Calculate required sample size for surveys and research studies.
Critical step for research planning
Sample size is the minimum number of individuals needed to represent a population in research. Too small sample doesn't give reliable results, while too large sample creates unnecessary cost and time loss. Parameter meanings: Confidence level = how reliable your results are (95% most common). Margin of error = how much your result can deviate from true value (±5% standard). Proportion = expected response percentage (50% safest if unknown). Population = total size of your target audience. Practical examples and applications: City survey (100,000 population, 95% confidence, ±5% error → ~385 people). Company satisfaction survey (500 employees → ~217 people). Product testing (unlimited customer base → ~384 people). Academic research (2000 student population → ~322 people).
Find answers to common questions
95% confidence level is the most common choice. This means if you conduct 100 surveys, results will be correct in 95 of them. You can use 99% for more sensitive research.
Other useful tools related to statistical calculations
Use 50% if unknown (most conservative option)