In a study, the sample is chosen by separating all cars by size, and selecting 10 of each size grouping

What is the sampling method?
Systematic
Convenience
Simple random
Stratified
Cluster

The sampling method described is **stratified sampling**.

In stratified sampling, the population is divided into distinct subgroups or "strata" (in this case, cars separated by size). Then, a sample is taken from each subgroup (10 cars from each size grouping). This ensures that all groups are represented in the sample.

Would you like further details on how stratified sampling works or any related concepts?

Here are 5 related questions:
1. How does stratified sampling differ from cluster sampling?
2. What are the advantages of using stratified sampling?
3. In what scenarios would simple random sampling be preferred over stratified sampling?
4. How do you determine the number of subgroups (strata) in stratified sampling?
5. What are potential challenges in implementing stratified sampling?

**Tip:** In stratified sampling, it's important that the strata are mutually exclusive and collectively exhaustive, meaning no overlap and all individuals must belong to one subgroup.

In a study, the sample is chosen by separating all cars by size, and selecting 10 of each size grouping. What is the sampling method? Options: Systematic, Convenience, Simple random, Stratified, Cluster.

Learn about stratified sampling, a method used in statistics where a population is divided into subgroups or strata, such as cars by size, with a sample taken from each group. This example demonstrates how selecting 10 cars from each size category ensures representative sampling, suitable for Grades 9-12.

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