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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Moduleesteq.wasp
Title produced by softwareEstimate Equation
Date of computationThu, 22 Nov 2007 00:17:15 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/22/t11957154065zprohfo5m7erkx.htm/, Retrieved Thu, 02 May 2024 20:33:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5910, Retrieved Thu, 02 May 2024 20:33:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact225

Tree of Dependent Computations

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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1508	0
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1385	0
1632	0
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1763	1

Tables (Output of Computation)





Multiple Linear Regression - Estimated Regression Equation
y[t] = -226.38503360266 x[t] +2325.8282284351 -1.7648553323769 t^1 -454.90468392106 M1[t] -635.46105332377 M2[t] -586.66340865614 M3[t] -694.55634265902 M4[t] -559.00869799139 M5[t] -609.46413199426 M6[t] -535.60398732664 M7[t] -515.43442132951 M8[t] -464.38677666189 M9[t] -319.71721066476 M10[t] -121.91956599713 M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
y[t] = -226.38503360266 x[t] +2325.8282284351 -1.7648553323769 t^1 -454.90468392106 M1[t] -635.46105332377 M2[t] -586.66340865614 M3[t] -694.55634265902 M4[t] -559.00869799139 M5[t] -609.46413199426 M6[t] -535.60398732664 M7[t] -515.43442132951 M8[t] -464.38677666189 M9[t] -319.71721066476 M10[t] -121.91956599713 M11[t] + e[t] \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=5910&T=0

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW]
y[t] = -226.38503360266 x[t] +2325.8282284351 -1.7648553323769 t^1 -454.90468392106 M1[t] -635.46105332377 M2[t] -586.66340865614 M3[t] -694.55634265902 M4[t] -559.00869799139 M5[t] -609.46413199426 M6[t] -535.60398732664 M7[t] -515.43442132951 M8[t] -464.38677666189 M9[t] -319.71721066476 M10[t] -121.91956599713 M11[t] + e[t][/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=5910&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5910&T=0

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


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

Multiple Linear Regression - Estimated Regression Equation
y[t] = -226.38503360266 x[t] +2325.8282284351 -1.7648553323769 t^1 -454.90468392106 M1[t] -635.46105332377 M2[t] -586.66340865614 M3[t] -694.55634265902 M4[t] -559.00869799139 M5[t] -609.46413199426 M6[t] -535.60398732664 M7[t] -515.43442132951 M8[t] -464.38677666189 M9[t] -319.71721066476 M10[t] -121.91956599713 M11[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
x[t]-226.38503441.037226-5.51657700
Constant2325.82822844.14871652.68167300
t^1-1.7648550.240551-7.33670700
M1[t]-454.90468453.95579-8.43106300
M2[t]-635.46105353.941479-11.78056400
M3[t]-586.66340953.952742-10.87365300
M4[t]-694.55634353.922166-12.8807200
M5[t]-559.00869853.931287-10.36520200
M6[t]-609.46413253.907141-11.30581400
M7[t]-535.60398753.914117-9.93439200
M8[t]-515.43442153.896405-9.56342900
M9[t]-464.38677753.901237-8.61551200
M10[t]-319.71721153.889963-5.93277800
M11[t]-121.91956653.892648-2.2622670.024890.012445
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%x[t]-0.0162360.002943-334.25869500
%Constant1.3924550.02643114.84801800
%t^1-0.1019620.013898-64.61831700
%M1[t]-0.0226960.002692-363.05247100
%M2[t]-0.0317040.002691-359.80152400
%M3[t]-0.0292690.002692-360.63086800
%M4[t]-0.0346520.00269-358.83445400
%M5[t]-0.027890.002691-361.28710800
%M6[t]-0.0304070.002689-360.51296900
%M7[t]-0.0267220.00269-361.83627600
%M8[t]-0.0257160.002689-362.32941600
%M9[t]-0.0231690.002689-363.24399900
%M10[t]-0.0159510.002689-366.00452300
%M11[t]-0.0060830.002689-369.65650800
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-x[t]-0.2544910.046132-5.51657700
S-Constant00010.5
S-t^1-0.3387460.046171-7.33670700
S-M1[t]-0.4352660.051626-8.43106300
S-M2[t]-0.6080270.051613-11.78056400
S-M3[t]-0.5613360.051624-10.87365300
S-M4[t]-0.6645710.051594-12.8807200
S-M5[t]-0.5348750.051603-10.36520200
S-M6[t]-0.5831530.05158-11.30581400
S-M7[t]-0.5124810.051587-9.93439200
S-M8[t]-0.4931820.05157-9.56342900
S-M9[t]-0.4443380.051574-8.61551200
S-M10[t]-0.3059140.051563-5.93277800
S-M11[t]-0.1166560.051566-2.2622670.024890.012445
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
x[t]-0.382109
Constant0.969397
t^1-0.481858
M1[t]-0.534208
M2[t]-0.66189
M3[t]-0.631766
M4[t]-0.69457
M5[t]-0.613511
M6[t]-0.646499
M7[t]-0.597232
M8[t]-0.582596
M9[t]-0.542482
M10[t]-0.406319
M11[t]-0.167178
Critical Values (alpha = 5%)
1-tail CV at 5%1.65
2-tail CV at 5%1.96

