Home
Back
Random Sample Probability Formula:
| From: | To: |
Random sample probability represents the chance that any individual in a population will be selected in a random sample. It's a fundamental concept in statistics and sampling theory that helps researchers understand selection likelihood.
The calculator uses the simple probability formula:
Where:
Explanation: This formula calculates the simple probability that any single individual from the population will be included in a random sample.
Details: Understanding sample probability is crucial for research design, survey methodology, and statistical analysis. It helps determine appropriate sample sizes and assess the representativeness of samples.
Tips: Enter the sample size and population size as whole numbers. The sample size must be less than or equal to the population size. The result will be displayed as a percentage.
Q1: What is a good sample probability for research?
A: This depends on the research context. Higher probabilities generally mean more representative samples, but practical constraints often limit sample sizes.
Q2: How does this relate to margin of error?
A: Sample probability is different from margin of error. While probability indicates selection chance, margin of error relates to the precision of estimates from the sample.
Q3: When is simple random sampling appropriate?
A: Simple random sampling works best when the population is homogeneous and a complete sampling frame is available.
Q4: What if my sample size exceeds population size?
A: This is mathematically impossible. The calculator will not compute results if sample size is greater than population size.
Q5: Can this calculator handle complex sampling designs?
A: No, this calculator only computes simple random sample probability. Stratified or cluster sampling require more complex calculations.