model. The results should improve with better R2 values. Discuss what outliers were removed and why. Generate supporting Excel graphs (use scatter plots) to answer the following questions for the Dry Goods 2002-2003 data: 1. Identify spikes (outliers) in the data where extreme sales values occur and correlate these spikes with actual calendar dates in 2002 or 2003 and with events that may occur during these periods. 2. 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? Output and discuss the R2 value. d. What are the marginal sales (derivative, i.e. rate of change) for this department using the linear model with two data points and the regression model? e. Compare the two models. Which do you feel is better? f. Remove appropriate outliers as you deem necessary and rerun the linear regression model. What is the marginal sales and discuss improvements. 3. Modeling the data quadratically - a. Generate a quadratic model for this data. Also output and discuss the R2 value. b. What are the marginal sales 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