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Power Analysis Added to SPSS 27


Power analysis is often an important first step in research. It is used to estimate the minimum sample size needed to detect a hypothesized difference or relationship. If the sample size is too small, your study may not have the power needed to detect a significant difference. If your sample size is unnecessarily large, you may be wasting time or other resources.

Power Analysis procedures are now included in SPSS 27. These include options to calculate sample sizes (or observed power) for:

  • Means comparisons: One Sample T-test, Paired Samples T-test, Independent Samples T-test, and One-way ANOVAs.
  • Proportions: Related-Sample Binomial Test (McNemar), Independent-Sample Binomial Test (2×2 Chi-Square), One-Sample Binomial Test
  • Correlations
  • Linear Regression

The power analysis tools available in SPSS are a great option for basic analyses however if you are needing to calculate a sample size for advanced statistical analysis, you may need to use a more complex power analysis tool, such as G-Power OIT’s Research Computing Support can also assist you in determining sample sizes. If you would like to set up a one-on-one consultation with a member of our staff, submit a request through the OIT HelpDesk online Research Computing Support portal or by phone at 865-974-9900.