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ordinary Least Squares \tabularnewline
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value \tabularnewline x[t]-226.38503441.037226-5.51657700 \tabularnewline Constant2325.82822844.14871652.68167300 \tabularnewline t^1-1.7648550.240551-7.33670700 \tabularnewline M1[t]-454.90468453.95579-8.43106300 \tabularnewline M2[t]-635.46105353.941479-11.78056400 \tabularnewline M3[t]-586.66340953.952742-10.87365300 \tabularnewline M4[t]-694.55634353.922166-12.8807200 \tabularnewline M5[t]-559.00869853.931287-10.36520200 \tabularnewline M6[t]-609.46413253.907141-11.30581400 \tabularnewline M7[t]-535.60398753.914117-9.93439200 \tabularnewline M8[t]-515.43442153.896405-9.56342900 \tabularnewline M9[t]-464.38677753.901237-8.61551200 \tabularnewline M10[t]-319.71721153.889963-5.93277800 \tabularnewline M11[t]-121.91956653.892648-2.2622670.024890.012445 \tabularnewline \tabularnewline VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value \tabularnewline %x[t]-0.0162360.002943-334.25869500 \tabularnewline %Constant1.3924550.02643114.84801800 \tabularnewline %t^1-0.1019620.013898-64.61831700 \tabularnewline %M1[t]-0.0226960.002692-363.05247100 \tabularnewline %M2[t]-0.0317040.002691-359.80152400 \tabularnewline %M3[t]-0.0292690.002692-360.63086800 \tabularnewline %M4[t]-0.0346520.00269-358.83445400 \tabularnewline %M5[t]-0.027890.002691-361.28710800 \tabularnewline %M6[t]-0.0304070.002689-360.51296900 \tabularnewline %M7[t]-0.0267220.00269-361.83627600 \tabularnewline %M8[t]-0.0257160.002689-362.32941600 \tabularnewline %M9[t]-0.0231690.002689-363.24399900 \tabularnewline %M10[t]-0.0159510.002689-366.00452300 \tabularnewline %M11[t]-0.0060830.002689-369.65650800 \tabularnewline VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value \tabularnewline S-x[t]-0.2544910.046132-5.51657700 \tabularnewline S-Constant00010.5 \tabularnewline S-t^1-0.3387460.046171-7.33670700 \tabularnewline S-M1[t]-0.4352660.051626-8.43106300 \tabularnewline S-M2[t]-0.6080270.051613-11.78056400 \tabularnewline S-M3[t]-0.5613360.051624-10.87365300 \tabularnewline S-M4[t]-0.6645710.051594-12.8807200 \tabularnewline S-M5[t]-0.5348750.051603-10.36520200 \tabularnewline S-M6[t]-0.5831530.05158-11.30581400 \tabularnewline S-M7[t]-0.5124810.051587-9.93439200 \tabularnewline S-M8[t]-0.4931820.05157-9.56342900 \tabularnewline S-M9[t]-0.4443380.051574-8.61551200 \tabularnewline S-M10[t]-0.3059140.051563-5.93277800 \tabularnewline S-M11[t]-0.1166560.051566-2.2622670.024890.012445 \tabularnewline *Notecomputed against deterministic endogenous series \tabularnewline VariablePartial Correlation \tabularnewline x[t]-0.382109 \tabularnewline Constant0.969397 \tabularnewline t^1-0.481858 \tabularnewline M1[t]-0.534208 \tabularnewline M2[t]-0.66189 \tabularnewline M3[t]-0.631766 \tabularnewline M4[t]-0.69457 \tabularnewline M5[t]-0.613511 \tabularnewline M6[t]-0.646499 \tabularnewline M7[t]-0.597232 \tabularnewline M8[t]-0.582596 \tabularnewline M9[t]-0.542482 \tabularnewline M10[t]-0.406319 \tabularnewline M11[t]-0.167178 \tabularnewline Critical Values (alpha = 5%) \tabularnewline 1-tail CV at 5%1.65 \tabularnewline 2-tail CV at 5%1.96 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=5910&T=1

