Why is 80% power the standard in education research?

Cohen (1988) argued 80% power represents an acceptable balance between Type I error (α = 0.05) and Type II error risk (β = 0.20), given that Type I errors are considered more serious in most scientific contexts. Many IES (Institute of Education Sciences) grants now require 80% power demonstration as a prerequisite for funding.

What effect sizes should education researchers anticipate?

Hattie's meta-analyses find most educational interventions produce small effects (d = 0.1–0.3). Planning for d = 0.2–0.3 is realistic for most school-based interventions. Planning only for d = 0.5 is optimistic and leads to underpowered studies that frequently produce false negatives.

Statistical Power Analysis for Education Studies

How It Works

Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification

Note: Interpret the power analysis result against the clinical thresholds and context described above.

How to Use

Enter the values for the patient or scenario you are assessing. Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification. Use the power analysis result to inform your clinical assessment.

Glossary and Definitions

Power analysis: A key concept in Power Analysis: Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification.
Statistical power: A key concept in Power Analysis: Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification.
Effect size education: A key concept in Power Analysis: Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification.
Type II error: A key concept in Power Analysis: Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification.
Sample size planning: A key concept in Power Analysis: Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification.
Education RCT: A key concept in Power Analysis: Calculate required sample size for a given effect size, significance level, and power level in education research contexts. Education studies require power ≥0.80; intervention studies typically target 0.90. Uses Cohen's conventions for effect size classification.