Buckeye Creek Amusement Park is open from the beginning of May to the end of October. Buckeye Creek relies heavily on the sale of season passes. The sale of season passes brings in significant revenue prior to the park opening each season, and season pass holders contribute a substantial portion of the food, beverage, and novelty sales in the park. Greg Ross, director of marketing at Buckeye Creek, has been asked to develop a targeted marketing campaign to increase season pass sales. 

Greg has data for last season that show the number of season pass holders for each zip code within 50 miles of Buckeye Creek. He has also obtained the total population of each zip code from the U.S. Census bureau website. Greg thinks it may be possible to use regression analysis to predict the number of season pass holders in a zip code given the total population of a zip code. If this is possible, he could then conduct a direct mail campaign that would target zip codes that have fewer than the expected number of season pass holders.

Managerial Report

1. Compute descriptive statistics and construct a scatter diagram for the data. Discuss your findings.

2. Using simple linear regression, develop an estimated regression equation that could be used to predict the number of season pass holders in a zip code given the total population of the zip code.

3. Test for a significant relationship at the .05 level of significance.

4. Did the estimated regression equation provide a good fit?

5. Use residual analysis to determine whether the assumed regression model is appropriate.

6. Discuss if/how the estimated regression equation should be used to guide the marketing campaign.

7. What other data might be useful to predict the number of season pass holders in a zip code?