[TABLE]

[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]

[ROW]
Variable[/C]Parameter[/C]S.E.[/C]T-STATH0: parameter = 0[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]x[t][/C]-226.385034[/C]41.037226[/C]-5.516577[/C]0[/C]0[/C][/ROW] [ROW][C]Constant[/C]2325.828228[/C]44.148716[/C]52.681673[/C]0[/C]0[/C][/ROW] [ROW][C]t^1[/C]-1.764855[/C]0.240551[/C]-7.336707[/C]0[/C]0[/C][/ROW] [ROW][C]M1[t][/C]-454.904684[/C]53.95579[/C]-8.431063[/C]0[/C]0[/C][/ROW] [ROW][C]M2[t][/C]-635.461053[/C]53.941479[/C]-11.780564[/C]0[/C]0[/C][/ROW] [ROW][C]M3[t][/C]-586.663409[/C]53.952742[/C]-10.873653[/C]0[/C]0[/C][/ROW] [ROW][C]M4[t][/C]-694.556343[/C]53.922166[/C]-12.88072[/C]0[/C]0[/C][/ROW] [ROW][C]M5[t][/C]-559.008698[/C]53.931287[/C]-10.365202[/C]0[/C]0[/C][/ROW] [ROW][C]M6[t][/C]-609.464132[/C]53.907141[/C]-11.305814[/C]0[/C]0[/C][/ROW] [ROW][C]M7[t][/C]-535.603987[/C]53.914117[/C]-9.934392[/C]0[/C]0[/C][/ROW] [ROW][C]M8[t][/C]-515.434421[/C]53.896405[/C]-9.563429[/C]0[/C]0[/C][/ROW] [ROW][C]M9[t][/C]-464.386777[/C]53.901237[/C]-8.615512[/C]0[/C]0[/C][/ROW] [ROW][C]M10[t][/C]-319.717211[/C]53.889963[/C]-5.932778[/C]0[/C]0[/C][/ROW] [ROW][C]M11[t][/C]-121.919566[/C]53.892648[/C]-2.262267[/C]0.02489[/C]0.012445[/C][/ROW] [ROW][C][/C][/ROW] [ROW]Variable[/C]Elasticity[/C]S.E.*[/C]T-STATH0: |elast| = 1[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]%x[t][/C]-0.016236[/C]0.002943[/C]-334.258695[/C]0[/C]0[/C][/ROW] [ROW][C]%Constant[/C]1.392455[/C]0.026431[/C]14.848018[/C]0[/C]0[/C][/ROW] [ROW][C]%t^1[/C]-0.101962[/C]0.013898[/C]-64.618317[/C]0[/C]0[/C][/ROW] [ROW][C]%M1[t][/C]-0.022696[/C]0.002692[/C]-363.052471[/C]0[/C]0[/C][/ROW] [ROW][C]%M2[t][/C]-0.031704[/C]0.002691[/C]-359.801524[/C]0[/C]0[/C][/ROW] [ROW][C]%M3[t][/C]-0.029269[/C]0.002692[/C]-360.630868[/C]0[/C]0[/C][/ROW] [ROW][C]%M4[t][/C]-0.034652[/C]0.00269[/C]-358.834454[/C]0[/C]0[/C][/ROW] [ROW][C]%M5[t][/C]-0.02789[/C]0.002691[/C]-361.287108[/C]0[/C]0[/C][/ROW] [ROW][C]%M6[t][/C]-0.030407[/C]0.002689[/C]-360.512969[/C]0[/C]0[/C][/ROW] [ROW][C]%M7[t][/C]-0.026722[/C]0.00269[/C]-361.836276[/C]0[/C]0[/C][/ROW] [ROW][C]%M8[t][/C]-0.025716[/C]0.002689[/C]-362.329416[/C]0[/C]0[/C][/ROW] [ROW][C]%M9[t][/C]-0.023169[/C]0.002689[/C]-363.243999[/C]0[/C]0[/C][/ROW] [ROW][C]%M10[t][/C]-0.015951[/C]0.002689[/C]-366.004523[/C]0[/C]0[/C][/ROW] [ROW][C]%M11[t][/C]-0.006083[/C]0.002689[/C]-369.656508[/C]0[/C]0[/C][/ROW] [ROW]Variable[/C]Stand. Coeff.