Business Statistics Center by Irwin/McGraw-Hill

Practical Data Analysis: Case Studies in Business Statistics

Sample Case

Case 71: The Bay Area Athletic Club

The Bay Area Athletic Club, located in San Francisco, California, offers the full range of athletic activities and equipment: indoor and outdoor pool and tennis, a weight room with free weights and Cybex machines, basketball, aerobics classes, yoga classes, an outdoor running track, and a senior center. By popular demand, yoga and aerobics classes are only offered during peak hours. Members can purchase two types of memberships. A Gold membership, costing $100 per month per family, allows the user full access to all activities and facilities. Silver memberships allow access to all facilities but not the aerobic and yoga classes; it costs $90 per family per month. Individual memberships are half the monthly family rates.

Even though the club has the latest equipment and fully trained staff, it has a problem. Management would like to increase club revenues, but dares not increase monthly rates. An alternative is to expand its membership base. However, current members are already complaining about insufficient access to parking, some even threatening to cancel their memberships. The club is surrounded on all sides by commercial property and cannot solve its parking problem by extending its existing lots to adjacent property. Management at Bay Area has come up with a solution. If new members can be encouraged to use the facilities during off-peak hours, revenues can be increased without compounding an already serious parking problem.

But what sort of individual can attend the club during off-peak hours? This is important to know since Bay Area has limited funds for advertising and would like to target its marketing efforts to potential nonpeak users.

When a user checks into the club, the bar code on his or her membership card is scanned and the time of entry is recorded. Management has compiled a data set by pulling every 20th record from the membership filing cabinets and matching the scanned entry data. The resulting data set, containing 94 observations, is described below and available in the file named PEAK. Use the data to determine a profile of the club's nonpeak members and provide appropriate recommendations to Bay Area Club management.

These data and scenario are real, although the name of the health club and its location have been changed.

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