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BEASTBUY Data Analysis

I need help with the following type of problem:

You work in the shipping and logistics department for Beast Buy, an American mail order company that specializes in pet food for VERY exotic pets. Beast Buy has four warehouses/distribution centers that provide product to each of four different regions in the US; Atlanta services the southeast, Boston services the northeast, Cleveland services the Midwest, and Denver services the west. Your manager has recently asked you to analyze the efficiency of these distribution centers.

4.1 The first issue your boss has asked you to address is whether or not there are differences in distribution cost between each of the four warehouses. Use the 0.05 level of significance to:
a) Perform a one-way ANOVA to look for differences in distribution costs between warehouses.
b) If the results in (a) indicate that it is appropriate, use the Tukey-Kramer procedure to determine which distribution centers differ in mean distribution costs.
4.2 In addition to looking at differences between distribution centers, your manager also wants to know the relationship between the number of orders routed through each center and the distribution cost. Thus, the number of orders is your independent variable and the cost is your dependent variable.
a)Construct a scatter plot of the two variables.
b)Estimate a simple linear regression between these two variables.
c)Interpret the meaning of b0 and b1.
Combine 4.1 and 4.2 into a single multiple regression model using dummy variables. To put the data in an Excel-friendly format, you will first need to create dummy variables for each of the different processing centers. a) Estimate a multiple regression model, again using cost as the dependent variable, however for your independent variables you will want to use orders AND your set of dummy variables (see technical note below).

I am not asking you to complete my assignment, I just need to see the formula and how it is worked to ensure I have computed my assignment correctly.

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Solution Summary

The solution provides step by step method for the calculation of ANOVA and multiple regression analysis. Formula for the calculation and Interpretations of the results are also included.

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