Generate supporting Excel spreadsheet(s) and graphs (use scatter plots) to answer the following questions for the Dry Goods 2002-2003 data:

1. Modeling the data linearly - a. Generate a linear model for this data by choosing two points.b. Generate a least squares linear regression model for this data.c. How good is this regression model?d. What is the marginal revenue for this department using the linear model with two data points and the regression model?Note that marginal revenue is the same as the first derivative of the revenue (sales) function. e. Compare the two models.Which do you feel is better?

2. Modeling the data quadratically - a. Generate a quadratic model for this data.b. What is the marginal revenue for this department using this model? c. Calculate the model generated relative max/min value.Show backup analytical work.d. Compare actual and model generated relative max/min value.

3. Comparing models a. Which model do you feel best predicts future trends?Explain your rationale.b. Based on the model selected, what type of seasonal adjustments, if any, would be required to meet customer needs?

4.Identify holiday periods or special events that cause spikes in the original data.WalMart weeks start the beginning of February.So, for example, Walmart week 30 in the 2002 is actually week 34 (30 + 4) in the calendar year 2002 which equates to the end of August 2002.To make the weeks continuous, week 53 is actually WalMart week 1 in 2003and this equates to week 5 (53 - 52 +4) or the first week in February 2003.Week 72 is week 24 (72 - 52 + 4) in the year 2003 or mid June 2003

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