The data set Housing Prices.xls contains data on 45 residential properties by a real estate company. The four variables included in the data set are: Price: Selling price of the property ($1,000) Beds: Number of bedrooms in the house Baths: Number of bathrooms in the house Square Feet: Size of the house in square feet Perform a comprehensive analysis to understand what the data tells you about the impact of number of bedrooms, number of bathrooms and the size of the house in terms of square feet on the price of the property. Make sure your analysis provides answers to the questions listed below: 1. Obtain the summary statistics for the variables and comment on them. 2. Comment on the distributions of data for the variables? Are they symmetrical? Skewed? 3. Obtain the correlations between variables and comment on them? 4. Perform a multiple linear regression analysis with selling price as the response variable and number of square feet, number of bed rooms and number of bath rooms as predictor variables. 5. State the regression equation and interpret the regression coefficients. 6. Comment on the goodness of fit of the regression equation for the data. 7. Explain how you will