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a. Statement of the Problem: Does Price (X3) and Promotion (X4) predict Satisfaction (X2)? b. Conceptual Framework: Independent Variable X3 - Price X4 - Promotion Model Variables Entered Variables Removed 1 Price 2 Promotion a. Dependent Variable: Sales c. Null Hypothesis: Price (X3) and Promotion (X4) does not predict Sales (X2). d. Process: 1 2 a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales Model 1 Regression Residual Total Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson .735¹ .870⁰ 864.946 638.065 2 Regression Residual .540 .758 Model ANOVAⓇ Sum of df Squares 2.815E7 1 2.394E7 32 5.209E7 33 3.947E7 2 1.262E7 31 407127.312 5.209E7 33 B Unstandardized Coefficients .526 .742 Mean Square Total a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales Promotion .361 a. Dependent Variable: Sales 748130.978 Dependent Variable Std. Error 1 (Constant) 7512.348 734.619 Price -56.714 9.245 2 (Constant) 5837.521 628.150 Price -53.217 6.852 .069 X2 - Sales Variables Entered/Removed Method Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= 100). 2.815E7 37.632 .000⁰ F 1.974E7 48.477 .000 Sig. Standardized Coefficients Beta -.735 Coefficients t Sig. 10.226 .000 -6.134 .000 9.293 .000 -.690 -7.766 .000 468 5.273 .000 Zero- order -.735 -.735 .535 2.282 Correlations Partial -.735 -.813 .688 Part -.735 -.687 .466 Collinearity Statistics Tolerance 1.000 -991 .991 VIF 1.000 1.009 1.009

a. Statement of the Problem: Does Price (X3) and Promotion (X4) predict Satisfaction (X2)? b. Conceptual Framework: Independent Variable X3 - Price X4 - Promotion Model Variables Entered Variables Removed 1 Price 2 Promotion a. Dependent Variable: Sales c. Null Hypothesis: Price (X3) and Promotion (X4) does not predict Sales (X2). d. Process: 1 2 a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales Model 1 Regression Residual Total Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson .735¹ .870⁰ 864.946 638.065 2 Regression Residual .540 .758 Model ANOVAⓇ Sum of df Squares 2.815E7 1 2.394E7 32 5.209E7 33 3.947E7 2 1.262E7 31 407127.312 5.209E7 33 B Unstandardized Coefficients .526 .742 Mean Square Total a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales Promotion .361 a. Dependent Variable: Sales 748130.978 Dependent Variable Std. Error 1 (Constant) 7512.348 734.619 Price -56.714 9.245 2 (Constant) 5837.521 628.150 Price -53.217 6.852 .069 X2 - Sales Variables Entered/Removed Method Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= 100). 2.815E7 37.632 .000⁰ F 1.974E7 48.477 .000 Sig. Standardized Coefficients Beta -.735 Coefficients t Sig. 10.226 .000 -6.134 .000 9.293 .000 -.690 -7.766 .000 468 5.273 .000 Zero- order -.735 -.735 .535 2.282 Correlations Partial -.735 -.813 .688 Part -.735 -.687 .466 Collinearity Statistics Tolerance 1.000 -991 .991 VIF 1.000 1.009 1.009

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
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Model 1 1 Promotion .468³ 5.273 .000 a. Predictors in the Model: (Constant), Price b. Dependent Variable: Sales Collinearity Diagnostics Model Dimension Eigenvalue Condition Index 1 2 1 2 3 a. Dependent Variable: Sales 2 Beta In Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Regression Standardized Predicted Value t Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: Sales A 1.979 .021 2.868 -114 .018 0 Excluded Variables Sig. Partial Correlation 1.000 9.803 1.000 5.014 12.618 O .012 .000 .000 Residuals Statistics Minimum Maximum Mean Std. Deviation N 1291.62 4865.53 3098.68 1093.683 34 -1.652 .000 1.000 34 1.616 241.166 186.182 36.022 34 110.077 1190.06 4974.50 3095.85 1094.978 34 -1.681E3 1342.426 -2.634 2.104 -2.732 2.136 -1.807E3 1383.604 -3.084 Scatterplot 0 00 Dependent Variable: Sales 00 O Variance Proportions (Constant) Price Promotion .01 .01 .99 .99 .00 .00 .02 .09 .98 .90 2.275 3.744 .187 .113 0 8 DO .688 O O Collinearity Statistics Tolerance VIF Minimum Tolerance .991 1.009 .991 O .000 .000 .002 2.823 .000 1.941 .027 .059 O O -1 0 Regression Standardized Residual 618.428 34 .969 34 1.008 34 669.075 34 1.057 34 02 .84 .15 0 EN 0 1.018 34 .040 34 .031 34
