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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 computationFri, 25 Apr 2008 13:19:17 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Apr/25/t1209151597aegq0cdfaovar9u.htm/, Retrieved Thu, 09 May 2024 21:16:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=10725, Retrieved Thu, 09 May 2024 21:16:56 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsmegsteroo
Estimated Impact278

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Estimate Equation] [megans math] [2008-04-25 19:19:17] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
660	39
930	59
710	33
970	52
660	34
720	45
1010	68
1140	85
1130	66
490	37
1070	76
1030	74
470	17
460	17
680	40
770	48
920	58
1010	66
1160	76
150	84
370	21
420	25
290	12
340	16
420	22
510	29
620	39
820	55
1010	70
950	59
970	55
250	9
300	12
440	23
410	19
510	26
740	42
540	29
460	24
510	28

Tables (Output of Computation)





Multiple Linear Regression - Estimated Regression Equation
Calories[t] = +10.236144286881 Fat(g)[t] +243.27880748647 + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Calories[t] = +10.236144286881 Fat(g)[t] +243.27880748647 + e[t] \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10725&T=0

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW]
Calories[t] = +10.236144286881 Fat(g)[t] +243.27880748647 + e[t][/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10725&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10725&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
Calories[t] = +10.236144286881 Fat(g)[t] +243.27880748647 + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
Fat(g)[t]10.2361441.2750368.02811900
Constant243.27880760.5927454.0149820.000270.000135
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%Fat(g)[t]0.6398540.079702-4.5186845.9E-52.9E-5
%Constant0.3601460.089701-7.13321700
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-Fat(g)[t]0.7931520.0987978.02811900
S-Constant00010.5
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
Fat(g)[t]0.793152
Constant0.545763
Critical Values (alpha = 5%)
1-tail CV at 5%1.69
2-tail CV at 5%2.02

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ordinary Least Squares \tabularnewline
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value \tabularnewline Fat(g)[t]10.2361441.2750368.02811900 \tabularnewline Constant243.27880760.5927454.0149820.000270.000135 \tabularnewline \tabularnewline VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value \tabularnewline %Fat(g)[t]0.6398540.079702-4.5186845.9E-52.9E-5 \tabularnewline %Constant0.3601460.089701-7.13321700 \tabularnewline VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value \tabularnewline S-Fat(g)[t]0.7931520.0987978.02811900 \tabularnewline S-Constant00010.5 \tabularnewline *Notecomputed against deterministic endogenous series \tabularnewline VariablePartial Correlation \tabularnewline Fat(g)[t]0.793152 \tabularnewline Constant0.545763 \tabularnewline Critical Values (alpha = 5%) \tabularnewline 1-tail CV at 5%1.69 \tabularnewline 2-tail CV at 5%2.02 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10725&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]Fat(g)[t][/C]10.236144[/C]1.275036[/C]8.028119[/C]0[/C]0[/C][/ROW] [ROW][C]Constant[/C]243.278807[/C]60.592745[/C]4.014982[/C]0.00027[/C]0.000135[/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]%Fat(g)[t][/C]0.639854[/C]0.079702[/C]-4.518684[/C]5.9E-5[/C]2.9E-5[/C][/ROW] [ROW][C]%Constant[/C]0.360146[/C]0.089701[/C]-7.133217[/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-Fat(g)[t][/C]0.793152[/C]0.098797[/C]8.028119[/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]*Note[/C]computed against deterministic endogenous series[/C][/ROW] [ROW]Variable[/C]Partial Correlation[/C][/ROW] [ROW][C]Fat(g)[t][/C]0.793152[/C][/ROW] [ROW][C]Constant[/C]0.545763[/C][/ROW] [ROW][C]Critical Values (alpha = 5%)[/C][/ROW] [ROW][C]1-tail CV at 5%[/C]1.69[/C][/ROW] [ROW][C]2-tail CV at 5%[/C]2.02[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10725&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10725&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
Fat(g)[t]10.2361441.2750368.02811900
Constant243.27880760.5927454.0149820.000270.000135
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%Fat(g)[t]0.6398540.079702-4.5186845.9E-52.9E-5
%Constant0.3601460.089701-7.13321700
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-Fat(g)[t]0.7931520.0987978.02811900
S-Constant00010.5
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
Fat(g)[t]0.793152
Constant0.545763
Critical Values (alpha = 5%)
1-tail CV at 5%1.69
2-tail CV at 5%2.02






Multiple Linear Regression - Regression Statistics
Multiple R0.793152
R-squared0.62909
Adjusted R-squared0.619329
F-TEST64.450694
Observations40
Degrees of Freedom38
Multiple Linear Regression - Residual Statistics
Standard Error175.830139
Sum Squared Errors1174817.035044
Log Likelihood-262.512412
Durbin-Watson1.914131
Von Neumann Ratio1.963211
# e[t] > 024
# e[t] < 016
# Runs8
Stand. Normal Runs Statistic-4.075734

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Regression Statistics \tabularnewline

Multiple R
0.793152 \tabularnewline R-squared0.62909 \tabularnewline Adjusted R-squared0.619329 \tabularnewline F-TEST64.450694 \tabularnewline Observations40 \tabularnewline Degrees of Freedom38 \tabularnewline Multiple Linear Regression - Residual Statistics \tabularnewline Standard Error175.830139 \tabularnewline Sum Squared Errors1174817.035044 \tabularnewline Log Likelihood-262.512412 \tabularnewline Durbin-Watson1.914131 \tabularnewline Von Neumann Ratio1.963211 \tabularnewline # e[t] > 024 \tabularnewline # e[t] < 016 \tabularnewline # Runs8 \tabularnewline Stand. Normal Runs Statistic-4.075734 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10725&T=2

