Topic 9 (Week 9) Exercise: The marketing manager of a chain of stores needed information about the effectiveness of television advertising on weekly sales. The manager collected data from 25 randomly selected stores. For each store, the variables "store sales" and "TV advertising" were recorded per week. Both variables are recorded in euros (i.e.1 unit-€1). You are given the following SPSS output. Model Summary Std. Error of the Estimate 2.43078 R Square Adjusted R Square 222 Model R. 471 .188 ANOVA Model Sum of Squares df Mean Square Sig. 38.764 5.909 38.764 6.560 017 Regression Residual 135.900 23 Total 174.663 24 Coefficients Standardized Coefficients Unstandardized Coefficients Std. Error 1.415 Model Sig. .000 B. Beta (Constant) 16.417 11.600 Television, 3.082 1.203 471 2,561 017 Answer the following questions:
The marketing manager of a chain of stores needed information about the
effectiveness of television advertising on weekly sales. The manager collected data from 25 randomly selected stores. For each store, the variables “store sales” and “TV advertising” were recorded per week.
Both variables are recorded in euros (i.e. 1 unit=€1).
You are given the following SPSS output. please see Image attached.
Answer the following questions:
(1) Test if television advertising generally affects the sales of this store. Use a 5% level of significance.
(2) Write down the estimated regression model and interpret the coefficients.
(3) Write down the value of the coefficient of determination and explain it. Is the fitting of
your regression model good?
(4) What is the value of the
expenditures on television advertising? Interpret it.
(5) Predict the weekly sales when television advertising is €700.
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