10% Condition
Definition
The 10% condition states that for sampling without replacement to be considered valid, the sample size must be less than 10% of the population size.
Analogy
Imagine you have a bag filled with different colored candies. If you want to randomly select candies from the bag without replacement (meaning once you pick one candy, it's not put back in), the number of candies you pick should be less than 10% of the total number in the bag. This ensures that your sample doesn't significantly affect the overall composition of candies in the bag.
Related terms
Sampling Bias: When certain members or groups in a population are systematically excluded or underrepresented in a sample.
Simple Random Sample: A sampling method where every member of the population has an equal chance of being selected for the sample.
Stratified Sampling: Dividing the population into subgroups (strata) and then selecting samples from each subgroup proportionally to their representation in the population.
"10% Condition" appears in:
Study guides (4)
Additional resources (2)
Practice Questions (2)
- What is the role of the 10% condition in a t-test for the slope?
- What is the purpose of the "10% condition" in determining the appropriateness of a binomial model for a random event?
Resources
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