Transcribed Image Text:Model 1 1 Promotion .468³ 5.273 .000 a. Predictors in the Model: (Constant), Price b. Dependent Variable: Sales Collinearity Diagnostics Model Dimension Eigenvalue Condition Index 1 2 1 2 3 a. Dependent Variable: Sales 2 Beta In Std. Residual Stud. Residual Deleted Residual Stud. Deleted Residual Predicted Value Std. Predicted Value Standard Error of Predicted Value Adjusted Predicted Value Residual Regression Standardized Predicted Value t Mahal. Distance Cook's Distance Centered Leverage Value a. Dependent Variable: Sales A 1.979 .021 2.868 -114 .018 0 Excluded Variables Sig. Partial Correlation 1.000 9.803 1.000 5.014 12.618 O .012 .000 .000 Residuals Statistics Minimum Maximum Mean Std. Deviation N 1291.62 4865.53 3098.68 1093.683 34 -1.652 .000 1.000 34 1.616 241.166 186.182 36.022 34 110.077 1190.06 4974.50 3095.85 1094.978 34 -1.681E3 1342.426 -2.634 2.104 -2.732 2.136 -1.807E3 1383.604 -3.084 Scatterplot 0 00 Dependent Variable: Sales 00 O Variance Proportions (Constant) Price Promotion .01 .01 .99 .99 .00 .00 .02 .09 .98 .90 2.275 3.744 .187 .113 0 8 DO .688 O O Collinearity Statistics Tolerance VIF Minimum Tolerance .991 1.009 .991 O .000 .000 .002 2.823 .000 1.941 .027 .059 O O -1 0 Regression Standardized Residual 618.428 34 .969 34 1.008 34 669.075 34 1.057 34 02 .84 .15 0 EN 0 1.018 34 .040 34 .031 34
a. Statement of the Problem: Does Price (X3) and Promotion (X4) predict Satisfaction (X2)? b. Conceptual Framework: Independent Variable X3 - Price X4 - Promotion Model Variables Entered Variables Removed 1 Price 2 Promotion a. Dependent Variable: Sales c. Null Hypothesis: Price (X3) and Promotion (X4) does not predict Sales (X2). d. Process: 1 2 a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales Model Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 735¹ 864.946 .526 742 .870 638.065 Sum of Squares 2.815E7 1 2.394E7 32 748130.978 5.209E7 33 3.947E7 2 1.262E7 31 407127.312 Total 5.209E7 33 a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales 1 Regression Residual Total 2 Regression Residual Model 540 .758 1 (Constant) Price ANOVAⓇ df Unstandardized Coefficients B Mean Square Dependent Variable X2 - Sales Std. Error 7512.348 734.619 -56.714 9.245 2 (Constant) 5837.521 628.150 Price -53.217 6.852 Promotion .361 .069 a. Dependent Variable: Sales Variables Entered/Removed Method Stepwise (Criteria: Probability-of-F-to-enter <= .050. Probability-of-F-to-remove >= .100). Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). F 2.815E7 37.632 .000² 1.974E7 48.477 .000⁰ Sig. Standardized Coefficients Beta Coefficients t Sig. 10.226.000 -.735 -6.134.000 9.293 .000 -.690 -7.766 .000 .468 5.273.000 Zero- order -.735 2.282 -.735 535 Correlations Partial -.735 -.813 .688 Part -.735 -.687 .466 Collinearity Statistics Tolerance 1.000 .991 .991 VIF 1.000 1.009 1.009
Transcribed Image Text:a. Statement of the Problem: Does Price (X3) and Promotion (X4) predict Satisfaction (X2)? b. Conceptual Framework: Independent Variable X3 - Price X4 - Promotion Model Variables Entered Variables Removed 1 Price 2 Promotion a. Dependent Variable: Sales c. Null Hypothesis: Price (X3) and Promotion (X4) does not predict Sales (X2). d. Process: 1 2 a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales Model Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 735¹ 864.946 .526 742 .870 638.065 Sum of Squares 2.815E7 1 2.394E7 32 748130.978 5.209E7 33 3.947E7 2 1.262E7 31 407127.312 Total 5.209E7 33 a. Predictors: (Constant), Price b. Predictors: (Constant), Price, Promotion c. Dependent Variable: Sales 1 Regression Residual Total 2 Regression Residual Model 540 .758 1 (Constant) Price ANOVAⓇ df Unstandardized Coefficients B Mean Square Dependent Variable X2 - Sales Std. Error 7512.348 734.619 -56.714 9.245 2 (Constant) 5837.521 628.150 Price -53.217 6.852 Promotion .361 .069 a. Dependent Variable: Sales Variables Entered/Removed Method Stepwise (Criteria: Probability-of-F-to-enter <= .050. Probability-of-F-to-remove >= .100). Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). F 2.815E7 37.632 .000² 1.974E7 48.477 .000⁰ Sig. Standardized Coefficients Beta Coefficients t Sig. 10.226.000 -.735 -6.134.000 9.293 .000 -.690 -7.766 .000 .468 5.273.000 Zero- order -.735 2.282 -.735 535 Correlations Partial -.735 -.813 .688 Part -.735 -.687 .466 Collinearity Statistics Tolerance 1.000 .991 .991 VIF 1.000 1.009 1.009
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