[/C]S.E.*[/C]T-STATH0: coeff = 0[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]S-x[t][/C]-0.254491[/C]0.046132[/C]-5.516577[/C]0[/C]0[/C][/ROW] [ROW][C]S-Constant[/C]0[/C]0[/C]0[/C]1[/C]0.5[/C][/ROW] [ROW][C]S-t^1[/C]-0.338746[/C]0.046171[/C]-7.336707[/C]0[/C]0[/C][/ROW] [ROW][C]S-M1[t][/C]-0.435266[/C]0.051626[/C]-8.431063[/C]0[/C]0[/C][/ROW] [ROW][C]S-M2[t][/C]-0.608027[/C]0.051613[/C]-11.780564[/C]0[/C]0[/C][/ROW] [ROW][C]S-M3[t][/C]-0.561336[/C]0.051624[/C]-10.873653[/C]0[/C]0[/C][/ROW] [ROW][C]S-M4[t][/C]-0.664571[/C]0.051594[/C]-12.88072[/C]0[/C]0[/C][/ROW] [ROW][C]S-M5[t][/C]-0.534875[/C]0.051603[/C]-10.365202[/C]0[/C]0[/C][/ROW] [ROW][C]S-M6[t][/C]-0.583153[/C]0.05158[/C]-11.305814[/C]0[/C]0[/C][/ROW] [ROW][C]S-M7[t][/C]-0.512481[/C]0.051587[/C]-9.934392[/C]0[/C]0[/C][/ROW] [ROW][C]S-M8[t][/C]-0.493182[/C]0.05157[/C]-9.563429[/C]0[/C]0[/C][/ROW] [ROW][C]S-M9[t][/C]-0.444338[/C]0.051574[/C]-8.615512[/C]0[/C]0[/C][/ROW] [ROW][C]S-M10[t][/C]-0.305914[/C]0.051563[/C]-5.932778[/C]0[/C]0[/C][/ROW] [ROW][C]S-M11[t][/C]-0.116656[/C]0.051566[/C]-2.262267[/C]0.02489[/C]0.012445[/C][/ROW] [ROW][C]*Note[/C]computed against deterministic endogenous series[/C][/ROW] [ROW]Variable[/C]Partial Correlation[/C][/ROW] [ROW][C]x[t][/C]-0.382109[/C][/ROW] [ROW][C]Constant[/C]0.969397[/C][/ROW] [ROW][C]t^1[/C]-0.481858[/C][/ROW] [ROW][C]M1[t][/C]-0.534208[/C][/ROW] [ROW][C]M2[t][/C]-0.66189[/C][/ROW] [ROW][C]M3[t][/C]-0.631766[/C][/ROW] [ROW][C]M4[t][/C]-0.69457[/C][/ROW] [ROW][C]M5[t][/C]-0.613511[/C][/ROW] [ROW][C]M6[t][/C]-0.646499[/C][/ROW] [ROW][C]M7[t][/C]-0.597232[/C][/ROW] [ROW][C]M8[t][/C]-0.582596[/C][/ROW] [ROW][C]M9[t][/C]-0.542482[/C][/ROW] [ROW][C]M10[t][/C]-0.406319[/C][/ROW] [ROW][C]M11[t][/C]-0.167178[/C][/ROW] [ROW][C]Critical Values (alpha = 5%)[/C][/ROW] [ROW][C]1-tail CV at 5%[/C]1.65[/C][/ROW] [ROW][C]2-tail CV at 5%[/C]1.96[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=5910&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5910&T=1

