Please note that the data to use is pasted below after the question part

For each of the scenarios below, use Excel to access the data (see the instructions of this assignment for the link to download the data in the file MSl'l'71007HW9Data.xls), construct the appropriate scatterplot(s), and produce the regression output relating y to X('s). Provide the values of the regression coefficiems from each regression output, as well as predictions, and interpret your results (Round all numeric answers to two decimal places.) (a) Estimating Residential Real Estate Values: The worksheet name is REALEST. Build a regression model to predict VALUE from SIZE. The value of each structure is measured in U.S. dollars and the size is measured in square feet. Therefore, the value of each residence is estimated to increase by I: dollars for every square foot increase in size. The predicted value of a residence with 1,500 square feet is E dollars. (b) Forecasting Housing Starts: The worksheet name is HSTARTS. Build a regression model to predict the average number of housing starts (STARTS) from mortgage rates (RATES). You can ignore the year variable for the purpose of this model. ,-:.:ms Therefore, \\:I is the average number of housing stars that our model would predict when mortgage rates are 0%, however this may not be a valid prediction due to lack of data in that region. The predicted average number of housing starts when the mortgage rate is 8.00% is S .