The two Excel based projects will focus on applications of linear equations and linear least squares regression.

All projects must be printed on letter size paper.No electronic copies or handwritten ones will be accepted.All content must be printed - no handwritten mathematics, graphs, labels, etc.All projects must be stapled.

Students can work with a partner and each group can submit one report, make sure both names are on the report.

The data used is from the Mart store in fiscal 2002-2003.

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

1. Identify at least 6 holiday periods or special events that cause spikes in the data. a. In each case, give the week number, date and what holiday or special event it represents.b. Which holiday results in the maximum sales for this department and how much are the sales?

2. Generate three different linear models for this data.Each linear model should be generated from a pair of data points.Do not use an Excel trend line or least squares regression line. a.For each linear model, find the equation of the line.Show your work.Write the equation in slope-intercept form.b. For each linear model, discuss the meaning of the slope and y-intercept.Also provide an analysis as to why you like or dislike that particular model.c. Discuss the rationale behind your model that you believe best predicts future results.

3. Predict and analyze sales for the next four weeks. a. Using your preferred linear model, predict sales for the next four weeks.Show your calculations.b. Using these predicted values, compute the percent rate of increase 2 1 1 ( )/ y y y for the next four weeks.

4.If you were the manager of this department, what recommendations would you make to the person in charge of ordering inventory?

l Mart Dry Goods Sales 2002-2003The data is for weekly sales in the dry goods department at the l*Mart store in fiscal 2002-2003.Peak values, i.e. spikes, usually occur at holiday periods.Week 1 is the first week of February 2002.To show continuity, week 1 of 2003 is represented as week 54 since week 53 represents the end of fiscal 2002 and start of the 2003 fiscal year.Dollar values are adjusted in order to disguise true sales figures, but trends in the data are retained for analysis purposes.

WeekSales in $2615200271560028164002915600301420031144003216400331520034144003513800361500037141003814400391400040156004115000421440043178004415000451520046158004718600481540049155005016800511870052214005320900541880055224005619400572000058181005918000601960061190006219200631800064176006517200661980067196006819600692000070208007122800722300073208007425000753060076240007721200