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
x[t]-226.38503441.037226-5.51657700
Constant2325.82822844.14871652.68167300
t^1-1.7648550.240551-7.33670700
M1[t]-454.90468453.95579-8.43106300
M2[t]-635.46105353.941479-11.78056400
M3[t]-586.66340953.952742-10.87365300
M4[t]-694.55634353.922166-12.8807200
M5[t]-559.00869853.931287-10.36520200
M6[t]-609.46413253.907141-11.30581400
M7[t]-535.60398753.914117-9.93439200
M8[t]-515.43442153.896405-9.56342900
M9[t]-464.38677753.901237-8.61551200
M10[t]-319.71721153.889963-5.93277800
M11[t]-121.91956653.892648-2.2622670.024890.012445
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%x[t]-0.0162360.002943-334.25869500
%Constant1.3924550.02643114.84801800
%t^1-0.1019620.013898-64.61831700
%M1[t]-0.0226960.002692-363.05247100
%M2[t]-0.0317040.002691-359.80152400
%M3[t]-0.0292690.002692-360.63086800
%M4[t]-0.0346520.00269-358.83445400
%M5[t]-0.027890.002691-361.28710800
%M6[t]-0.0304070.002689-360.51296900
%M7[t]-0.0267220.00269-361.83627600
%M8[t]-0.0257160.002689-362.32941600
%M9[t]-0.0231690.002689-363.24399900
%M10[t]-0.0159510.002689-366.00452300
%M11[t]-0.0060830.002689-369.65650800
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-x[t]-0.2544910.046132-5.51657700
S-Constant00010.5
S-t^1-0.3387460.046171-7.33670700
S-M1[t]-0.4352660.051626-8.43106300
S-M2[t]-0.6080270.051613-11.78056400
S-M3[t]-0.5613360.051624-10.87365300
S-M4[t]-0.6645710.051594-12.8807200
S-M5[t]-0.5348750.051603-10.36520200
S-M6[t]-0.5831530.05158-11.30581400
S-M7[t]-0.5124810.051587-9.93439200
S-M8[t]-0.4931820.05157-9.56342900
S-M9[t]-0.4443380.051574-8.61551200
S-M10[t]-0.3059140.051563-5.93277800
S-M11[t]-0.1166560.051566-2.2622670.024890.012445
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
x[t]-0.382109
Constant0.969397
t^1-0.481858
M1[t]-0.534208
M2[t]-0.66189
M3[t]-0.631766
M4[t]-0.69457
M5[t]-0.613511
M6[t]-0.646499
M7[t]-0.597232
M8[t]-0.582596
M9[t]-0.542482
M10[t]-0.406319
M11[t]-0.167178
Critical Values (alpha = 5%)
1-tail CV at 5%1.65
2-tail CV at 5%1.96