[TABLE]

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

[ROW][C]Multiple R[/C]
0.793152[/C][/ROW] [ROW][C]R-squared[/C]0.62909[/C][/ROW] [ROW][C]Adjusted R-squared[/C]0.619329[/C][/ROW] [ROW][C]F-TEST[/C]64.450694[/C][/ROW] [ROW][C]Observations[/C]40[/C][/ROW] [ROW][C]Degrees of Freedom[/C]38[/C][/ROW] [ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW] [ROW][C]Standard Error[/C]175.830139[/C][/ROW] [ROW][C]Sum Squared Errors[/C]1174817.035044[/C][/ROW] [ROW][C]Log Likelihood[/C]-262.512412[/C][/ROW] [ROW][C]Durbin-Watson[/C]1.914131[/C][/ROW] [ROW][C]Von Neumann Ratio[/C]1.963211[/C][/ROW] [ROW][C]# e[t] > 0[/C]24[/C][/ROW] [ROW][C]# e[t] < 0[/C]16[/C][/ROW] [ROW][C]# Runs[/C]8[/C][/ROW] [ROW][C]Stand. Normal Runs Statistic[/C]-4.075734[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10725&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10725&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 R0.793152
R-squared0.62909
Adjusted R-squared0.619329
F-TEST64.450694
Observations40
Degrees of Freedom38
Multiple Linear Regression - Residual Statistics
Standard Error175.830139
Sum Squared Errors1174817.035044
Log Likelihood-262.512412
Durbin-Watson1.914131
Von Neumann Ratio1.963211
# e[t] > 024
# e[t] < 016
# Runs8
Stand. Normal Runs Statistic-4.075734






Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error32462.049653
Akaike (1973) Log Information Criterion10.387744
Akaike (1974) Information Criterion32459.34053
Schwarz (1978) Log Criterion10.472187
Schwarz (1978) Criterion35319.394001
Craven-Wahba (1979) Generalized Cross Validation32543.408173
Hannan-Quinn (1979) Criterion33465.682794
Rice (1984) Criterion32633.806529
Shibata (1981) Criterion32307.468464

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ad Hoc Selection Test Statistics \tabularnewline

Akaike (1969) Final Prediction Error
32462.049653 \tabularnewline Akaike (1973) Log Information Criterion10.387744 \tabularnewline Akaike (1974) Information Criterion32459.34053 \tabularnewline Schwarz (1978) Log Criterion10.472187 \tabularnewline Schwarz (1978) Criterion35319.394001 \tabularnewline Craven-Wahba (1979) Generalized Cross Validation32543.408173 \tabularnewline Hannan-Quinn (1979) Criterion33465.682794 \tabularnewline Rice (1984) Criterion32633.806529 \tabularnewline Shibata (1981) Criterion32307.468464 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10725&T=3

[TABLE]

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

[ROW][C]Akaike (1969) Final Prediction Error[/C]
32462.049653[/C][/ROW] [ROW][C]Akaike (1973) Log Information Criterion[/C]10.387744[/C][/ROW] [ROW][C]Akaike (1974) Information Criterion[/C]32459.34053[/C][/ROW] [ROW][C]Schwarz (1978) Log Criterion[/C]10.472187[/C][/ROW] [ROW][C]Schwarz (1978) Criterion[/C]35319.394001[/C][/ROW] [ROW][C]Craven-Wahba (1979) Generalized Cross Validation[/C]32543.408173[/C][/ROW] [ROW][C]Hannan-Quinn (1979) Criterion[/C]33465.682794[/C][/ROW] [ROW][C]Rice (1984) Criterion[/C]32633.806529[/C][/ROW] [ROW][C]Shibata (1981) Criterion[/C]32307.468464[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10725&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10725&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 Error32462.049653
Akaike (1973) Log Information Criterion10.387744
Akaike (1974) Information Criterion32459.34053
Schwarz (1978) Log Criterion10.472187
Schwarz (1978) Criterion35319.394001
Craven-Wahba (1979) Generalized Cross Validation32543.408173
Hannan-Quinn (1979) Criterion33465.682794
Rice (1984) Criterion32633.806529
Shibata (1981) Criterion32307.468464






Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression11992572.9649561992572.964956
Residual381174817.03504430916.237764
Total39316739081215.128205128
F-TEST64.450694
p-value0

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Analysis of Variance \tabularnewline

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

Regression
11992572.9649561992572.964956 \tabularnewline Residual381174817.03504430916.237764 \tabularnewline Total39316739081215.128205128 \tabularnewline F-TEST64.450694 \tabularnewline p-value0 \tabularnewline
\hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=10725&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]
1[/C]1992572.964956[/C]1992572.964956[/C][/ROW] [ROW][C]Residual[/C]38[/C]1174817.035044[/C]30916.237764[/C][/ROW] [ROW][C]Total[/C]39[/C]3167390[/C]81215.128205128[/C][/ROW] [ROW][C]F-TEST[/C]64.450694[/C][/ROW] [ROW][C]p-value[/C]0[/C][/ROW]
[/TABLE] Source: https://freestatistics.org/blog/index.php?pk=10725&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10725&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
Regression11992572.9649561992572.964956
Residual381174817.03504430916.237764
Total39316739081215.128205128
F-TEST64.450694
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):