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Conduct a multiple regression analysis, using ‘monthly sales value’ as the Dependent Variable and entering all other variables simultaneously as the predictors. Determine the regression equation. Which are the best p

Conduct a multiple regression analysis, using ‘monthly sales value’ as the Dependent Variable and entering all other variables simultaneously as the predictors. Determine the regression equation. Which are the best p

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Could you please help interpret this SPSS output, i already conducted the multiple regression analysis i just need 1 and 2...THIS IS THE COMPLETE QUESTION

Conduct a multiple regression analysis, using ‘monthly sales value’ as the Dependent Variable and entering all other variables simultaneously as the predictors.

  1. Determine the regression equation.
  2. Which are the best predictors and which predictors contribute very little to the estimate of mean monthly sales value? Interpret the regression results in terms of (1) the variance explained, (2) the overall significance of the regression equation, and (3) the significance, sign and value of each regression coefficient.
Distance in kms from .764 -.025 -.003 .170 5.898 nearest competitor median housing cost in $k within 5km radius Branches of multiple .681 -.096 -.013 .335 2.988 a. Dependent Variable: Value of monthly sales in $k in 2007 .320 .030 .004 .445 2.247 store Floor area in sq mts .954 .716 .135 .116 8.596 Residuals Statistics Std. Minimum Maximum Mean Deviation Predicted Value 2652.0798 11307.1230 5826.9286 2970.58071 14 a. Dependent Variable: Value of monthly sales in $k in 2007 Residual -707.65735 765.92017 .00000 394.56188 14 Std. Predicted Value -1.069 1.845 .000 1.000 14 Collinearity Diagnostics: Std. Residual -1.316 1.424 .000 .734 14 Variance Proportions a. Dependent Variable: Value of monthly sales in $k in 2007 Number of Number of Eigenvalu Condition employees in branch carparking Model Dimension e Index (Constant) spaces .00 1 1 6.492 1.000 .00 .00 Charts .239 5.217 .01 .00 .01 6.246 10.194 .166 .02 .01 .00 4 .062 .00 .04 .00 .026 15.955 .02 .37 .01 Histogram .010 24.880 .22 .34 .59 Dependent Variable: Value of monthly sales in $k in 2007 7 .004 38.306 .73 .24 .38 Mean = -1.47E-15 Std. Dev, N= 14 Collinearity Diagnostics Variance Proportions Distance in median housing cost in within kms from nearest Branches of Floor area in Model Dimension competitor 5km radius multiple store sq mts 1 1 .00 .00 .00 .00 .00 .00 .13 .02 .02 .01 .27 .01 4 .38 .00 .10 .06 .01 .01 .11 .46 -1.5 -1.0 0.0 0.5 1.0 1.5 .07 .09 .11 .18 Regression Standardized Residual 7 .51 .28 .27 Frequency 888888| 88858%
Transcribed Image Text:Distance in kms from .764 -.025 -.003 .170 5.898 nearest competitor median housing cost in $k within 5km radius Branches of multiple .681 -.096 -.013 .335 2.988 a. Dependent Variable: Value of monthly sales in $k in 2007 .320 .030 .004 .445 2.247 store Floor area in sq mts .954 .716 .135 .116 8.596 Residuals Statistics Std. Minimum Maximum Mean Deviation Predicted Value 2652.0798 11307.1230 5826.9286 2970.58071 14 a. Dependent Variable: Value of monthly sales in $k in 2007 Residual -707.65735 765.92017 .00000 394.56188 14 Std. Predicted Value -1.069 1.845 .000 1.000 14 Collinearity Diagnostics: Std. Residual -1.316 1.424 .000 .734 14 Variance Proportions a. Dependent Variable: Value of monthly sales in $k in 2007 Number of Number of Eigenvalu Condition employees in branch carparking Model Dimension e Index (Constant) spaces .00 1 1 6.492 1.000 .00 .00 Charts .239 5.217 .01 .00 .01 6.246 10.194 .166 .02 .01 .00 4 .062 .00 .04 .00 .026 15.955 .02 .37 .01 Histogram .010 24.880 .22 .34 .59 Dependent Variable: Value of monthly sales in $k in 2007 7 .004 38.306 .73 .24 .38 Mean = -1.47E-15 Std. Dev, N= 14 Collinearity Diagnostics Variance Proportions Distance in median housing cost in within kms from nearest Branches of Floor area in Model Dimension competitor 5km radius multiple store sq mts 1 1 .00 .00 .00 .00 .00 .00 .13 .02 .02 .01 .27 .01 4 .38 .00 .10 .06 .01 .01 .11 .46 -1.5 -1.0 0.0 0.5 1.0 1.5 .07 .09 .11 .18 Regression Standardized Residual 7 .51 .28 .27 Frequency 888888| 88858%
