Regression Analysis

Please review the Case Study 2 in the textbook: Modeling the Sale Prices of Residential Properties in Four Neighbourhoods. I uploaded the data into MyCourse. Please briefly describe the purpose of this case study - you need to describe the data set and the relevant variables. Then, list all the models used in this case study and describe the main feature(s) of each model. For example, one of the main features of the first model is that, it assumes there is no interaction between appraised land value and appraised improvement values. Please do not just copy the words in the textbooks. Your description should be much shorter! Then, write a SAS program to produce the output included in the textbook. Your SAS program should be well- organized with comments. Please note, the sample SAS programs I gave you will produce some unneeded numbers or charts. Please delete some options so that the unneeded numbers or charts will not appear. With the SAS output, please make a table for some summary statistics of the models analyzed. Your summary statistics should include MSE, R-square, Adjusted R-square, s - the estimate of the standard deviation of the response variable y, and the degrees of freedom for the MSE for all models. With this information, you can compare the models used in the case study. Please do the F-tests for model comparisons by yourself. Report the F-statistics and the corresponding P-value. Please state how you compute the p-values. Finally, you will pick a best model. Please briefly state why you select the model.