You are a real estate broker and your clients always ask about utility costs when they are considering a new home for purchase. You decide to use your analytical skills to build a model that will enable you to predict the amount of the electric bill for a particular location based on a number of different factors. You have collected data and summarized it in a spreadsheet. In addition to the amount of the monthly electric bill, you have information on temperature, the number of days when the heat or air conditioner might need to run, whether or not a new meter or heat pump has been installed, and total energy consumption.

Dataset:

https://docs.google.com/spreadsheets/d/1vanPCoD3Vo1DNAbzBtjR48IdTjhUOaQc/edit?usp=sharing&ouid=110026528864652775525&rtpof=true&sd=true

Question

After several iterations, you arrive at Model which includes the predictors: TEMP, SIZE, METER, PUMP1, PUMP2. Perform a residual analysis for the model. Look at the residual vs. predicted plot.

Which of the following best describes the plot? (Select one:)

a. There appears to be a potential issue with non-constant variance..

b. There is definitely a non-linear pattern.

c. There are definitely no issues with non-constant variance.