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Understanding Stratified Sample vs Cluster Sample

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Understanding Stratified Sample vs Cluster Sample

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Questions and Answers

What is a key difference between a stratified sample and a cluster sample?

In a stratified sample, random samples from each strata are included.

In a cluster sample, every sample of size n has an equal chance of being included.

In a stratified sample, the clusters to be included are selected at random and then all members of each cluster are included. (correct)

In a cluster sample, the only samples possible are those including every kth item from the random set.

What is a characteristic of a cluster sample?

The only samples possible are those including every kth item from the random set.

Random samples from each strata are included.

Every sample of size n has an equal chance of being included.

The clusters to be included are selected at random and then all members of each cluster are included. (correct)

Which statement accurately describes a stratified sample?

The only samples possible are those including every kth item from the random set.

The clusters to be included are selected at random and then all members of each cluster are included.

Random samples from each strata are included. (correct)

Every sample of size n has an equal chance of being included.

Which sampling method ensures that every individual in the population has an equal chance of being included?

<p>Simple random sample</p> Signup and view all the answers

Study Notes

Sampling Methods Overview

Stratified Sample vs. Cluster Sample:
- Stratified sampling divides the population into distinct subgroups (strata) based on specific characteristics (e.g., age, income) and samples from each stratum. In contrast, cluster sampling divides the population into clusters (often geographically) and randomly selects entire clusters to represent the population.
Characteristic of Cluster Sample:
- In cluster sampling, entire groups are used as units of analysis, which means every member of a selected cluster participates in the study, rather than sampling individuals from various strata.
Describing Stratified Samples:
- A stratified sample accurately reflects the diversity of the population by ensuring that every stratum is represented in the sample proportionally to its size in the population.
Equal Chance Sampling Method:
- Simple random sampling ensures that each individual in the population has an equal chance of being included, promoting fairness and reducing selection bias.

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Description

This quiz assesses your knowledge of the difference between a stratified sample and a cluster sample. Test your understanding of sampling methods in statistics.