1. What is the Raosoft Sample Size Formula?

The Raosoft sample size formula calculates the minimum number of participants needed for a prevalence study based on desired confidence level, expected prevalence, and precision. It's widely used in epidemiological research and survey design.

2. How Does the Calculator Work?

The calculator uses the Raosoft formula:

Where:

• \( n \) — Required sample size
• \( Z \) — Z-score for desired confidence level
• \( p \) — Expected prevalence (proportion)
• \( d \) — Desired precision (margin of error)

Explanation: The formula balances confidence level (Z), expected prevalence (p), and desired precision (d) to determine the minimum sample size needed.

3. Importance of Sample Size Calculation

Details: Proper sample size calculation ensures studies have adequate power to detect effects while avoiding unnecessary resource expenditure on excessive sampling.

4. Using the Calculator

Tips:

• For unknown prevalence, use 0.5 (50%) for most conservative estimate
• Common precision values are 0.05 (5%) or 0.03 (3%)
• 95% confidence (Z=1.96) is standard for most studies

5. Frequently Asked Questions (FAQ)

Q1: When should I use this formula?
A: Use for cross-sectional studies estimating prevalence or proportion in a population.

Q2: What if my population is small?
A: For populations under 10,000, apply finite population correction: n_adjusted = n / (1 + (n - 1)/N)

Q3: How does prevalence affect sample size?
A: Sample size peaks at p=0.5; less common prevalences (near 0 or 1) require smaller samples.

Q4: What's the relationship between precision and sample size?
A: Halving precision requires quadrupling sample size (inverse square relationship).

Q5: Are there alternatives to this formula?
A: Yes, other formulas exist (e.g., Cochran's) but Raosoft is simple and widely accepted for prevalence studies.