Model 1: Simple Linear Regression Model

Using the data analysis that appears below, assess Visits as a predictor of Post-Promo Service Spend. Answer the questions below.

Dependent Variable: Y = Post-Promo Service Spend

Independent Variables: X = Visits

1. Describe the relationship that appears to exist between customer service-spending during the three months after a manufacturer incentive offer and the number of customer visits to a retailer store in the past 12 months. Defend your answer.
2. How strong is the correlation between customer service-spending during the three months after a manufacturer incentive offer and the number of customer visits to a retailer store in the past 12 months? Be sure to defend your answer.
3. What is the sample linear regression equation that uses number of customer visits to a retailer store in the past 12 months to predict customer service-spending during the three months after a manufacturer incentive offer? Interpret the coefficients in the model.
4. How much of the variation in customer service-spending during the three months after a manufacturer incentive offer is explained for by the variation in number of customer visits to a retailer store in the past 12 months?
5. Is number of customer visits to a retailers store in the past 12 months a useful predictor of customer service-spending during the three months after a manufacturer incentive offer? Be sure to defend your answer.
6. Is number of customer visits to a retailers store in the past 12 months a significant predictor of customer service-spending during the three months after a manufacturer incentive offer? Be sure to defend your answer.
7. Predict customer service-spending during the three months after a manufacturer incentive offer for a customer who is known to have visited the retailers store 15 times in the last 12 months.
8. Any concerns about the validity of a regression analysis? (any violations of regression assumptions?) Be sure to defend your answer.