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Probability Sample: Definition, Problems & Examples

Instructor: Tara Lehan

With a doctorate in marriage and family therapy and a certificate in measurement and statistics, Tara has taught social science courses to students of all levels.

When using inferential statistics to generalize findings from a sample to a population, a probability sample must be used. In this lesson, you will learn about the definition of a probability sample as well as the various types.

What is a Probability Sample?

A probability sample is a portion of a population that is selected using a method based on the theory of probability. To be considered as a probability sample, it must be developed using random selection. Therefore, each member of the population of interest from which the sample is drawn has the same chance of being selected.

In this context, the word 'random' has a precise meaning. For example, it is not accurate to collect responses from individuals who happen to be passing by on a street in Boston, Massachusetts, and say that you have a random sample of Boston residents. The people on that street might not be representative of the larger population for many reasons. For example, they might be more likely to live or work on or near that street than other people in Boston. Such a sample would be considered to be 'biased,' because some members of the population are more likely to be selected than others.

Collecting Random Samples

Since they are representative of the larger population, probability samples provide the most valid or credible results, as they reflect the characteristics of the population from which they are selected. Random selection can be achieved in a variety of ways, including drawing slips of paper from a hat or using a computer program that assigns random numbers to each member of the population.

Different methods can be employed to select a random sample, including:

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