the questions below please ASAP
Evans_2013_Ch7_OCR.pdf
Evans_2013_Ch8_OCR.pdf
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.
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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:
http://www.youtube.com/watch?v=H07l1zgM-cw
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.