Sample Size Calculator
Design your study with confidence. This calculator helps you determine the minimum sample size needed to detect meaningful effects — so your research is powered, precise, and publishable.
Free Version
A quick and easy calculator for students and early-stage researchers estimating sample size for t-tests or ANOVAs using Cohen's d.
PRO Version
A robust, professional-grade tool with expanded test support, contextual guidance, and real-time assumption validation — ideal for grant proposals, dissertations, and published studies.
| Feature | Free Version | PRO Version |
|---|---|---|
| 📊 Calculates required sample size | ✅ Yes | ✅ Yes |
| 🧪 Supports t-tests (Cohen's d) | ✅ Yes | ✅ Yes |
| 📊 Supports one-way ANOVA (Cohen's f) | ✅ Yes | ✅ Yes |
| 🔁 Two-group designs only | ✅ Yes | ✅ Yes |
| 📈 Includes confidence interval estimate | ✅ Yes | ✅ No (replaced with precision commentary) |
| 📘 Uses jStat for calculations | ✅ Yes | ✅ Yes |
| 🔬 Includes Pearson’s r (correlation) | ❌ No | ✅ Yes |
| 📚 Input guidance and tooltips | ❌ No | ✅ Yes |
| 📌 Dynamic test-specific explanations | ❌ No | ✅ Yes |
| ⚠️ Input validation with highlighting | ❌ Basic | ✅ Advanced |
| 📋 APA-style output phrasing | ❌ No | ✅ Yes |
| 🧠 Designed for power analysis in psych research | ✅ Yes | ✅ Yes |
Quickly estimate the minimum sample size you need for your psychology experiments and research projects. This simple calculator helps you determine sample size based on effect size (Cohen’s d), desired statistical power, significance level (alpha), and test type (t-test or ANOVA).
Ideal for psychology students, dissertation writers, and social science researchers. Understand how effect size, power, and alpha affect sample size — and receive clear confidence intervals and standard deviation estimates. No login, no complex formulas — just fast, reliable guidance for study planning.
Note: This tool uses simplified formulas for quick estimation. For complex designs, consider using our Pro version or GPower.
Disclaimer
This tool is designed to assist psychology students and researchers with calculating sample size. While we strive for accuracy, the output provided is for guidance purposes only.
The creators of this tool are not responsible for decisions made based on its output. Always ensure your work aligns with the requirements of APA academic or professional standards.
Frequently Asked Questions
Sample Size Calculator for Psychology Research
What does this calculator do?
This tool estimates the minimum sample size needed for statistical tests like t-tests or ANOVAs, based on:
Your expected effect size (Cohen’s d)
Desired statistical power (typically 0.80)
Alpha level (usually 0.05 for 5% significance)
Selected test type (e.g., t-test)
It gives you a quick guideline for planning your study.
What is statistical power?
Power refers to the probability of detecting a true effect. A power of 0.80 means you have an 80% chance of detecting an effect if one exists. Psychology studies often use 0.80 as the standard.
What is effect size and why does it matter?
Effect size (Cohen’s d) measures the magnitude of the difference between groups. Typical benchmarks:
0.2 = small effect
0.5 = medium effect
0.8 = large effect
Larger effects require smaller sample sizes, while smaller effects need more participants to detect.
What’s the significance level (alpha)?
Alpha is the threshold for statistical significance — most researchers use 0.05, meaning a 5% chance of a Type I error (false positive). Lower alpha = more confidence, but more data needed.
Which test types does this calculator support?
Currently:
T-tests
ANOVA
How accurate is this calculator?
It uses standard approximation formulas based on statistical norms. For quick planning, it’s very effective — but for complex study designs, consider more advanced tools like G*Power or consulting a statistician.
Can I use this for dissertations, theses, or class assignments?
Yes. It’s designed specifically for:
Psychology undergrads
Master’s students
Dissertation writers
Research methods coursework
It gives you a fast starting point for IRB proposals, ethics forms, or pilot studies.
Does this tool account for dropout or missing data?
No — you should increase your sample size by 10–20% to allow for potential dropout, incomplete responses, or data exclusion.