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:

You decide to create Model 1 which is a "full model" including all of the predictor variables as a starting point Based on these model results match the number from the output that would best allow you to answereach of the following questions (responses have been rounded to three digits after the decimal): Note "Model 1" or the full model should include these predictors: (TEMP, HDD

, CDD, SIZE, METER, PUMP1, PUMP2, RIDERTOT)

What percentage of the variability in electric bill cost can be explained by the variables that you have included in the model?

Choose the correct answer from below....

0.56

1119

.0001 (less than)

-48.297

.123

.223

.529

-42.273

Could this be a useful model for predicting electric bill costs (meaning overall model is statistically significant)?

Choose the correct answer from below....

0.56

1119

.0001 (less than)

-48.297

.123

.223

.529

-42.273

Do the number of cooling degree says appear to be significant at the .05 level?

Choose the correct answer from below....

0.56

1119

.0001 (less than)

-48.297

.123

.223

.529

-42.273

What is the expected change in the bill given there is a new second heat pump?

Choose the correct answer from below....

0.56

1119

.0001 (less than)

-48.297

.123

.223

.529

-42.273