Multiple Linear Regression - Regression Statistics
Multiple R0.861322
R-squared0.741876
Adjusted R-squared0.723025
F-TEST39.353229
Observations192
Degrees of Freedom178
Multiple Linear Regression - Residual Statistics
Standard Error152.41776
Sum Squared Errors4135148.87029
Log Likelihood-1230.279896
Durbin-Watson0.918093
Von Neumann Ratio0.9229
# e[t] > 0100
# e[t] < 092
# Runs66
Stand. Normal Runs Statistic-4.469906

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Regression Statistics \tabularnewline

Multiple R
0.861322 \tabularnewline R-squared0.741876 \tabularnewline Adjusted R-squared0.723025 \tabularnewline F-TEST39.353229 \tabularnewline Observations192 \tabularnewline Degrees of Freedom178 \tabularnewline Multiple Linear Regression - Residual Statistics \tabularnewline Standard Error152.41776 \tabularnewline Sum Squared Errors4135148.87029 \tabularnewline Log Likelihood-1230.279896 \tabularnewline Durbin-Watson0.918093 \tabularnewline Von Neumann Ratio0.9229 \tabularnewline # e[t] > 0100 \tabularnewline # e[t] < 092 \tabularnewline # Runs66 \tabularnewline Stand. Normal Runs Statistic-4.469906 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=5910&T=2

[TABLE]

[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]

[ROW][C]Multiple R[/C]
0.861322[/C][/ROW] [ROW][C]R-squared[/C]0.741876[/C][/ROW] [ROW][C]Adjusted R-squared[/C]0.723025[/C][/ROW] [ROW][C]F-TEST[/C]39.353229[/C][/ROW] [ROW][C]Observations[/C]192[/C][/ROW] [ROW][C]Degrees of Freedom[/C]178[/C][/ROW] [ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW] [ROW][C]Standard Error[/C]152.41776[/C][/ROW] [ROW][C]Sum Squared Errors[/C]4135148.87029[/C][/ROW] [ROW][C]Log Likelihood[/C]-1230.279896[/C][/ROW] [ROW][C]Durbin-Watson[/C]0.918093[/C][/ROW] [ROW][C]Von Neumann Ratio[/C]0.9229[/C][/ROW] [ROW][C]# e[t] > 0[/C]100[/C][/ROW] [ROW][C]# e[t] < 0[/C]92[/C][/ROW] [ROW][C]# Runs[/C]66[/C][/ROW] [ROW][C]Stand. Normal Runs Statistic[/C]-4.469906[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=5910&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5910&T=2

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.861322
R-squared0.741876
Adjusted R-squared0.723025
F-TEST39.353229
Observations192
Degrees of Freedom178
Multiple Linear Regression - Residual Statistics
Standard Error152.41776
Sum Squared Errors4135148.87029
Log Likelihood-1230.279896
Durbin-Watson0.918093
Von Neumann Ratio0.9229
# e[t] > 0100
# e[t] < 092
# Runs66
Stand. Normal Runs Statistic-4.469906






Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error24925.113158
Akaike (1973) Log Information Criterion10.123372
Akaike (1974) Information Criterion24918.651283
Schwarz (1978) Log Criterion10.360898
Schwarz (1978) Criterion31599.530877
Craven-Wahba (1979) Generalized Cross Validation25058.344372
Hannan-Quinn (1979) Criterion27434.908117
Rice (1984) Criterion25214.32238
Shibata (1981) Criterion24678.080281