Regression Sum of Squares Regression 114716546.93 Mean Square 6 19119424.49 df F Sig. <.001 Model 1 66.130 Variables Entered/Removeda 7 Variables Variables Residual 2023827.991 7 289118.284 Model Entered Removed Method Total 116740374.92 13 1 Floor area in Enter 9. sq mts, Branches of a. Dependent Variable: Value of monthly sales in $k in 2007 multiple store, median b. Predictors: (Constant), Floor area in sq mts, Branches of multiple store, median housing cost in $k within 5km radius, Number of employees in branch, Distance in kms from nearest competitor, Number of carparking spaces housing cost in $k within 5km radius, Number of Coefficients employees in branch, Unstandardized Standardized Coefficients Coefficients Distance in Model B Std. Error Beta Sig. kms from 1 (Constant) 505.676 1215.593 .416 .690 nearest competitor, Number of Number of employees in 91.408 83.206 .131 1.099 .308 branch carparking spaces Number of carparking 28.442 11.355 .521 2.505 .041 a. Dependent Variable: Value of monthly sales in $k in 2007 spaces Distance in kms from -9.787 145.917 -.008 -.067 .948 nearest competitor median housing cost in $k within 5km radius Branches of multiple b. All requested variables entered. -.995 3.910 -.022 -.254 .807 4.302 53.438 .006 .081 .938 Model Summary Adjusted R Square store Std. Error of Floor area in sq mts .700 .258 .396 2.713 .030 R Square the Estimate Model 1 a. Predictors: (Constant), Floor area in sq mts, Branches of multiple store, median housing cost in $k within 5km radius, Number of employees in branch, Distance in kms from nearest competitor, Number of carparking spaces .991a .983 .968 537.69721 Coefficients: Correlations Collinearity Statistics Model Zero-order Partial Part Tolerance VIF 1 (Constant) Number of employees in .892 .383 .055 .174 5.747 b. Dependent Variable: Value of monthly sales in $k in 2007 branch Number of carparking .975 .687 .125 .057 17.441 ANOVA: spaces
Transcribed Image Text:Regression Sum of Squares Regression 114716546.93 Mean Square 6 19119424.49 df F Sig. <.001 Model 1 66.130 Variables Entered/Removeda 7 Variables Variables Residual 2023827.991 7 289118.284 Model Entered Removed Method Total 116740374.92 13 1 Floor area in Enter 9. sq mts, Branches of a. Dependent Variable: Value of monthly sales in $k in 2007 multiple store, median b. Predictors: (Constant), Floor area in sq mts, Branches of multiple store, median housing cost in $k within 5km radius, Number of employees in branch, Distance in kms from nearest competitor, Number of carparking spaces housing cost in $k within 5km radius, Number of Coefficients employees in branch, Unstandardized Standardized Coefficients Coefficients Distance in Model B Std. Error Beta Sig. kms from 1 (Constant) 505.676 1215.593 .416 .690 nearest competitor, Number of Number of employees in 91.408 83.206 .131 1.099 .308 branch carparking spaces Number of carparking 28.442 11.355 .521 2.505 .041 a. Dependent Variable: Value of monthly sales in $k in 2007 spaces Distance in kms from -9.787 145.917 -.008 -.067 .948 nearest competitor median housing cost in $k within 5km radius Branches of multiple b. All requested variables entered. -.995 3.910 -.022 -.254 .807 4.302 53.438 .006 .081 .938 Model Summary Adjusted R Square store Std. Error of Floor area in sq mts .700 .258 .396 2.713 .030 R Square the Estimate Model 1 a. Predictors: (Constant), Floor area in sq mts, Branches of multiple store, median housing cost in $k within 5km radius, Number of employees in branch, Distance in kms from nearest competitor, Number of carparking spaces .991a .983 .968 537.69721 Coefficients: Correlations Collinearity Statistics Model Zero-order Partial Part Tolerance VIF 1 (Constant) Number of employees in .892 .383 .055 .174 5.747 b. Dependent Variable: Value of monthly sales in $k in 2007 branch Number of carparking .975 .687 .125 .057 17.441 ANOVA: spaces
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