Power & Sample Size Analysis in Prism

Stop guessing how many samples you need! In this tutorial, Professor Keenan Hartert from Minnesota State University walks you through Prism's powerful Power and Sample Size Analysis tool to design robust experiments and confidently interpret your results. Learn how to: • Determine the ideal sample size for t-tests and ANOVA before you run an experiment. • Understand the relationship between sample size, power, effect size, and significance. • Use your existing data to calculate effect size and plan future replication studies. • Avoid false negatives by ensuring your study has sufficient power to detect a real effect. • Access and use the integrated online tool within the Prism ecosystem. This is an essential skill for any researcher or student who wants to save time, resources, and ensure their statistical conclusions are reliable. Key Topics Covered: • Unpaired t-test Power Analysis • Paired t-test Power Analysis (accounting for correlation) • One-Way ANOVA Power Analysis • Interpreting Power Curves and Tables • Using Real Data to Inform Your Calculations OTHER FREE USEFUL TOOLS FOR RESEARCHERS Explore our educational resources to advance your knowledge of Prism, statistics and data visualization https://www.graphpad.com/resources