# What is Statistics? How Is It Applied to the Health Sciences?

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## Chapter: Biostatistics for the Health Sciences: What is Statistics? How Is It Applied to the Health Sciences?

All of us are familiar with statistics in everyday life.

What is Statistics? How Is It Applied to the Health Sciences?

All of us are familiar with statistics in everyday life. Very often, we read about sports statistics; for example, predictions of which country is favored to win the World Cup in soccer, baseball batting averages, standings of professional football teams, and tables of golf scores.

Other examples of statistics are the data collected by forms from the decennial U.S. census, which attempts to enumerate every U.S. resident. The U.S. Bureau of the Census publishes reports on the demographic characteristics of the U.S. population. Such reports describe the overall population in terms of gender, age, and income distributions; state and local reports are also available, as well as other levels of aggregation and disaggregation. One of the interesting types of census data that often appears in newspaper articles is regional economic status classified according to standardized metropolitan areas. Finally, census data are instrumental in determining rates for mortality and diseases in geographic areas of the United States.

A widely recognized use of statistics is for public opinion polls that predict the outcome of elections of government officials. For example, a local newspaper article reports that two candidates are in a dead heat with one garnering 45% of the votes, the other garnering 47% percent, and the remaining 8% of voters undecided. The article also qualifies these results by reporting a margin of error of ±4%; the margin of error is an expression of the statistical uncertainty associated with the sample. You will understand the meaning of the concept of statistical uncertainty when we cover the binomial distribution and its associated statistical inference. We will see that the binomial distribution is a probability model for independent repeated tests with events that have two mutually exclusive outcomes, such as “heads” or “tails” in coin tossing experiments or “alive” or “dead” for patients in a medical study.

Regarding the health applications of statistics, the popular media carry articles on the latest drugs to control cancer or new vaccines for HIV. These popular articles restate statistical findings to the lay audience based on complex analyses reported in scientific journals. In recent years, the health sciences have become increasingly quantitative. Some of the health science disciplines that are particularly noteworthy in their use of statistics include public health (biostatistics, epidemiology, health education, environmental health); medicine (biometry, preventive medicine, clinical trials); nursing (nursing research); and health care administration (operations re-search, needs assessment), to give a few illustrations. Not only does the study of statistics help one to perform one’s job more effectively by providing a set of valuable skills, but also a knowledge of statistics helps one to be a more effective consumer of the statistical information that bombards us incessantly.

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