Regression # 1 & 2 1) For Regression #1, what is the elasticity (a number)? In words, what does this mean? 2) For Regression #1, intercept the "Sale" coefficient ( 2 ). That is, in words tell me how to interpret the coefficient. . 3) For Regression #2, what is the elasticity of Relist items? Is the elasticity of Relist items different from non-Relist items? How do I tell this? Relist items are items that have been sold previously - for example, a shirt that was sold in January 1999 and January 2000. Non-relist items are "new" and are appearing for the first time. Given this, do your results make sense? 4) Answer the following questions for Regression #2: a) If an item is discounted 15%, what is the expected % increase in sales (do this for both relist and non-relist items)? 5) For this question, assume that only the price changes and all other factors are held constant (e.g., if an item has "sale" sign, it keeps it in your analysis). Use only data from Book 1 (rows 2- 173 and columns labeled Book 1); use Regression #2; use the cost data given in the spreadsheet. a) For Item 1233485 (row 3) in Book 1: What is the BE quantity for a 5% discount? What is the expected quantity sold for a 5% discount? Do we expect the price cut to be profitable? b) For how many items sold in Book 1 is a 5% discount profitable? (your answer is a number between 1 and 171). c) Management is under pressure to raise margins and would like your input. Calculate the expected change in profits if the price of every item in Book 1 is raised by $5. Based on your findings, make a recommendation