# Solve problem and applications: ch7- prob 12, and ch 8- prob 4 at the

Solve Problem and Applications: ch7- prob 12, and ch 8- prob 4 at the end of chapters 7 and 8 in your textbook.

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Please be sure your work is organized, legible, and your responses are substantive. You need to submit all details of your work including excel sheets used to arrive to the solution. It is not enough to attach your excel sheet. You MUST provide interpretation of results and describe conclusions.

7-12: Develop a multiple regression model with categorical variables that incorporate seasonality for forecasting sales using the last three years of data in the Excel file New Car Sales.

Tips for problem 7-12: This is a multiple regression problem based on monthly data. You will need to create dummy variables for the months to represent seasonality in the model.

Here is a video about the concept:

Here is part of what want to do:
Year Month Units t Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

1 Jan 39,810 1 0 0 0 0 0 0 0 0 0 0 0

1 Feb 40,081 2 1 0 0 0 0 0 0 0 0 0 0

1 Mar 47,440 3 0 1 0 0 0 0 0 0 0 0 0

1 Apr 47,297 4 0 0 1 0 0 0 0 0 0 0 0

1 May 49,211 5 0 0 0 1 0 0 0 0 0 0 0

You will fill all entries for three years, then run regression in excl.

8-4: If 30 samples of 100 items are tested for nonconformity, and 95 of the 3,000 items are defective, find the upper and lower control limits for a p -chart.