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Regression Analysis - Statistics and Minitab

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Management of a soft-drink bottling company wishes to develop a method for allocating delivery costs to customers. Although part of total cost clearly relates to travel time within a particular outlet, another variable reflects the time required to unload the cases of soft drink at the delivery point. A sample of 20 customers was selected from routes within a particular sales territory and the delivery time (in minutes) and the number of cases delivered were measured and recorded in the data set. Develop a regression model to help allocate delivery costs by predicting unloading time based on the number of cases delivered.

1) Begin with a brief description of the problem in your own words. Prepare a report using headings that reflect the tasks you are asked to complete in (4). You are expected to follow the report format guidelines document provided in D2L. You should cut-and-paste al Minitab output--tabular and/or graphical--that is relevant to your analysis,from Minitab into your document.

4) Use your Minitab software to generate the numerical and graphical output
used in your analysis. The file containing the problem data, <DELIVERY.MTW>, is available to you from the D2L announcement for this assignment. Complete the following tasks and discuss each, excluding (b) which does not require discussion:
-1-
Computer Project #3
a) Set up a scatter diagram.
b) Use Minitab's least squares method to obtain the regression output. Show the entire tabluar output for this problem here (you may wish to copy and paste pieces of it into other sections of your report for discussion) .
c) State the regression equation and interpret (justify if necessary) the values for b0 and b1 as applicable for this problem.

d) State the coefficient of determination r2 and interpret its meaning for this problem.

e) Predict the delivery time with both confidence and prediction intervals for a customer that is receiving 20 cases of soft drink.

f) Would it be apropriate to use this model to predict delivery time for a customer who is receiving 50 cases of soft drink? Explain.

g) Discus evidence of a linearelationship betwen the model variables using both the F-test and t-test statistics. Discus the t-test for the y-intercept. Asume an α = .05
level of significance for al tests.

h) Perform a residual analysis. Using the standardized residuals, generate a histogram, normal probabilty plot, and residuals vs. fits. Discus each in terms of the apropriate asumptions of linear egresion.

i) Summarize your findings above in determining the adequacy of the fit of the model and your confidence in its abilty to alocate delivery costs to customers.

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