Statistics concepts and applications

Statistics in the Hardware Store

Statistics can be used in a variety of ways in a hardware store. Because it is a retail business, the main reason for the use of statistics for decision making that will help the business financially prosper. They are used to determine what products customers want and need and how much of each item to keep in stock. Statistics are used answer important questions like when customers are going to purchase and how much they are going to spend (Boatwright, Borle, & Kadane, 2003). They are also are used in pricing models for the merchandise, in the marketing strategies of the store (for example, determining who the target customer is), and almost every other aspect of the store's operation.

A hardware store has many uses for descriptive statistics. The owners and managers need to know what the data look like in order to make informed decisions. One example would be products to have in stock. If the store determines the average products that sell the most, they know which items should have the most stock (and have their stock replaced). For example, if an average (arithmetic mean) of one hammer is sold per month, but, on average (arithmetic mean), ten saws are sold per month, when the store goes to order their products, they would know to stock more saws than hammers (as the stock of saws would been depleted more than the stock of hammers).

The hardware store also has several uses for interferential statistics. One example would be a customer satisfaction survey. Because the hardware store managers feel that they need feedback from their customers, they choose to have the cashiers ask a few customers about their shopping experience. A few customers are asked at the register how satisfied they were on a scale of one (very dissatisfied) to five (very satisfied), and the management generalized the answers to the entire shopping population. Because 95% of customers said they were very satisfied, the store management assumed that they were doing a good job and meeting the needs of their customers (and hoped to maintain profits). The store management can generalize the results because it is assuming that the (sample of) people who were chosen to answer the question represent the larger population of shoppers (since not all shoppers were asked). The management has no reason to think that the shoppers who were asked were somehow different from everyone else.

All four levels of data measurement are used in the hardware store. Nominal scales are used most often to label the groups of products. Items are arranged by category (for example, lawn and garden, paint, tools, and plumbing). Then, items were arranged by subcategories (for example, in "paint" there are rollers, ladders, and wallpaper accessories). Ordinal scales are used in the customer satisfaction survey (mentioned above) and in product ratings. Some of the product tags had ratings on them that say "good," "better," and "best" to help customers determine the best product out of the categorical group (for example, the best electric screwdriver). These ratings just ordered the products without saying much about the differences between them. The interval scale was used most noticeably in pricing. Each item in the store has a monetary price tag and the difference between two items is measurable. For example, painting buckets ranged from $49.50 to $83.88, and it is easy to tell the difference between the least expensive item and the most expensive item ($34.38). Ratio scales are used, for example, when looking at sales or rental timing. Some items are on sale for two days while others are on sale for four (that is, they are on sale for twice the amount of time). The same is true for rental equipment. A customer can rent a steam cleaner for one day or for twice as long (for an increase in price that is not a ratio measurement - about 80% ($49.99 to $89.99)).