Sample Size Calculator

Accurately determine the required sample size for clinical trials, public health surveys, and population studies using validated statistical methods.

1. Select Study Design

Parameters for Comparing Means (T-Test)

Significance Level (α)

Statistical Power (1 - β)

Effect Size (Cohen's d)

Small: 0.2, Medium: 0.5, Large: 0.8

Allocation Ratio (n2/n1)

Parameters for Comparing Proportions

Significance Level (α)

Statistical Power (1 - β)

Proportion in Group 1 (p1)

Proportion in Group 2 (p2)

Parameters for Cohort Studies

Incidence in Exposed (Ie)

Incidence in Unexposed (Iu)

Ratio of Unexposed to Exposed (r)

Alpha

Parameters for Population Estimation

Population Size (N)

Expected Prevalence (p)

Margin of Error (e)

Confidence Level (Z)

Required Sample Size

Mathematical Logic & Accuracy

This tool predicts sample sizes by applying standard biostatistical power equations. It dynamically adjusts the complexity of the calculation based on your study design to ensure the results are both statistically valid and practically feasible.

Experimental (Comparing Means): We use the two-sample t-test power formula.

n = 2 * (Z_α/2 + Z_β)² / δ²

Where Z values represent the critical values for significance and power, and δ is the standardized effect size (Cohen's d). This ensures the study has sufficient sensitivity to detect the hypothesized difference.