La Cabaña, a popular motel chain in the southwest, is interestedin developing a regression model that can predict the occupancyrate % of its motels. Currently, the company is interested in usingtwo explanatory variables to predict occupancy. They want to usethe amount of advertising in $ used by each motel and if theparticular location a franchised location. Some regressioninformation is presented below:
Summary measures
Multiple R 0.5358
R-Square 0.2871
Adj R-Square 0.2223
StErr of Estimate 7.582
Regression coefficients
Coefficient Std Err t-value p-value
Constant 43.118 11.4263 3.7735 0.0010
Advertising 0.0013 0.0006 2.4119 0.0247
Franchise 3.038 3.1759 0.9567 0.3491
If we write the linear regression model asf$hat{Y}=a+bX_{1}+cX_{2}f$ , where is Advertising, and isFranchise, then from the above information, we can infer that a is_____________, b is _________________, and c is____________________. (Please keep three decimal points.)
The coefficient of determination is 0.2871; this represents__________________ percentage of the variation in the occupancy canbe explained by this regression equation. (Please keep two decimalpoints.)
From the p-values, we may conclude that at 5% confidence level, allthe coefficients are statistically ______________________ afterrefining the regressors. (Please only fill in \"significant\" or\"insignificant\".)
