Sample Size Calculator

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Clinical Trial Calculator

FDA-compliant sample size calculations for clinical trials, RCTs, and medical research with proper power analysis.

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Survey Sample Size

Calculate minimum sample size for surveys and market research with confidence intervals and margin of error.

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Power Analysis

Determine statistical power for your study design. Calculate effect size, power, and sample size relationships.

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G*Power Alternative

Free online alternative to G*Power software with intuitive interface and comprehensive statistical calculations.

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Multiple Study Designs

Support for t-tests, ANOVA, regression analysis, correlation studies, and two-proportion comparisons.

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Dissertation Support

Perfect for PhD and Masters students. Generate sample size justifications for thesis and dissertation committees.

Sample Size Calculator Types

Unknown Population Calculator

Most common scenario for surveys and research studies where population size is unknown or very large.

95% confidence level standard
5% margin of error default
Conservative estimates

Two Group Comparison

Calculate sample size for comparing means or proportions between two independent groups.

Independent t-test calculations
Chi-square test sample sizes
Effect size considerations

Regression Analysis

Determine adequate sample size for multiple regression and correlation studies.

Multiple predictor variables
R-squared effect sizes
Statistical power optimization

Pilot Study Calculator

Calculate sample sizes for preliminary studies and feasibility assessments.

10% rule of thumb
Variance estimation
Resource optimization

How to Calculate Sample Size

Define Your Research Question

Clearly specify your study objectives, primary outcome measures, and the type of statistical test you plan to use.

Set Statistical Parameters

Choose your significance level (α = 0.05), desired power (typically 80%), and expected effect size based on literature or pilot data.

Input Values in Calculator

Enter your parameters into our sample size calculator. The tool will compute the minimum required sample size for your study.

Account for Attrition

Add 10-20% to your calculated sample size to account for potential dropouts, missing data, and non-response rates.

Sample Size Calculator Comparison

Feature	DataStatPro	G*Power	Manual Calculation	SPSS
Web-based Access	✅ No download required	❌ Software installation	❌ Complex formulas	❌ License required
Clinical Trial Support	✅ FDA compliant	✅ Comprehensive	❌ Error-prone	✅ Advanced features
User-Friendly Interface	✅ Intuitive design	❌ Complex interface	❌ Manual calculations	❌ Steep learning curve
Multiple Study Types	✅ Comprehensive coverage	✅ Extensive options	❌ Limited scope	✅ Professional features
Cost	✅ Free	✅ Free	✅ Free	❌ Expensive license

Sample Size Calculator FAQ

How do I calculate sample size for unknown population?

For unknown populations, use our sample size calculator with 95% confidence level and 5% margin of error. The formula accounts for infinite population size and provides conservative estimates suitable for most research scenarios.

What is the minimum sample size for clinical trials?

Clinical trial sample sizes depend on effect size, power (typically 80%), and significance level (usually 0.05). Our calculator provides FDA-compliant sample size calculations for various clinical trial designs.

How is power analysis related to sample size?

Power analysis determines the probability of detecting a true effect. Higher statistical power requires larger sample sizes. Our calculator computes both sample size and power analysis simultaneously.

What effect size should I use for my study?

Effect sizes depend on your research field and study type. Small effects (0.2), medium effects (0.5), and large effects (0.8) are common benchmarks. Review literature in your field for appropriate effect size estimates.

Can I use this calculator for dissertation research?

Yes! Our calculator is perfect for PhD and Masters students. It provides sample size justifications that meet dissertation committee requirements and follows established statistical guidelines.