Sample Size Estimation: The Easy Way

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2 Scopus citations


This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and by holding the error probabilities constant (α =.05 and β =.20), an investigator can focus on effect size. The effect size can be thought of as a measure of association, such as the correlation coefficient. Here, effect size is linked across three of the most commonly used bivariate analyses (simple linear regression, the two-group analysis of variance [ANOVA] or t-test, and the comparison of proportions or χ2 test) with a correlation coefficient or equivalent measure of association. Tabled values and examples are provided.

Original languageEnglish (US)
Pages (from-to)333-347
Number of pages15
JournalField Methods
Issue number4
StatePublished - Nov 1 2015


  • chi-square test
  • measures of association
  • regression
  • sample size
  • t-test

ASJC Scopus subject areas

  • Anthropology


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