Please download the attached excel file that contains two sheets, 2000 housing data points (2016) for training/Assignment #2 (Linear Regression) and another sheet containing an additional 2000 housing data points (2017) for test purposes. As discussed in class, there is NO overlap between the two sets of data.

In this assignment:

• First, start with the "Training" sheet and pick 10 (and only 10) descriptive features (variables or columns) to include in the regression analysis by:

1. Considering the quality of the data in the column (pick the ones with highest quality)
2. Considering the correlation between the feature (column) and the target variable which is the last column or price column (pick the ones with the highest correlation)

• Second, perform the Regression in excel using the built-in Data Analysis tool. You should select to output the results into a new sheet.
• Third, use the multiple linear regression model you built in the previous step to perform prediction on the new 2000 data points provided to you in the "Prediction" sheet. You are provided with empty template in the Prediction sheet. Fill in the YELLOW part related to model and then form the right formula for the model to perform [prediction for every data points in that sheet. You need to fill in the GREEN part related to Predicted Price and Residual/Error. Finally visualize your prediction errors using a graph/chart and add it to the GRAY part. Remember you should only use the same 10 features that you selected in step number 1 and in the "Training" sheet. Remove the other columns and only keep those you selected in the exact same order!

If you have any questions regarding this assignment, please feel free to post it on moodle (our course discussion forum).

Submission: You only need to submit your completed excel file (with three sheets) for this assignment. Please embed all the formula, computations, and explanations (if needed) into the body of the excel sheets. Rename your final excel file to FirstName-LastName.xlsx and submit.

HousingPricePrediction.xlsx 31 August 2021, 9:01 PM