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Calculate power & sample size for one-sample, two-sample and k-sample experiments. Advanced power and sample size calculator online: calculate sample size for a single group, or for differences between two groups (more than two groups supported for binomial data).
G*Power is a tool to compute statistical power analyses for many different t tests, F tests, χ2 tests, z tests and some exact tests. G*Power can also be used to compute effect sizes and to display graphically the results of power analyses.
The user can specify the type of test being run, their desired level of power, and alpha level to determine the sample size needed. The rest of this blog will show each step to determine the sample size needed for a paired samples t-test.
You can download the current version of G*Power from https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html. You can also find help files, the manual and the user guide on this website. Single-sample t-test; Paired-sample t-test; Independent-sample t-test; Two independent proportions; One-way ANOVA
Optimize your research design with the G Power Sample Size Calculator. Input effect size, significance level, and statistical power to determine the required sample size for robust study outcomes.
Calculator to determine the minimum number of subjects to enroll in a study for adequate power.
I recommend using the free power analysis tool called G*Power. Below I show an example of using it to find the sample size I’d need to detect a correlation of 0.7 with 95% power. The answer is a sample size of 20. See how I set up G*Power to get this answer below.