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Presented November 13, 2015


Effect Size & Power Analysis + G*Power

What is Effect Size?

  • A quantitative (numerical) measure of the strength or magnitude of a relationship
  • The criterion for evaluating the strength of a statistical claim
  • A larger absolute value indicates a stronger effect
  • Plays an important role in power analysis, sample size planning, and meta-analysis
  • Examples: correlation between 2 variables, difference in group means, risk ratio, ect.

What is Power Analysis?

  • Answers the question: how large does my sample need to be?
  • Should always be done while designing an experiment or survey
  • Four pieces: sample size, effect size, significance level, & Power (given any 3, you can solve for the 4th)

What you will be able to do after this workshop

  • Know how to determine effect size for various types of study designs
  • Convert between various measures of effect size
  • Understand the relationship between the four components of a power analysis
  • Use G*Power to determine required sample size ‘a priori’ when planning a study
  • Use G*Power to determine observed power after a study is complete

How to obtain G*Power

Directly available for FREE for PC or MAC at


Workshop Materials