Question: Chapter 16 Case Study, pages 668-669, only the part starting with "Suppose Foot Locker ..." and ending at the end of the data on location and sex. Answer the following questions: a) is there a relationship between geographic location and sex in terms of numbers of suggestions? And b) if they are related, what does this relationship mean to the company?

Hint: Use the chi-square test of independence formula on page 658 to compute by hand or go to http://www.changbioscience.com/stat/chi2.html and copy and paste the data to the top blank box (note: only data, not the labels of the rows or columns); right below this box, choose "test of independence"’ and then click "go".

The overall objective of this chapter is to provide an understanding of two-statistical techniques used to analyze categorical data, thereby enabling you to:

 Use the chi-square goodness-of-fit test to analyzer probabilities of multinomial distribution trials along a single dimension and test a population proportion.

 Use the chi-square test of independenced to perform contingency analysis

CASE STUDY: Ch 16

Foot Locker in the Shoe Mix

Foot Locker, Inc., is the world's number one retailer of athletic footwear and apparel. The company has approximately 3,800 retail stores in 21 countries across North America, Europe, and Australia under various brand names. Foot Locker estimates that it controls about 18% of the U.S. $15 billion athletic footwear market. The company intends to increase its share of the worldwide market by adding additional stores and by growing its Internet and catalog business.

In recent years, Foot Locker officials have been rethinking the company's retail mix. Determining the shoe mix that will maximize profits is an important decision for Foot Locker. By the year 2002, in an effort to stock more lower-priced footwear, the company had reduced its inventory of sneakers priced at $120 or more by 50%.

Discussion:

Suppose Foot Locker strongly encourages its employees to make formal suggestions to improve the store, the product, and the working environment. Suppose a quality auditor keeps records of the suggestions, the persons who submitted them, and the geographic region from which they come. A possible breakdown of the number of suggestions over a 3-year period by employee sex and geographic location follows. Is there any relationship between the sex of the employee and the geographic location in terms of number of suggestions? If there are related, what does this relationship mean to the company? What business implications might be there for such an analysis?

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