Sample Size Calculator

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.