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Knowledge of statistics is essential to understand the biomedical science literature. The focus of this chapter is to describe concepts as they relate to evaluating medical literature, as opposed to mathematical calculation and programming of specific statistical tests.

Populations and Samples

A population refers to all objects of a similar type in the universe, while a sample is a fraction of the population chosen to be representative of the specific population of interest. Thus, samples are chosen to make generalizations about the population of interest. Researchers typically do not attempt to study the entire population as most often data cannot be collected for everyone within a population. This emphasizes why the sample must be chosen at random; that is, each member of the population must have an equal chance of being included in the sample. A random sample does not imply that the sample is drawn haphazardly or in an unplanned fashion. There are several approaches of selecting a random sample, with the most common method employing a random number table. A random number table contains all integers between one and infinity that have been selected without any trends or patterns (ie, completely random). Depending on the type of study design, a simple random sample may not be the best method for selecting a representative sample. On occasion, it may be necessary to separate the population into mutually exclusive groups called strata, where a specific factor (eg, patient race, gender) will be contained in separate strata to aid in analysis. In this case, the random sample is drawn within each stratum individually, termed a stratified random sample. Another method of randomly sampling a population is known as cluster sampling. Cluster sampling is appropriate when there are natural groupings within the population of interest. Another sampling method is known as systematic sampling. This method is used when information about the population is provided in list format, such as in the telephone book, election records, class lists, licensure records, and so forth. A form of systematic sampling is the equal-probability method where one individual is selected at random and every nth individual is then selected thereafter. Finally, it should be noted that researchers often use convenience sampling. A convenience sample selects participants based on the convenience of the researcher. That is, no attempt is made to select a random sample representative of the population. However, within the convenience sample, participants may be selected randomly. Obviously, there are significant weaknesses to this type of sampling, primarily, limited generalization (ie, external validity).

Variables and Data

A variable is a characteristic that is being observed or measured. Data are the measured values assigned to the variable for each individual member of the population. For example, a variable would be patient gender, while the data are whether the patient is male or female. There are three types of variables: dependent (DV), independent (IV), ...

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