Understanding Sample Proportion
How we calculate. Sample proportion % = successes ÷ sample size × 100. The form uses the same arithmetic as the worked examples on this page. See our methodology and accuracy policy.
Real-world scenario: A typical Sample Proportion case uses successes 42 and sample size (n) 200. Enter the same figures below to reproduce the worked path.
What is Sample Proportion?
A basic inferential building block for confidence intervals and hypothesis tests about a population share.
- Successes ≤ n
- Define success clearly
- Use with MoE for interval width
The Formula
Worked Example
Common Use Cases
- Surveys: yes-rate estimates
- A/B tests: conversion shares
- QA sampling: defect shares
Pro Tips
- Report n with the percent
- Check independence assumptions
- Small n → unstable p̂
Limitations: Sample Proportion results are educational statistics aids—not formal statistical certification. Confirm assumptions (SRS, large-sample approximations, labeling) for your analysis.
FAQ
Is this the population proportion?
No—this is the sample estimate p̂. Population p is usually unknown.
What if n is 0?
Proportion is undefined—enter a positive sample size.
Authoritative References
For statistical definitions and survey practice, consult: