.1718 \tabularnewline
41 &  0 & -0.231 &  0.231 \tabularnewline
42 &  0 & -0.7976 &  0.7976 \tabularnewline
43 &  0 & -0.9247 &  0.9247 \tabularnewline
44 &  0 &  0.734 & -0.734 \tabularnewline
45 & -2 & -1.441 & -0.5587 \tabularnewline
46 & -1 & -0.1024 & -0.8976 \tabularnewline
47 &  0 &  0.7363 & -0.7363 \tabularnewline
48 &  2 &  1.456 &  0.5441 \tabularnewline
49 &  0 &  0.3604 & -0.3604 \tabularnewline
50 &  0 &  0.6063 & -0.6063 \tabularnewline
51 &  0 &  0.3427 & -0.3427 \tabularnewline
52 &  0 & -0.03895 &  0.03895 \tabularnewline
53 &  0 &  0.02963 & -0.02963 \tabularnewline
54 &  0 & -0.01223 &  0.01223 \tabularnewline
55 &  0 & -0.524 &  0.524 \tabularnewline
56 &  5 &  3.251 &  1.749 \tabularnewline
57 &  5 &  4.442 &  0.5583 \tabularnewline
58 &  1 &  0.5222 &  0.4778 \tabularnewline
59 &  4 &  2.787 &  1.213 \tabularnewline
60 & -2 & -0.9579 & -1.042 \tabularnewline
61 &  0 & -0.04144 &  0.04144 \tabularnewline
62 &  0 &  0.3427 & -0.3427 \tabularnewline
63 &  0 &  0.05027 & -0.05027 \tabularnewline
64 &  0 &  0.06042 & -0.06042 \tabularnewline
65 &  0 &  0.07169 & -0.07169 \tabularnewline
66 &  0 &  0.4867 & -0.4867 \tabularnewline
67 &  0 & -0.2311 &  0.2311 \tabularnewline
68 & -3 & -2.772 & -0.2276 \tabularnewline
69 & -3 & -2.953 & -0.04742 \tabularnewline
70 & -1 & -0.5392 & -0.4608 \tabularnewline
71 & -1 &  0.09985 & -1.1 \tabularnewline
72 &  1 &  0.6512 &  0.3488 \tabularnewline
73 &  0 & -0.3118 &  0.3118 \tabularnewline
74 &  0 &  0.009624 & -0.009624 \tabularnewline
75 &  0 & -0.24 &  0.24 \tabularnewline
76 &  0 &  0.03772 & -0.03772 \tabularnewline
77 &  0 &  0.1716 & -0.1716 \tabularnewline
78 &  0 & -0.2748 &  0.2748 \tabularnewline
79 &  0 & -0.4165 &  0.4165 \tabularnewline
80 &  1 & -0.2212 &  1.221 \tabularnewline
81 & -4 & -3.302 & -0.6977 \tabularnewline
82 & -1 & -0.3057 & -0.6943 \tabularnewline
83 & -1 & -1.495 &  0.4954 \tabularnewline
84 & -1 & -0.9096 & -0.09036 \tabularnewline
85 &  0 &  0.09296 & -0.09296 \tabularnewline
86 &  0 &  0.4448 & -0.4448 \tabularnewline
87 &  0 &  0.008144 & -0.008144 \tabularnewline
88 &  0 & -0.2458 &  0.2458 \tabularnewline
89 &  0 &  0.4795 & -0.4795 \tabularnewline
90 &  0 &  0.6458 & -0.6458 \tabularnewline
91 & -1 & -0.1394 & -0.8606 \tabularnewline
92 & -2 & -3.298 &  1.298 \tabularnewline
93 &  4 &  4.07 & -0.07026 \tabularnewline
94 &  5 &  4.858 &  0.1421 \tabularnewline
95 & -1 &  0.3202 & -1.32 \tabularnewline
96 &  1 &  0.8848 &  0.1152 \tabularnewline
97 &  0 &  0.533 & -0.533 \tabularnewline
98 &  0 & -0.4687 &  0.4687 \tabularnewline
99 &  0 &  0.5275 & -0.5275 \tabularnewline
100 &  0 & -0.03392 &  0.03392 \tabularnewline
101 &  0 & -0.3428 &  0.3428 \tabularnewline
102 &  0 & -0.2889 &  0.2889 \tabularnewline
103 &  1 & -0.4825 &  1.483 \tabularnewline
104 & -1 & -0.1407 & -0.8593 \tabularnewline
105 &  0 & -1.933 &  1.933 \tabularnewline
106 & -3 & -3.047 &  0.04725 \tabularnewline
107 &  2 &  1.217 &  0.7829 \tabularnewline
108 &  0 & -0.8112 &  0.8112 \tabularnewline
109 &  0 & -0.5092 &  0.5092 \tabularnewline
110 &  0 &  0.5062 & -0.5062 \tabularnewline
111 &  0 & -0.4272 &  0.4272 \tabularnewline
112 &  0 &  0.2665 & -0.2665 \tabularnewline
113 &  0 &  0.009 & -0.009 \tabularnewline
114 &  0 & -0.1963 &  0.1963 \tabularnewline
115 & -1 &  0.044 & -1.044 \tabularnewline
116 &  0 &  0.9262 & -0.9262 \tabularnewline
117 &  0 &  0.8893 & -0.8893 \tabularnewline
118 &  4 &  2.631 &  1.369 \tabularnewline
119 &  1 &  0.4729 &  0.5271 \tabularnewline
120 & -1 & -1.017 &  0.01678 \tabularnewline
121 &  0 & -0.6442 &  0.6442 \tabularnewline
122 &  0 & -0.3079 &  0.3079 \tabularnewline
123 &  0 &  0.2771 & -0.2771 \tabularnewline
124 &  0 &  0.1235 & -0.1235 \tabularnewline
125 &  0 &  0.3458 & -0.3458 \tabularnewline
126 &  0 &  0.4137 & -0.4137 \tabularnewline
127 &  1 &  1.551 & -0.5511 \tabularnewline
128 &  1 &  0.8128 &  0.1872 \tabularnewline
129 & -1 & -0.6295 & -0.3705 \tabularnewline
130 & -2 & -2.74 &  0.7397 \tabularnewline
131 &  1 & -0.3833 &  1.383 \tabularnewline
132 &  2 &  0.6334 &  1.367 \tabularnewline
133 &  0 &  0.198 & -0.198 \tabularnewline
134 &  0 & -0.05876 &  0.05876 \tabularnewline
135 &  0 &  0.04185 & -0.04185 \tabularnewline
136 &  0 &  0.09943 & -0.09943 \tabularnewline
137 &  0 &  0.2908 & -0.2908 \tabularnewline
138 &  0 & -0.06648 &  0.06648 \tabularnewline
139 & -1 & -1.202 &  0.2021 \tabularnewline
140 &  0 & -0.8333 &  0.8333 \tabularnewline
141 &  0 & -0.2396 &  0.2396 \tabularnewline
142 &  3 &  2.036 &  0.964 \tabularnewline
143 & -5 & -4.755 & -0.2448 \tabularnewline
144 & -2 & -1.309 & -0.6906 \tabularnewline
145 &  0 &  0.189 & -0.189 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286233&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[/C][C]-0.411[/C][C] 0.411[/C][/ROW]
[ROW][C]2[/C][C] 0[/C][C]-0.6739[/C][C] 0.6739[/C][/ROW]
[ROW][C]3[/C][C] 0[/C][C] 0.1779[/C][C]-0.1779[/C][/ROW]
[ROW][C]4[/C][C] 0[/C][C]-0.0188[/C][C] 0.0188[/C][/ROW]
[ROW][C]5[/C][C] 0[/C][C] 0.003252[/C][C]-0.003252[/C][/ROW]
[ROW][C]6[/C][C] 0[/C][C] 0.03585[/C][C]-0.03585[/C][/ROW]
[ROW][C]7[/C][C] 1[/C][C] 1.852[/C][C]-0.8515[/C][/ROW]
[ROW][C]8[/C][C]-3[/C][C]-1.214[/C][C]-1.786[/C][/ROW]
[ROW][C]9[/C][C]-4[/C][C]-3.801[/C][C]-0.1986[/C][/ROW]
[ROW][C]10[/C][C] 1[/C][C] 1.34[/C][C]-0.3404[/C][/ROW]
[ROW][C]11[/C][C]-1[/C][C]-1.303[/C][C] 0.3026[/C][/ROW]
[ROW][C]12[/C][C] 0[/C][C] 0.5594[/C][C]-0.5594[/C][/ROW]
[ROW][C]13[/C][C] 0[/C][C]-0.5002[/C][C] 0.5002[/C][/ROW]
[ROW][C]14[/C][C] 0[/C][C] 0.2588[/C][C]-0.2588[/C][/ROW]
[ROW][C]15[/C][C] 0[/C][C]-0.4279[/C][C] 0.4279[/C][/ROW]
[ROW][C]16[/C][C] 0[/C][C] 0.09496[/C][C]-0.09496[/C][/ROW]
[ROW][C]17[/C][C] 1[/C][C]-0.2033[/C][C] 1.203[/C][/ROW]
[ROW][C]18[/C][C] 0[/C][C]-0.01866[/C][C] 0.01866[/C][/ROW]
[ROW][C]19[/C][C]-1[/C][C]-0.4104[/C][C]-0.5896[/C][/ROW]
[ROW][C]20[/C][C] 0[/C][C] 0.3321[/C][C]-0.3321[/C][/ROW]
[ROW][C]21[/C][C] 0[/C][C] 0.005535[/C][C]-0.005535[/C][/ROW]
[ROW][C]22[/C][C] 1[/C][C] 1.805[/C][C]-0.8047[/C][/ROW]
[ROW][C]23[/C][C]-2[/C][C]-1.829[/C][C]-0.1715[/C][/ROW]
[ROW][C]24[/C][C] 0[/C][C] 0.3195[/C][C]-0.3195[/C][/ROW]
[ROW][C]25[/C][C] 0[/C][C] 1.055[/C][C]-1.055[/C][/ROW]
[ROW][C]26[/C][C] 0[/C][C]-0.2966[/C][C] 0.2966[/C][/ROW]
[ROW][C]27[/C][C] 0[/C][C] 0.06497[/C][C]-0.06497[/C][/ROW]
[ROW][C]28[/C][C] 0[/C][C]-0.5168[/C][C] 0.5168[/C][/ROW]
[ROW][C]29[/C][C]-1[/C][C]-0.6242[/C][C]-0.3758[/C][/ROW]
[ROW][C]30[/C][C] 0[/C][C] 0.07297[/C][C]-0.07297[/C][/ROW]
[ROW][C]31[/C][C] 1[/C][C] 0.8841[/C][C] 0.1159[/C][/ROW]
[ROW][C]32[/C][C] 0[/C][C] 0.4239[/C][C]-0.4239[/C][/ROW]
[ROW][C]33[/C][C] 3[/C][C] 2.893[/C][C] 0.107[/C][/ROW]
[ROW][C]34[/C][C]-1[/C][C]-0.4583[/C][C]-0.5417[/C][/ROW]
[ROW][C]35[/C][C]-1[/C][C] 0.132[/C][C]-1.132[/C][/ROW]
[ROW][C]36[/C][C] 0[/C][C] 0.5007[/C][C]-0.5007[/C][/ROW]
[ROW][C]37[/C][C] 0[/C][C]-0.01037[/C][C] 0.01037[/C][/ROW]
[ROW][C]38[/C][C] 0[/C][C]-0.3626[/C][C] 0.3626[/C][/ROW]
[ROW][C]39[/C][C] 0[/C][C]-0.3954[/C][C] 0.3954[/C][/ROW]
[ROW][C]40[/C][C] 0[/C][C] 0.1718[/C][C]-0.1718[/C][/ROW]
[ROW][C]41[/C][C] 0[/C][C]-0.231[/C][C] 0.231[/C][/ROW]
[ROW][C]42[/C][C] 0[/C][C]-0.7976[/C][C] 0.7976[/C][/ROW]
[ROW][C]43[/C][C] 0[/C][C]-0.9247[/C][C] 0.9247[/C][/ROW]
[ROW][C]44[/C][C] 0[/C][C] 0.734[/C][C]-0.734[/C][/ROW]
[ROW][C]45[/C][C]-2[/C][C]-1.441[/C][C]-0.5587[/C][/ROW]
[ROW][C]46[/C][C]-1[/C][C]-0.1024[/C][C]-0.8976[/C][/ROW]
[ROW][C]47[/C][C] 0[/C][C] 0.7363[/C][C]-0.7363[/C][/ROW]
[ROW][C]48[/C][C] 2[/C][C] 1.456[/C][C] 0.5441[/C][/ROW]
[ROW][C]49[/C][C] 0[/C][C] 0.3604[/C][C]-0.3604[/C][/ROW]
[ROW][C]50[/C][C] 0[/C][C] 0.6063[/C][C]-0.6063[/C][/ROW]
[ROW][C]51[/C][C] 0[/C][C] 0.3427[/C][C]-0.3427[/C][/ROW]
[ROW][C]52[/C][C] 0[/C][C]-0.03895[/C][C] 0.03895[/C][/ROW]
[ROW][C]53[/C][C] 0[/C][C] 0.02963[/C][C]-0.02963[/C][/ROW]
[ROW][C]54[/C][C] 0[/C][C]-0.01223[/C][C] 0.01223[/C][/ROW]
[ROW][C]55[/C][C] 0[/C][C]-0.524[/C][C] 0.524[/C][/ROW]
[ROW][C]56[/C][C] 5[/C][C] 3.251[/C][C] 1.749[/C][/ROW]
[ROW][C]57[/C][C] 5[/C][C] 4.442[/C][C] 0.5583[/C][/ROW]
[ROW][C]58[/C][C] 1[/C][C] 0.5222[/C][C] 0.4778[/C][/ROW]
[ROW][C]59[/C][C] 4[/C][C] 2.787[/C][C] 1.213[/C][/ROW]
[ROW][C]60[/C][C]-2[/C][C]-0.9579[/C][C]-1.042[/C][/ROW]
[ROW][C]61[/C][C] 0[/C][C]-0.04144[/C][C] 0.04144[/C][/ROW]
[ROW][C]62[/C][C] 0[/C][C] 0.3427[/C][C]-0.3427[/C][/ROW]
[ROW][C]63[/C][C] 0[/C][C] 0.05027[/C][C]-0.05027[/C][/ROW]
[ROW][C]64[/C][C] 0[/C][C] 0.06042[/C][C]-0.06042[/C][/ROW]
[ROW][C]65[/C][C] 0[/C][C] 0.07169[/C][C]-0.07169[/C][/ROW]
[ROW][C]66[/C][C] 0[/C][C] 0.4867[/C][C]-0.4867[/C][/ROW]
[ROW][C]67[/C][C] 0[/C][C]-0.2311[/C][C] 0.2311[/C][/ROW]
[ROW][C]68[/C][C]-3[/C][C]-2.772[/C][C]-0.2276[/C][/ROW]
[ROW][C]69[/C][C]-3[/C][C]-2.953[/C][C]-0.04742[/C][/ROW]
[ROW][C]70[/C][C]-1[/C][C]-0.5392[/C][C]-0.4608[/C][/ROW]
[ROW][C]71[/C][C]-1[/C][C] 0.09985[/C][C]-1.1[/C][/ROW]
[ROW][C]72[/C][C] 1[/C][C] 0.6512[/C][C] 0.3488[/C][/ROW]
[ROW][C]73[/C][C] 0[/C][C]-0.3118[/C][C] 0.3118[/C][/ROW]
[ROW][C]74[/C][C] 0[/C][C] 0.009624[/C][C]-0.009624[/C][/ROW]
[ROW][C]75[/C][C] 0[/C][C]-0.24[/C][C] 0.24[/C][/ROW]
[ROW][C]76[/C][C] 0[/C][C] 0.03772[/C][C]-0.03772[/C][/ROW]
[ROW][C]77[/C][C] 0[/C][C] 0.1716[/C][C]-0.1716[/C][/ROW]
[ROW][C]78[/C][C] 0[/C][C]-0.2748[/C][C] 0.2748[/C][/ROW]
[ROW][C]79[/C][C] 0[/C][C]-0.4165[/C][C] 0.4165[/C][/ROW]
[ROW][C]80[/C][C] 1[/C][C]-0.2212[/C][C] 1.221[/C][/ROW]
[ROW][C]81[/C][C]-4[/C][C]-3.302[/C][C]-0.6977[/C][/ROW]
[ROW][C]82[/C][C]-1[/C][C]-0.3057[/C][C]-0.6943[/C][/ROW]
[ROW][C]83[/C][C]-1[/C][C]-1.495[/C][C] 0.4954[/C][/ROW]
[ROW][C]84[/C][C]-1[/C][C]-0.9096[/C][C]-0.09036[/C][/ROW]
[ROW][C]85[/C][C] 0[/C][C] 0.09296[/C][C]-0.09296[/C][/ROW]
[ROW][C]86[/C][C] 0[/C][C] 0.4448[/C][C]-0.4448[/C][/ROW]
[ROW][C]87[/C][C] 0[/C][C] 0.008144[/C][C]-0.008144[/C][/ROW]
[ROW][C]88[/C][C] 0[/C][C]-0.2458[/C][C] 0.2458[/C][/ROW]
[ROW][C]89[/C][C] 0[/C][C] 0.4795[/C][C]-0.4795[/C][/ROW]
[ROW][C]90[/C][C] 0[/C][C] 0.6458[/C][C]-0.6458[/C][/ROW]
[ROW][C]91[/C][C]-1[/C][C]-0.1394[/C][C]-0.8606[/C][/ROW]
[ROW][C]92[/C][C]-2[/C][C]-3.298[/C][C] 1.298[/C][/ROW]
[ROW][C]93[/C][C] 4[/C][C] 4.07[/C][C]-0.07026[/C][/ROW]
[ROW][C]94[/C][C] 5[/C][C] 4.858[/C][C] 0.1421[/C][/ROW]
[ROW][C]95[/C][C]-1[/C][C] 0.3202[/C][C]-1.32[/C][/ROW]
[ROW][C]96[/C][C] 1[/C][C] 0.8848[/C][C] 0.1152[/C][/ROW]
[ROW][C]97[/C][C] 0[/C][C] 0.533[/C][C]-0.533[/C][/ROW]
[ROW][C]98[/C][C] 0[/C][C]-0.4687[/C][C] 0.4687[/C][/ROW]
[ROW][C]99[/C][C] 0[/C][C] 0.5275[/C][C]-0.5275[/C][/ROW]
[ROW][C]100[/C][C] 0[/C][C]-0.03392[/C][C] 0.03392[/C][/ROW]
[ROW][C]101[/C][C] 0[/C][C]-0.3428[/C][C] 0.3428[/C][/ROW]
[ROW][C]102[/C][C] 0[/C][C]-0.2889[/C][C] 0.2889[/C][/ROW]
[ROW][C]103[/C][C] 1[/C][C]-0.4825[/C][C] 1.483[/C][/ROW]
[ROW][C]104[/C][C]-1[/C][C]-0.1407[/C][C]-0.8593[/C][/ROW]
[ROW][C]105[/C][C] 0[/C][C]-1.933[/C][C] 1.933[/C][/ROW]
[ROW][C]106[/C][C]-3[/C][C]-3.047[/C][C] 0.04725[/C][/ROW]
[ROW][C]107[/C][C] 2[/C][C] 1.217[/C][C] 0.7829[/C][/ROW]
[ROW][C]108[/C][C] 0[/C][C]-0.8112[/C][C] 0.8112[/C][/ROW]
[ROW][C]109[/C][C] 0[/C][C]-0.5092[/C][C] 0.5092[/C][/ROW]
[ROW][C]110[/C][C] 0[/C][C] 0.5062[/C][C]-0.5062[/C][/ROW]
[ROW][C]111[/C][C] 0[/C][C]-0.4272[/C][C] 0.4272[/C][/ROW]
[ROW][C]112[/C][C] 0[/C][C] 0.2665[/C][C]-0.2665[/C][/ROW]
[ROW][C]113[/C][C] 0[/C][C] 0.009[/C][C]-0.009[/C][/ROW]
[ROW][C]114[/C][C] 0[/C][C]-0.1963[/C][C] 0.1963[/C][/ROW]
[ROW][C]115[/C][C]-1[/C][C] 0.044[/C][C]-1.044[/C][/ROW]
[ROW][C]116[/C][C] 0[/C][C] 0.9262[/C][C]-0.9262[/C][/ROW]
[ROW][C]117[/C][C] 0[/C][C] 0.8893[/C][C]-0.8893[/C][/ROW]
[ROW][C]118[/C][C] 4[/C][C] 2.631[/C][C] 1.369[/C][/ROW]
[ROW][C]119[/C][C] 1[/C][C] 0.4729[/C][C] 0.5271[/C][/ROW]
[ROW][C]120[/C][C]-1[/C][C]-1.017[/C][C] 0.01678[/C][/ROW]
[ROW][C]121[/C][C] 0[/C][C]-0.6442[/C][C] 0.6442[/C][/ROW]
[ROW][C]122[/C][C] 0[/C][C]-0.3079[/C][C] 0.3079[/C][/ROW]
[ROW][C]123[/C][C] 0[/C][C] 0.2771[/C][C]-0.2771[/C][/ROW]
[ROW][C]124[/C][C] 0[/C][C] 0.1235[/C][C]-0.1235[/C][/ROW]
[ROW][C]125[/C][C] 0[/C][C] 0.3458[/C][C]-0.3458[/C][/ROW]
[ROW][C]126[/C][C] 0[/C][C] 0.4137[/C][C]-0.4137[/C][/ROW]
[ROW][C]127[/C][C] 1[/C][C] 1.551[/C][C]-0.5511[/C][/ROW]
[ROW][C]128[/C][C] 1[/C][C] 0.8128[/C][C] 0.1872[/C][/ROW]
[ROW][C]129[/C][C]-1[/C][C]-0.6295[/C][C]-0.3705[/C][/ROW]
[ROW][C]130[/C][C]-2[/C][C]-2.74[/C][C] 0.7397[/C][/ROW]
[ROW][C]131[/C][C] 1[/C][C]-0.3833[/C][C] 1.383[/C][/ROW]
[ROW][C]132[/C][C] 2[/C][C] 0.6334[/C][C] 1.367[/C][/ROW]
[ROW][C]133[/C][C] 0[/C][C] 0.198[/C][C]-0.198[/C][/ROW]
[ROW][C]134[/C][C] 0[/C][C]-0.05876[/C][C] 0.05876[/C][/ROW]
[ROW][C]135[/C][C] 0[/C][C] 0.04185[/C][C]-0.04185[/C][/ROW]
[ROW][C]136[/C][C] 0[/C][C] 0.09943[/C][C]-0.09943[/C][/ROW]
[ROW][C]137[/C][C] 0[/C][C] 0.2908[/C][C]-0.2908[/C][/ROW]
[ROW][C]138[/C][C] 0[/C][C]-0.06648[/C][C] 0.06648[/C][/ROW]
[ROW][C]139[/C][C]-1[/C][C]-1.202[/C][C] 0.2021[/C][/ROW]
[ROW][C]140[/C][C] 0[/C][C]-0.8333[/C][C] 0.8333[/C][/ROW]
[ROW][C]141[/C][C] 0[/C][C]-0.2396[/C][C] 0.2396[/C][/ROW]
[ROW][C]142[/C][C] 3[/C][C] 2.036[/C][C] 0.964[/C][/ROW]
[ROW][C]143[/C][C]-5[/C][C]-4.755[/C][C]-0.2448[/C][/ROW]
[ROW][C]144[/C][C]-2[/C][C]-1.309[/C][C]-0.6906[/C][/ROW]
[ROW][C]145[/C][C] 0[/C][C] 0.189[/C][C]-0.189[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286233&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286233&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	-0.411	0.411
2	0	-0.6739	0.6739
3	0	0.1779	-0.1779
4	0	-0.0188	0.0188
5	0	0.003252	-0.003252
6	0	0.03585	-0.03585
7	1	1.852	-0.8515
8	-3	-1.214	-1.786
9	-4	-3.801	-0.1986
10	1	1.34	-0.3404
11	-1	-1.303	0.3026
12	0	0.5594	-0.5594
13	0	-0.5002	0.5002
14	0	0.2588	-0.2588
15	0	-0.4279	0.4279
16	0	0.09496	-0.09496
17	1	-0.2033	1.203
18	0	-0.01866	0.01866
19	-1	-0.4104	-0.5896
20	0	0.3321	-0.3321
21	0	0.005535	-0.005535
22	1	1.805	-0.8047
23	-2	-1.829	-0.1715
24	0	0.3195	-0.3195
25	0	1.055	-1.055
26	0	-0.2966	0.2966
27	0	0.06497	-0.06497
28	0	-0.5168	0.5168
29	-1	-0.6242	-0.3758
30	0	0.07297	-0.07297
31	1	0.8841	0.1159
32	0	0.4239	-0.4239
33	3	2.893	0.107
34	-1	-0.4583	-0.5417
35	-1	0.132	-1.132
36	0	0.5007	-0.5007
37	0	-0.01037	0.01037
38	0	-0.3626	0.3626
39	0	-0.3954	0.3954
40	0	0.1718	-0.1718
41	0	-0.231	0.231
42	0	-0.7976	0.7976
43	0	-0.9247	0.9247
44	0	0.734	-0.734
45	-2	-1.441	-0.5587
46	-1	-0.1024	-0.8976
47	0	0.7363	-0.7363
48	2	1.456	0.5441
49	0	0.3604	-0.3604
50	0	0.6063	-0.6063
51	0	0.3427	-0.3427
52	0	-0.03895	0.03895
53	0	0.02963	-0.02963
54	0	-0.01223	0.01223
55	0	-0.524	0.524
56	5	3.251	1.749
57	5	4.442	0.5583
58	1	0.5222	0.4778
59	4	2.787	1.213
60	-2	-0.9579	-1.042
61	0	-0.04144	0.04144
62	0	0.3427	-0.3427
63	0	0.05027	-0.05027
64	0	0.06042	-0.06042
65	0	0.07169	-0.07169
66	0	0.4867	-0.4867
67	0	-0.2311	0.2311
68	-3	-2.772	-0.2276
69	-3	-2.953	-0.04742
70	-1	-0.5392	-0.4608
71	-1	0.09985	-1.1
72	1	0.6512	0.3488
73	0	-0.3118	0.3118
74	0	0.009624	-0.009624
75	0	-0.24	0.24
76	0	0.03772	-0.03772
77	0	0.1716	-0.1716
78	0	-0.2748	0.2748
79	0	-0.4165	0.4165
80	1	-0.2212	1.221
81	-4	-3.302	-0.6977
82	-1	-0.3057	-0.6943
83	-1	-1.495	0.4954
84	-1	-0.9096	-0.09036
85	0	0.09296	-0.09296
86	0	0.4448	-0.4448
87	0	0.008144	-0.008144
88	0	-0.2458	0.2458
89	0	0.4795	-0.4795
90	0	0.6458	-0.6458
91	-1	-0.1394	-0.8606
92	-2	-3.298	1.298
93	4	4.07	-0.07026
94	5	4.858	0.1421
95	-1	0.3202	-1.32
96	1	0.8848	0.1152
97	0	0.533	-0.533
98	0	-0.4687	0.4687
99	0	0.5275	-0.5275
100	0	-0.03392	0.03392
101	0	-0.3428	0.3428
102	0	-0.2889	0.2889
103	1	-0.4825	1.483
104	-1	-0.1407	-0.8593
105	0	-1.933	1.933
106	-3	-3.047	0.04725
107	2	1.217	0.7829
108	0	-0.8112	0.8112
109	0	-0.5092	0.5092
110	0	0.5062	-0.5062
111	0	-0.4272	0.4272
112	0	0.2665	-0.2665
113	0	0.009	-0.009
114	0	-0.1963	0.1963
115	-1	0.044	-1.044
116	0	0.9262	-0.9262
117	0	0.8893	-0.8893
118	4	2.631	1.369
119	1	0.4729	0.5271
120	-1	-1.017	0.01678
121	0	-0.6442	0.6442
122	0	-0.3079	0.3079
123	0	0.2771	-0.2771
124	0	0.1235	-0.1235
125	0	0.3458	-0.3458
126	0	0.4137	-0.4137
127	1	1.551	-0.5511
128	1	0.8128	0.1872
129	-1	-0.6295	-0.3705
130	-2	-2.74	0.7397
131	1	-0.3833	1.383
132	2	0.6334	1.367
133	0	0.198	-0.198
134	0	-0.05876	0.05876
135	0	0.04185	-0.04185
136	0	0.09943	-0.09943
137	0	0.2908	-0.2908
138	0	-0.06648	0.06648
139	-1	-1.202	0.2021
140	0	-0.8333	0.8333
141	0	-0.2396	0.2396
142	3	2.036	0.964
143	-5	-4.755	-0.2448
144	-2	-1.309	-0.6906
145	0	0.189	-0.189

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
68	0.07776	0.1555	0.9222
69	0.02585	0.0517	0.9741
70	0.08105	0.1621	0.9189
71	0.03466	0.06931	0.9653
72	0.08664	0.1733	0.9134
73	0.2505	0.501	0.7495
74	0.2562	0.5125	0.7438
75	0.1922	0.3843	0.8078
76	0.4201	0.8403	0.5799
77	0.6146	0.7709	0.3854

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
68 &  0.07776 &  0.1555 &  0.9222 \tabularnewline
69 &  0.02585 &  0.0517 &  0.9741 \tabularnewline
70 &  0.08105 &  0.1621 &  0.9189 \tabularnewline
71 &  0.03466 &  0.06931 &  0.9653 \tabularnewline
72 &  0.08664 &  0.1733 &  0.9134 \tabularnewline
73 &  0.2505 &  0.501 &  0.7495 \tabularnewline
74 &  0.2562 &  0.5125 &  0.7438 \tabularnewline
75 &  0.1922 &  0.3843 &  0.8078 \tabularnewline
76 &  0.4201 &  0.8403 &  0.5799 \tabularnewline
77 &  0.6146 &  0.7709 &  0.3854 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286233&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]68[/C][C] 0.07776[/C][C] 0.1555[/C][C] 0.9222[/C][/ROW]
[ROW][C]69[/C][C] 0.02585[/C][C] 0.0517[/C][C] 0.9741[/C][/ROW]
[ROW][C]70[/C][C] 0.08105[/C][C] 0.1621[/C][C] 0.9189[/C][/ROW]
[ROW][C]71[/C][C] 0.03466[/C][C] 0.06931[/C][C] 0.9653[/C][/ROW]
[ROW][C]72[/C][C] 0.08664[/C][C] 0.1733[/C][C] 0.9134[/C][/ROW]
[ROW][C]73[/C][C] 0.2505[/C][C] 0.501[/C][C] 0.7495[/C][/ROW]
[ROW][C]74[/C][C] 0.2562[/C][C] 0.5125[/C][C] 0.7438[/C][/ROW]
[ROW][C]75[/C][C] 0.1922[/C][C] 0.3843[/C][C] 0.8078[/C][/ROW]
[ROW][C]76[/C][C] 0.4201[/C][C] 0.8403[/C][C] 0.5799[/C][/ROW]
[ROW][C]77[/C][C] 0.6146[/C][C] 0.7709[/C][C] 0.3854[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286233&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286233&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
68	0.07776	0.1555	0.9222
69	0.02585	0.0517	0.9741
70	0.08105	0.1621	0.9189
71	0.03466	0.06931	0.9653
72	0.08664	0.1733	0.9134
73	0.2505	0.501	0.7495
74	0.2562	0.5125	0.7438
75	0.1922	0.3843	0.8078
76	0.4201	0.8403	0.5799
77	0.6146	0.7709	0.3854

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	0	0	OK
10% type I error level	2	0.2	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 & 0 & 0 & OK \tabularnewline
10% type I error level & 2 & 0.2 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286233&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]2[/C][C]0.2[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286233&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286233&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	0	0	OK
10% type I error level	2	0.2	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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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Seasonal Differences (s=12) ; par4 = 11 ; par5 = 41 ;

Parameters (R input):

par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Seasonal Differences (s=12) ; par4 = 11 ; par5 = 41 ;

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

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