ERIC Number: EJ1136939
Record Type: Journal
Publication Date: 2015-Nov
Abstractor: As Provided
Reference Count: 15
Sample Size Estimation: The Easy Way
Weller, Susan C.
Field Methods, v27 n4 p333-347 Nov 2015
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 (a = 0.05 and ß = 0.20), 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 ?[superscript 2] test) with a correlation coefficient or equivalent measure of association. Tabled values and examples are provided.
Descriptors: Sample Size, Statistical Analysis, Computation, Hypothesis Testing, Measurement, Effect Size, Correlation, Error of Measurement, Regression (Statistics), Statistical Inference
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
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