3) You are the marketing director for a minor league baseball team, and (not unlike a certain major league baseball team in this city) you are interested in ways to increase attendance. You think that attendance is likely driven by several factors, including how competitive the team is, the weather, and certain price promotions which are offered periodically throughout the season (e.g., 'Buck Night', where all parking, hot dogs and soft drinks are only $1). Based on data from several prior seasons, you estimate the following regression model for attendance: attend = 1000 + 10,000 win% + 1500 sun + 1200 sun*promo where, attend = attendance in number or patrons win% = team's winning percentage (a measure of how competitive they are) sun = 1 if the weather is sunny, 0 else promo = 1 if the game offered a price promotion, 0 else. a) Draw a graph of the relationship between attendance and the team's winning percentage, for the case when there is a price promotion on a sunny night. Also, graph the relationship when the weather is sunny but there is no price promotion. Be sure to clearly label the graph axes, the numerical values of slopes and intercepts, along with which lines you are graphing. b) Suppose you are planning on offering a price promotion, although the forecast calls for periodic rain showers through the evening. According to the above model, does it make any sense to offer this promotion? Why or why not