The questions in this case are based on the case Have Text, Will Travel: Can Airbnb Use Review Text Data to Optimize Profits? 3. Use the data in the two excel data files named M-0897-Miami and M-0897-Paris available on eLearning. The names of data columns are explained in case exhibit 2. Question 1: Airbnb wants to help the hosts maximize their revenues because in doing so, it can improve its own revenues. There is a lot of data available related to each property that is available to Airbnb managers for the two locations of Miami and Paris (see the two excel data files). While the available data-sets has information about the price at each property, there is no information about the number of bookings, and so there is no information about the actual revenues earned by a property (since, revenue = price X number of bookings). Which variable(s) can be used from the data-set in place of the actual number of bookings to get an estimate of the revenue earned by a property? Explain in 1-2 sentences. Question 2: Suppose the Airbnb managers decide to use a regression model to identify the variables associated with estimated revenue (from question 1). What regression model would you suggest? Please execute the regression analysis as per the model you suggest and identify which variables may play a role in driving revenues? Since there is data for two cities (Paris and Miami), discuss whether the variables that are associated with revenues differ with location. Please add the screenshots of your regression analysis to support your discussion. Please limit your response to 1.5 pages including the screenshots.