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:

Before building your model, you decided to compute correlations between the continuous variables (excluding NUMID and YEAR). Based on these correlations, which variable appears to be the best potential predictors of the amount of the electric bill?

Select one:

a. RIDERTOT b. HDD c. BILLAMT d. TEMP