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Survey Sample Size Calculator

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Survey Sample Size Calculator

Figure out how many people you need to survey to get reliable results. The Survey Sample Size Calculator turns Cochran’s formula into a one-click answer, supports finite populations with the appropriate correction, and shows a sensitivity table so you can see exactly how the requirement shifts as your margin of error or confidence level changes.

كيفية استخدام

Enter your population – the total people you could possibly survey. Leave it empty if the population is unknown or very large (national surveys, online users, etc.).
Set your margin of error – the acceptable error in your final results. Five percent is a common default for marketing and customer research; political polls often target three percent.
Pick a confidence level – how often the true result will fall inside your margin of error if you repeated the survey. Ninety-five percent is the standard.
Adjust the expected proportion – your best guess at the share of “yes” answers. Leave the slider at fifty percent for the most conservative (largest) estimate.
Read the result – the calculator shows the minimum sample size, a step-by-step formula breakdown, and a sensitivity table comparing different margins of error.

خصائص

Cochran’s formula – uses the classic n = z² × p(1 − p) / e² formula trusted by statisticians since 1963.
Finite population correction – automatically applies the FPC when you supply a known population, dramatically lowering the sample size for small audiences.
Six confidence levels – from 80% all the way to 99.9%, with the matching critical z-score shown next to each option.
Adjustable expected proportion – slide between 1% and 99% when you have prior information about the likely response distribution.
Sensitivity table – instantly compare sample sizes across margins of error from 1% to 10%, with your current setting highlighted.
Step-by-step formula – see the math substituted with your real numbers, ideal for thesis appendices or methodology sections.
إعدادات مسبقة سريعة – jump to common scenarios like a national poll, customer survey, employee survey, or pilot study with one click.
Copy-ready summary – grab a plain-text summary of the calculation to paste into briefs, emails, or documents.
يُشغل بالكامل في المتصفح الخاص بك – nothing is sent to a server, so your survey planning stays private.

 التعليمات

What is sample size in a survey?

Sample size is the number of respondents you collect data from. It determines how precisely the results from your sample reflect the true value in the wider population — bigger samples produce narrower margins of error, but with diminishing returns.
What is the margin of error?

The margin of error is the maximum expected difference between the percentage you observe in your sample and the true percentage in the full population, at a given confidence level. A five percent margin of error means the real value is expected to fall within plus-or-minus five percentage points of the surveyed value.
What is a confidence level?

The confidence level is the long-run probability that the true value lies inside your margin of error. A ninety-five percent confidence level means that if you repeated the survey many times, ninety-five percent of those samples would produce an interval containing the true value.
What is the finite population correction?

The finite population correction (FPC) is a multiplier applied to a sample-size formula when the population is small relative to the sample. It accounts for the fact that sampling a large fraction of a finite population reduces sampling variance, allowing a smaller sample to reach the same precision.
Why is fifty percent the most conservative expected proportion?

In Cochran's formula the term p × (1 − p) is maximised when p equals 0.5. Picking fifty percent therefore yields the largest possible required sample, guaranteeing your study has enough power even when no prior information about the true proportion exists.