Build a linear regression model to predict house value. Interpret the regression results to your customer.

TASK 1: The data for Task 1 is presented on the sheet “Real Estate” of the excel file “Coursework assignment two data.xlsx” You are a business analyst. Your customer, a real estate company, has given you a sample of observations of real estate prices from their database. Your customer wants to know how to determine the price of a house once he or she knows the transaction date, house age, distance to MRT stations, and the number of convenience stores nearby. Question 1. Build a linear regression model to predict house value. Interpret the regression results to your customer. (14 marks) Question 2. One of your colleagues suggests that a linear model may not be good enough and he suggests using a nonlinear model. What would you say? If you do not agree, please explain your logics with relevant references. If you agree, please suggest a decent non-linear model and show evidence. (10 marks) Question 3. Assuming that a linear model will be used for this case. One of your colleagues suggests using a regularised model. Why would she propose using a regularised model? Could you apply such a model and briefly explain how it deals with the potential problem(s)? (9 marks) Question 4. Assuming that a linear model will be used for this case. Another of your colleagues suggests conducting a Principal Component Analysis (PCA). Do you agree? Critically evaluate this suggestion. (7 marks)