At a
95.00%
confidence level, is insulation the best predictor of heating cost? Is the age of the furnace the best predictor of heating cost? Or is a combination of the two the best predictor of heating cost?
(check figure: Significance
F=.0189
)
\table[[Home,Insulation (inch) Fumace Age (year) Heating Cost ($)],[1,3,6,250],[2,4,10,360],[3,7,3,165],[4,6,9,43],[5,5,6,92],[6,5,5,200],[7,6,7,355],[8,10,10,290],[9,9,11,230],[10,2,6,120],[11,12,4,73],[12,5,1,205],[13,5,15,400],[14,4,7,320],[15,8,6,72],[16,5,8,272],[17,7,3,94],[18,8,11,190],[19,9,8,235],[20,7,5,139]]
What is the R-Squared for Insulation predicting Heating Costs?
(hint: you do not have to create a scatterplot graph - simply just use the RSQ function/formula)
What is the R-Squared for Furnace Age predicting Heating Costs?
(hint: you do not have to create a scatterplot graph - simply just use the RSQ function/formula)
What is the
R
-Squared for Both Insulation and Furnace Age predicting Heating Costs?
(hint: this is the R-Squared calculated when the regression test results are displayed)
What is the hypothesis of the study?
What will be the area of rejection in the study using the p critical value?
Insulation:
Furnace Age:
?
Combination:
?
Create the statement of rejection and not-rejection based upon the p value and p critical value
Insulation:
Furnace Age:
Combination:
What is the confidence interval estimate for the SLOPE.P
Insulation:
Furnace Age:
What will be the conclusion of this study?