The data are from a small moving company that moves people from urban apartment buildings to other urban apartment building in the same or different cities. The company needs assistance in predicting the labor hours for jobs so they can provide more accurate price quotes. Run two separate regressions using the data in the sections of the spreadsheet titled Regression Model 1 and Regression Model 2. Use a 95% confidence level.
Fill in all the blanks below. Do not round any numbers except for when entering them in the blanks for this quiz, round these numbers to exactly 2 decimal places even if the number has only one or no decimal places. Use commas to separate thousands (e. g., 1225 should be entered as 1,225.00).
Regression Model 1
R Square expressed as a percentage rounded and carried out to two decimal places is % and Adjusted R Square expressed as a percentage rounded and carried out to two decimal places is %. Refer to the spreadsheet embedded in your Module 14 Regression document I provided you to see the calculation and format for answering this next question. The gap between R Square and Adjusted R Square expressed as a percentage rounded and carried out to two decimal places is 0.%.
The overall regression model (was / was not) significant.
Using square footage of 1,500 and mileage of 92, the model estimates that hours of labor would be required, with a margin of error of hours.
Regression Model 2
R Square expressed as a percentage rounded and carried out to two decimal places is % and Adjusted R Square expressed as a percentage rounded and carried out to two decimal places is %. Refer to the spreadsheet embedded in your Module 14 Regression document I provided you to see the calculation and format for answering this next question. The gap between R Square and Adjusted R Square expressed as a percentage rounded and carried out to two decimal places is 0.%.
The overall regression model (was / was not) significant.
Using square footage of 1,500, mileage of 92, and floors of 71, the model estimates that hours of labor would be required, with a margin of error of hours.
Model Selection
Because the R Square is (higher / lower) in regression model 1 than in regression model 2 and the gap between R Square and Adjusted R Square is (smaller / larger) in regression model 1 than in regression model 2 and the margin of error of the estimated labor hours is (smaller / larger) in regression model 1 than in regression model 2 , we would characterize regression model (1 or 2) as being the better model.