In early days, before it was a well-known company, FedEx undertook a campaign to promote the use of its Courier packages (now called FedEx Paks). Each customer was targeted for sales promotion. Sales representatives visited customers and worked to increase their use of the packages. Some of the customers were already aware of the Courier packaging before the campaign began, but it was unknown to others. The ?le fedex.csv contains the records of 125 customers. For each customer, the observed value of three variables were recorded. The response variable is the number of Courier package shipments per month by the customer (Mailings). One predictor is the number of contact hours the customer had with the sale representative (HoursOfEffort). A second predictor is an indicator of whether the customer was aware of FedEx and its products prior to the start of the campaign (Aware).

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1. In early days, before it was a well-known company, FedEx undertook a campaign to promote the use of its Courier packages (now called FedEx Paks). Each customer was targeted for sales promotion. Sales representatives visited customers and worked to increase their use of the packages. Some of the customers were already aware of the Courier packaging before the campaign began, but it was unknown to others. The file fedex. cav contains the records of 125 customers. For each customer, the observed value of three variables were recorded. The response variable is the number of Courier package shipments per month by the customer (Mailings). One predictor is the number of contact hours the customer had with the sale representative (HoursOfEffort). A second predictor is an indicator of whether the customer was aware of FedEx and its products prior to the start of the campaign (Aware). (a) Fit a regression model with Mailings as response and HoursOfEffort, Aware and the interaction between them as predictors in R. (b) Interpret the LS estimate of the regression coefficient for the interaction term. (c) Under the model in part (a), controlling the value of HoursOfEffort, does Aware ex- plain a significant extra amount of variation in the number of shipments per month by customers? Specify the relevant null and alternative hypotheses, and test at significance level 0.05. (d) Fit two simple regression models with Mailings as response and HoursOfEffort as predictor for the group of customers with Aware = YES and the group with Aware = NO, respectively. How are the estimated regression coefficients in these two models related to the estimated coefficients in the model of part (a). (e) Report the 95% prediction interval of the actual number of shipments per month by a customer who was aware of the service before the campaign and have talked with a sales representative for 4 hours