Russo decided to first assess the effects of ad copy and advertising on sales by
ID: 3376473 • Letter: R
Question
Russo decided to first assess the effects of ad copy and advertising on sales by running a regression, with "Sales" being the dependent variable. The results are shown below. Based on the results, please explain: 1. What do Model Summary and Anova Table tell us about this model? Be specific; 2. Explain the effect of each independent variable (DumCopy, DumSeg, NopaneAd$, CompAdS) on sales. Again, be specific. Model Summary Adjusted R Std. Error of the Model R Square Square Estimate 767a .589 .502 3.411 a. Predictors: (Constant), DumCopy, DumSeg, NopaneAd$, CompAd$ ANOVAa df Model Sum of Squares 316.744 221.090 537.833 Mean Square Sig 4 19 23 79.186 6.805 001 Residual 11.636 Total a. Dependent Variable: UnitSales b. Predictors: (Constant), DumCopy, DumSeg, NopaneAd$, CompAd$Explanation / Answer
a)
From the ANOVA Table, Since the p-value is less than 0.05, the model is significant.
The R Square of the model is 0.598 ie the independent variables help in explaining 59.8% of the variation in the dependent variable.
b)
Regression Equation:
UnitSales = 32.594 + 1.477 * Nopane – 0.565 * CompanyAd + 0.351 * DumSeg + 2.134 * DumCopy
Since the p-value for Nopane is less than 0.05, hence this variable is significant in explaining the variation in the dependent variable(UnitSales)
The p-value for CompanyAd is less than 0.05, hence this variable is significant in explaining the variation in the dependent variable(UnitSales)
The p-value for DumSeg is greater than 0.05, hence this variable is not significant in explaining the variation in the dependent variable(UnitSales)
The p-value for DumCopy is greater than 0.05, hence this variable is not significant in explaining the variation in the dependent variable(UnitSales)