INPUTS
Slovin's formula
Use when the population size is known and you only need to set the margin of error.
SAMPLE SIZE CALCULATOR
INPUTS
Use when the population size is known and you only need to set the margin of error.
METHOD
n = N ÷ (1 + N·e²)N is the population size and e is the margin of error as a decimal. For N = 1,200 and e = 0.05: n = 1,200 ÷ (1 + 1,200 × 0.0025) = 1,200 ÷ 4 = 300 respondents.
The formula is short and easy to defend in a methods chapter, which is why it is common in undergraduate and master's research. It quietly assumes maximum variability (p = 0.5).
n₀ = z²·p(1 − p) ÷ e² → n = n₀ ÷ (1 + (n₀ − 1) ÷ N)At 95% confidence (z = 1.96), p = 0.5, and e = 0.05, n₀ = 384.16. For a population of 1,000 the correction gives 277.7, so you need 278 respondents.
Use Cochran when a reviewer may ask about the confidence level, or when a pilot study suggests p is far from 0.5.
State the population, the formula, the margin of error (and confidence level for Cochran), and the final rounded sample. The calculator generates this sentence for you; cite Yamane (1967) or Cochran (1977) as your department prefers.
Always round up. If you expect non-response, divide by the expected response rate to decide how many people to invite.
ABOUT THIS TOOL
Find the minimum sample size for a survey or thesis using Slovin/Yamane or Cochran's formula, with confidence level, margin of error, population size, response-rate adjustment, and a copy-ready methods sentence.
KEY FUNCTIONS
LEARN THE METHOD
Justify your sample size the way supervisors expect: choose the test, set the expected effect size, alpha, and power, and get the required N, a power curve, and a methodology sentence.
Turn questionnaire frequency counts into weighted means, standard deviations, rankings, and a verbal interpretation table ready for a thesis results chapter.
Check the internal consistency of a questionnaire scale from raw item scores, reverse-code negatively worded items, and see which items lower reliability.