Case Analysis: Answer all questions

Gross profit is a key indicator of enterprise benefits and business performance for a company. The regional manager of a clothes retailing chain company has noted that the gross profit margins (defined in a variable with the name of Profit) that individual shops are able to achieve may well be affected by the local advertising used on the radio (defined in a variable with the name of Radioads) and/or in newspapers (defined in a variable with the name of Newsads). If so, the company plans to adjust their advertising spending accordingly to promote its profit. To explore the influence, market researchers sampled 100 shops in his region and collected data. Data analysis was conducted in SPSS to support the decision making of this clothes retailing company.

Profit: gross profit as % of sales revenue

Radioads: radio advertising spending ()

Newsads: newspaper advertising spending ()

-------------

The profit (Profit) has been regressed against the amount of radio advertising spending (Radioads) and the amount of newspaper advertising spending (Newsads) separately using SPSS, with the results shown under the headings MODEL 1 and MODEL 2 in Appendix I and II respectively. Please answer the following questions supposing that you have checked that the usual assumptions needed for regression hold.

4(a). Determine whether the amount of radio advertising spending or the amount of newspaper advertising spending would provide the better indicator of the profit. Explain your conclusions carefully.

4(b). Use your preferred model from part 4(a) to estimate the average profit of a shop with 3200 spending on radio advertising and 1800 on local newspaper advertising.

Appendix I: SPSS Output of Model 1 Variables Entered/Removed Variables Variables Model Entered Removed Method 1 Radioadsb a. Dependent Variable: Profit b. All requested variables entered. Model R R Square 1 906 .820 a. Predictors: (Constant), Radioads Model 1 Regression Residual Total a. Dependent Variable: Profit b. Predictors: (Constant), Radioads Model 1 (Constant) Radioads a. Dependent Variable: Profit Model Summary Enter Adjusted R Square Sum of Squares 2701.940 591.185 3293.126 .819 ANOVA df Std. Error of the Estimate 2.45612 Mean Square 2701.940 6.033 Standardized Coefficients Beta 1 98 99 Coefficients Unstandardized Coefficients B Std. Error -6.038 .015 2.076 .001 .906 F 447.897 -2.909 21.164 Sig. .000b Sig. .004 .000 Appendix II: SPSS Output of Model 2 Variables Entered/Removed Variables Variables Model Entered Removed Method 1 Newsadsb a. Dependent Variable: Profit b. All requested variables entered. Model R R Square 1 .839 .703 a. Predictors: (Constant), Newsads Model 1 Regression Residual Total a. Dependent Variable: Profit b. Predictors: (Constant), Newsads Model 1 (Constant) Newsads a. Dependent Variable: Profit Model Summary Enter Adjusted R Square Sum of Squares 2316.328 976.797 3293.126 .700 ANOVA df Std. Error of the Estimate 3.15711 Mean Square 1 98 99 Coefficients Unstandardized Coefficients B Std. Error -46.434 .049 5.520 .003 F 2316.328 232.392 9.967 Standardized Coefficients Beta .839 -8.412 15.244 Sig. .000b Sig. .000 .000