Lecture Data ans statistics Applications in Business and Economics

Marketing
Electronic scanners at retail checkout counters collect data for a variety of marketing research
applications. For example, data suppliers such as ACNielsen and Information Resources,
Inc., purchase point-of-sale scanner data from grocery stores, process the data, and
then sell statistical summaries of the data to manufacturers. Manufacturers spend hundreds
of thousands of dollars per product category to obtain this type of scanner data. Manufacturers
also purchase data and statistical summaries on promotional activities such as special
pricing and the use of in-store displays. Brand managers can review the scanner
statistics and the promotional activity statistics to gain a better understanding of the relationship
between promotional activities and sales. Such analyses often prove helpful in
establishing future marketing strategies for the various products.
Production
Today’s emphasis on quality makes quality control an important application of statistics
in production. A variety of statistical quality control charts are used to monitor the output
of a production process. In particular, an x-bar chart can be used to monitor the average
output. Suppose, for example, that a machine fills containers with 12 ounces of a soft drink.
Periodically, a production worker selects a sample of containers and computes the average
number of ounces in the sample. This average, or x-bar value, is plotted on an x-bar chart. A
plotted value above the chart’s upper control limit indicates overfilling, and a plotted value
below the chart’s lower control limit indicates underfilling. The process is termed “in control”
and allowed to continue as long as the plotted x-bar values fall between the chart’s upper
and lower control limits. Properly interpreted, an x-bar chart can help determine when
adjustments are necessary to correct a production process.
Economics
Economists frequently provide forecasts about the future of the economy or some aspect of it.
They use a variety of statistical information in making such forecasts. For instance, in forecasting
inflation rates, economists use statistical information on such indicators as the Producer
Price Index, the unemployment rate, and manufacturing capacity utilization. Often these statistical
indicators are entered into computerized forecasting models that predict inflation rates.
Applications of statistics such as those described in this section are an integral part of
this text. Such examples provide an overview of the breadth of statistical applications. To
supplement these examples, practitioners in the fields of business and economics provided
chapter-opening Statistics in Practice articles that introduce the material covered in each
chapter. The Statistics in Practice applications show the importance of statistics in a wide
variety of business and economic situations.