When conducting a study and reporting results, sample size, or the number of participants in a study, plays a key role in defining the validity and applicability of a study's results. Often, the larger the sample size, the more applicable the results in a real world setting. When reporting your results, presenting sample size is a very basic step in the overall study.

An italicized "n" is a broadly-accepted variable; the American Psychological Association style for reporting sample size, and it is also used in chemistry, physics and mathematics. Although the larger the sample size the less the variability that could occur, a sample size can be too big and unwieldy depending on the study. (Consider that prior to an election, a straw poll does not sample 100% of voters.) Some professors or publications may require you to report standard error as well as your sample size. See the Resources below for more information on calculating standard error.

Report sample size along alongside an italicized "n"; this is the statistical abbreviation for sample size. Therefore, n = 120 means your sample size, or number of participants, was 120.

Outside of just reporting your sample size, you may also wish to explain how you obtained your sample, whether through random sampling or convenience sampling. This information will have an impact on how your data is viewed.

Discuss the population from which your sample was taken. If you only selected students for your sample, mention that information.

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- An italicized "n" is a broadly-accepted variable; the American Psychological Association style for reporting sample size, and it is also used in chemistry, physics and mathematics. Although the larger the sample size the less the variability that could occur, a sample size can be too big and unwieldy depending on the study. (Consider that prior to an election, a straw poll does not sample 100% of voters.) Some professors or publications may require you to report standard error as well as your sample size. See the Resources below for more information on calculating standard error.

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