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Management of a soft-drink bottling company has the business objective of developing a method for allocating delivery costs to customers. Although one cost clearly relates to travel time within a particular route, another variable cost reflects the time required to unload the cases of soft drink at the delivery point. To begin, management decided to develop a regression model to predict delivery time based on the number of cases delivered. A sample of 20 deliveries within a territory was selected. The delivery times and the number of cases delivered were organized in the datafile delivery.xls
1. Use least square method to estimate the regression line of these dataset.
2. Predict the mean delivery time for 150 cases of soft drink.
3. Should you use the model in a) to predict the delivery time for a customer who is receiving 500 cases of soft drink? Why or why not?
4. Determine the coefficient of determination and interpret on it.
5. Perform residuals analysis to verify the model assumptions
6. At 5% significant level, is there any evidence of a linear relationship between delivery tie and the number of cases delivered?
7. Construct a 95% confidence interval estimate of the mean delivery time for 150 cases of soft drink and a 95% prediction interval of the delivery time for a single delivery of 150 cases of soft drink.
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