The Intersection of Data, Business, and Statistics

Statistical methods are used in numerous occupations as their purpose is to help people identify, study, and solve complex problems. In the business and economic world, these methods enable managers to make informed decisions about uncertain situations. In other words, business statistics is the science of good decision-making. While many computer programs are now available for the collection of data, it takes educated individuals to analyze that data in a meaningful way. This guide introduces the history of statistics as well as some of the basic concepts and ways in which they are applied to business.

History of Statistics and Data

Today, statistics are widely used in government, both physical and social sciences, and virtually all forms of business. Although we now utilize the principles of statistics in fields as diverse as education, agriculture, and medicine, the history of statistics as a mathematical branch isn’t nearly as long as some other branches. In fact, the formal study of statistics dates back only as far as the mid-1600s, when a commoner named John Graunt published the first treatise on statistics entitled Natural and Political Observations on the London Bills of Mortality. This treatise, published in 1662, spelled out some theories about the higher birthrates of males vs. females, child mortality, and the longer lifespan of women that Graunt deduced via his interpretations of data he observed by reviewing a weekly church publication that listed the births and deaths of people in the parish. Graunt’s treatise was received well. Just a month after publication, Charles II recommended him to the Royal Society, into which he was swiftly admitted.

Statistics, then, is the science of collecting, classifying, analyzing, and interpreting numerical facts or data. As Graunt’s initial treatise testified, statistics have borrowed from sociological concepts like population from the outset. Very often, statistics reflects the study of human behavior, and as such it is sometimes excluded from the physical sciences. More often than not, statistics is partnered with probability, that branch of mathematics concerned with the likelihood of a given outcome. While concepts of probability have existed in the form of games of chance for thousands of years, probability as a mathematical notion arose around the same time as statistics. One thought is that the harmonious relationship between statistics and probability arose from 17th- and 18th-century studies of card games and gambling.

In the 1800s, renowned mathematician Pierre-Simon Laplace extended and systematized the field of statistics, after which the field has continually been developed. Statistical reasoning and probability models are used with inductive logic, business, philosophy, sociology, and economics, while computers have greatly enhanced the speed of statistical computation. Therefore, statistics and data also overlap with computer science and information science.

Using Data in Business

In business, statistical data is particularly applicable to the fields of financial analysis, economics, production and operations, and marketing strategy. Data falls into two broad categories: qualitative and quantitative.

Qualitative data, also called categorical variables, cannot by computed. It describes some aspect of a given topic. For instance, take a group of ten different dogs. Four of the dog have brown eyes, three of them have black eyes, and three of them have eyes that are neither black nor brown. The color of the dogs’ eyes is an inherent quality that statisticians would describe as qualitative.

Quantitative data, on the other hand, consists of measures with numerical value. This kind of data can be further divided into discrete (countable) data or continuous data, which is when the data expressed continually. For example, a measure of the number of defective pieces produced during a day’s factory work would be discrete, while the current height of a person is continuous data, since it will change continally.

Statistical data analysis involves four steps:

1. Clearly defining the problem
2. Collecting the data, either through existing sources or obtaining new data by observation
3. Analyzing the data to find out what it tells us
4. Reporting the results with tables, graphs, or percentages

A set of data is a representative model of the reality. Therefore, the sample through which data is collected should be carefully designed so as to reflect reality.

Many universities offer majors in business statistics; a typical course of study includes classes in statistical theory and methods, computer science, information processing, forecasting methods, and data analysis. Business statisticians provide institutions with the knowledge and skills to interpret and implement statistical methods with many applications.

Additional Resources for Statisticians

The World Wide Web Virtual Library: Statistics is your first stop for information about job opportunities, global statistics departments, and research groups. You can also find a list of prominent statistical software vendors with links to individual web sites.

UCLA’s History of Statistics page provides biographies of influential statisticians as well as scanned copies of several important statistical treatises. A handy glossary of statistics terms is maintained by Bob Hall of Texas A&M University. Some introductory notes on statistics were compiled by Jamie DeCoster at the University of Alabama.

The Journal of Business and Economic Statistics publishes research and commentary on such topics as data quality, forecasting, and policy evaluation for use by statisticians, economists, and businessmen. Additionally, this page contains a list of other specific occupational statistics journals.

The American Statistical Association features a career center with the following video entitled “Statistics – Dream Job of the Next Decade”. Similarly, the U.S. Census Bureau produced a video about World Statistics Day, which happened on October 20, 2010.