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ad Hoc Selection Test Statistics \tabularnewline

Akaike (1969) Final Prediction Error
24925.113158 \tabularnewline Akaike (1973) Log Information Criterion10.123372 \tabularnewline Akaike (1974) Information Criterion24918.651283 \tabularnewline Schwarz (1978) Log Criterion10.360898 \tabularnewline Schwarz (1978) Criterion31599.530877 \tabularnewline Craven-Wahba (1979) Generalized Cross Validation25058.344372 \tabularnewline Hannan-Quinn (1979) Criterion27434.908117 \tabularnewline Rice (1984) Criterion25214.32238 \tabularnewline Shibata (1981) Criterion24678.080281 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=5910&T=3

[TABLE]

[ROW][C]Multiple Linear Regression - Ad Hoc Selection Test Statistics[/C][/ROW]

[ROW][C]Akaike (1969) Final Prediction Error[/C]
24925.113158[/C][/ROW] [ROW][C]Akaike (1973) Log Information Criterion[/C]10.123372[/C][/ROW] [ROW][C]Akaike (1974) Information Criterion[/C]24918.651283[/C][/ROW] [ROW][C]Schwarz (1978) Log Criterion[/C]10.360898[/C][/ROW] [ROW][C]Schwarz (1978) Criterion[/C]31599.530877[/C][/ROW] [ROW][C]Craven-Wahba (1979) Generalized Cross Validation[/C]25058.344372[/C][/ROW] [ROW][C]Hannan-Quinn (1979) Criterion[/C]27434.908117[/C][/ROW] [ROW][C]Rice (1984) Criterion[/C]25214.32238[/C][/ROW] [ROW][C]Shibata (1981) Criterion[/C]24678.080281[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=5910&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5910&T=3

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


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

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error24925.113158
Akaike (1973) Log Information Criterion10.123372
Akaike (1974) Information Criterion24918.651283
Schwarz (1978) Log Criterion10.360898
Schwarz (1978) Criterion31599.530877
Craven-Wahba (1979) Generalized Cross Validation25058.344372
Hannan-Quinn (1979) Criterion27434.908117
Rice (1984) Criterion25214.32238
Shibata (1981) Criterion24678.080281






Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression1311884881.999502914221.692269
Residual1784135148.8702923231.173429
Total19116020030.86979283874.507171684
F-TEST39.353229
p-value0

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Analysis of Variance \tabularnewline

ANOVA & DF & Sum of Squares & Mean Square \tabularnewline

Regression
1311884881.999502914221.692269 \tabularnewline Residual1784135148.8702923231.173429 \tabularnewline Total19116020030.86979283874.507171684 \tabularnewline F-TEST39.353229 \tabularnewline p-value0 \tabularnewline
\hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=5910&T=4

[TABLE]

[ROW][C]Multiple Linear Regression - Analysis of Variance[/C][/ROW]

[ROW][C]ANOVA[/C][C]DF[/C][C]Sum of Squares[/C][C]Mean Square[/C][/ROW]

[ROW][C]Regression[/C]
13[/C]11884881.999502[/C]914221.692269[/C][/ROW] [ROW][C]Residual[/C]178[/C]4135148.87029[/C]23231.173429[/C][/ROW] [ROW][C]Total[/C]191[/C]16020030.869792[/C]83874.507171684[/C][/ROW] [ROW][C]F-TEST[/C]39.353229[/C][/ROW] [ROW][C]p-value[/C]0[/C][/ROW]
[/TABLE] Source: https://freestatistics.org/blog/index.php?pk=5910&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5910&T=4

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


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

Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression1311884881.999502914221.692269
Residual1784135148.8702923231.173429
Total19116020030.86979283874.507171684
F-TEST39.353229
p-value0


Figures (Output of Computation)

Input Parameters & R Code

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