h Use the model youve selected to make a point prediction of coachs salary for

# H use the model youve selected to make a point

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h. Use the model you’ve selected to make a point prediction of coach’s salary for the median(s) of your predictor(s) along with 95% prediction and confidence intervals. The regression equation is: Overall = _________________________________________________________ Predictor Coef SE Coef T P Constant 35.62 13.23 2.69 0.016 Itineraries/Schedule 0.1105 0.1297 0.85 0.407 Shore Excursions 0.24454 0.04336 ____ ______ Food/Dining 0.24736 0.06212 3.98 0.000 S = 1.38775 R-Sq = _____________ R-Sq(adj) = 70.3% Analysis of Variance Source DF SS MS F P Regression __ 92.352 _______ ______ 0.000 Residual Error __ _______ ______ Total 19 _______ Predicted Values for New Observations New Obs Fit SE Fit 95% ____ 95% ____ 1 ____ 0.320 (________, 89.620) (85.922, _______) Values of Predictors for New Observations Shore New Obs Itineraries/Schedule Excursions Food/Dining 1 93.0 84.0 91.0 2. In a 2012 issue, Conde Nast Magazine listed the overall ratings of their 20 highest rated cruise ships along with the ratings on the predictors shown above. a. Complete the regression and ANOVA output for the multiple regression of overall rating vs. these predictors. b. Which predictor should we consider removing from the model and why? c. Compute a regression model with the predictor identified in b. removed. d. Compute separate simple regression models with all 3 predictors, respectively. Does the multiple regression model you computed in c. give any prediction advantage over the best of the simple regression models? e. For the model in c. and the best of the simple regression models, make point predictions for the medians of the predictors along with 95% prediction and confidence intervals. Compare the confidence intervals. What relationship should you expect between the regression models and their confidence intervals? #### You've reached the end of your free preview.

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• Spring '08
• Priya
• Regression Analysis, Prediction interval, NCAA, simple regression models
• • • 