How do we define the word statistics? We encounter it frequently in our everyday language. It really has two meanings. In the more common usage, statistics refers to numerical information. Examples include the average starting salary of college graduates, the number of deaths due to alcoholism last year, the change in the Dow Jones Industrial Average from yesterday to today, and the number of home runs hit by the Chicago Cubs during the 2005 season. In these examples statistics are a value or a percentage. Other examples include:

• The typical automobile in the United States travels 11,099 miles per year, the typical bus 9,353 miles per year, and the typical truck 13,942 miles per year. In Canada the corresponding information is 10,371 miles for automobiles, 19,823 miles for buses, and 7,001 miles for trucks.

• The mean time waiting for technical support is 17 minutes.

• The mean length of the business cycle since 1945 is 61 months.

The above are all examples of statisticsThe science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions.. A collection of numerical information is called statisticsThe science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions. (plural).

We often present statistical information in a graphical form. A graph is often useful for capturing reader attention and to portray a large amount of information. For example, Chart 1–1 shows Frito-Lay volume and market share for the major snack and potato chip categories in supermarkets in the United States. It requires only a quick glance to discover there were nearly 800 million pounds of potato chips sold and that Frito-Lay sold 64 percent of that total. Also note that Frito-Lay has 82 percent of the corn chip market.

The subject of statistics, as we will explore it in this text, has a much broader meaning than just collecting and publishing numerical information. We define statistics as:

As the definition suggests, the first step in investigating a problem is to collect relevant data. They must be organized in some way and perhaps presented in a chart, such as Chart 1–1. Only after the data have been organized are we then able to analyze and interpret them. Here are some examples of the need for data collection.

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• Research analysts for Merrill Lynch evaluate many facets of a particular stock before making a “buy” or “sell” recommendation. They collect the past sales data of the company and estimate future earnings. Other factors, such as the projected worldwide demand for the company’s products, the strength of the competition, and the effect of the new union–management contract, are also considered before making a recommendation.

• The marketing department at Colgate-Palmolive Co., a manufacturer of soap products, has the responsibility of making recommendations regarding the potential profitability of a newly developed group of face soaps having fruit smells, such as grape, orange, and pineapple. Before making a final decision, the marketers will test it in several markets. That is, they may advertise and sell it in Topeka, Kansas, and Tampa, Florida. On the basis of test marketing in these two regions, Colgate-Palmolive will make a decision whether to market the soaps in the entire country.

• The United States government is concerned with the present condition of our economy and with predicting future economic trends. The government conducts a large number of surveys to determine consumer confidence and the outlook of managers regarding sales and production for the next 12 months. Indexes, such as the Consumer Price Index, are constructed each month to assess inflation. Information on department store sales, housing starts, money turnover, and industrial production are just a few of the hundreds of items used to form the basis of the projections. These projections are used by banks to decide their prime lending rate and by the Federal Reserve Board to decide the level of control to place on the money supply.

• Managers must make decisions about the quality of their product or service. For example, customers call software companies for technical advice when they are not able to resolve an issue regarding the software. One measure of the quality of customer service is the time a customer must wait for a technical consultant to answer the call. A software company might set a target of one minute as the typical response time. The company would then collect and analyze data on the response time. Does the typical response time differ by day of the week or time of day? If the response times are increasing, managers might decide to increase the number of technical consultants at particular times of the day or week.

Chapter Exercises  12