10-46. 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: 1. Nandita performs a regression analysis, comparing each month's online advertising expense with that month's revenue Verify that she obtains the following result Sales revenue =$51,999.64(0.98 Online advertising expense ) 2. Plot the preceding data on a graph and draw the regression line. What does the cost formula indicate about the relationstip between monthly online advertiting expense and monthly sales revenue? is the relationshap economically plausibie? 3. After further thought, Nandita realizes there may have been a flaw in her approsch. in purticulas, there may be a lag between the time eustomens click through to the Modus website and peruse its social media content (Whilch ts when the online ad expense is incurred) and the time they actually shop in the phivsical store. Nandita modifles her aralyais by comparing each month's sales revenue to the advertising expense in the prior month After discarding September sales revenue and August adveatiting expense, show that the moditied regression yrelds the folsoving Sales revenue =$28,361.37+(5.38 Online advertising expense )