Interpreting regression results, matching time periods. Nandita Summers works at Mod...

Interpreting regression results, matching time periods. Nandita Summers works at Modus, a store that caters to fashion for young adults. Nandita is responsible for the store’s online advertising and promotion budget. For the past year, she has studied search engine optimization and has been purchasing keywords and display advertising on Google, Facebook, and Twitter. In order to analyze the effectiveness of her efforts and to decide whether to continue online advertising or move her advertising dollars back to traditional print media, Nandita collects the following data:

Nandita performs a regression analysis, comparing each month’s online advertising expense with that month’s revenue. Verify that she obtains the following result:

2. Plot the preceding data on a graph and draw the regression line. What does the cost formula indicate

about the relationship between monthly online advertising expense and monthly revenues? Is the relationship

economically plausible?

3. After further thought, Nandita realizes there may have been a flaw in her approach. In particular, there

may be a lag between the time customers click through to the Modus website and peruse its social

media content (which is when the online ad expense is incurred) and the time they actually shop in

the physical store. Nandita modifies her analysis by comparing each month’s sales revenue to the

advertising expense in the prior month. After discarding September revenue and August advertising

expense, show that the modified regression yields the following:

4. What does the revised formula indicate? Plot the revised data on a graph. Is this relationship economically

plausible?

5. Can Nandita conclude that there is a cause-and-effect relationship between online advertising expense

and sales revenue? Why or why not?