1. What is G*Power Sample Size Calculation?

G*Power is a statistical power analysis program used to compute sample size requirements for various statistical tests. It helps researchers determine the minimum number of participants needed to detect an effect of a given size with a specified level of confidence.

2. How Does the Calculator Work?

The calculator uses G*Power principles for sample size estimation:

Where:

• \( \alpha \) — Significance level (typically 0.05)
• \( \text{power} \) — Statistical power (typically 0.8)
• \( \text{effect size} \) — Cohen's d effect size measure
• \( n \) — Required sample size per group

Explanation: The calculation determines the minimum sample size needed to achieve adequate statistical power while controlling for Type I and Type II errors.

3. Importance of Sample Size Calculation

Details: Proper sample size calculation ensures studies have sufficient power to detect meaningful effects, prevents wasted resources on underpowered studies, and enhances the validity and reliability of research findings.

4. Using the Calculator

Tips: Enter alpha level (typically 0.05), desired power (typically 0.8), and expected effect size (Cohen's d). The calculator will determine the required sample size per group for your study.

5. Frequently Asked Questions (FAQ)

Q1: What is statistical power?
A: Statistical power is the probability that a test will correctly reject a false null hypothesis (typically set at 0.8 or 80%).

Q2: What are typical values for alpha and power?
A: Alpha is typically 0.05 (5% significance level) and power is typically 0.8 (80% chance of detecting an effect if it exists).

Q3: How do I determine effect size?
A: Effect size can be estimated from previous studies, pilot data, or based on minimum clinically important difference. Cohen's d of 0.2=small, 0.5=medium, 0.8=large.

Q4: What if I have multiple groups?
A: This calculator provides sample size per group. For multiple groups, multiply by the number of groups and consider adjustments for multiple comparisons.

Q5: Are there limitations to sample size calculations?
A: Yes, calculations depend on accurate effect size estimates and assume normal distribution. Actual requirements may vary based on study design and statistical methods.