Sales: Monthly sales volume in thousand cases (a case contains 12 liters of juice)

TVAd : Monthly spending on TV advertising in thousand Dollars

OnlineAd : Monthly spending on online advertising (mostly display ads) in thousand Dollars

A regression analysis was applied on XYZ historical dataset and produced this summarized regression output::

Sales = 121 + 0.41*TVAd + 0.32*OnlineAd R-squared=0.55 F-Statistic=12.83 p-value=0.01 (for the overall regression) All regression coefficients are statistically significant at the 5% level.

Use this output to answer the following questions.

For the purpose of this exercise, assume that you can interpret the estimated coefficient values as causal effects of advertising on sales.

A. Is the overall regression equation statistically significant at the 5% level? Give reasons for the same?

B. How do you interpret the R-squared value of 0.55?

C. By how much would the sales volume increase if XYZ increases its TV advertising spending by one thousand Dollars?

D. What would be the predicted sales volume (thousand cases) if XYZ does not advertise either on TV or online?

E. By how much would the sales volume increase if XYZ increases its online advertising spending by one thousand Dollars?

F. If XYZ makes a net margin of $6 per case, what is the impact of an incremental one thousand Dollar TV advertising spend on profit?