How are samples randomly chosen from several groups in stratified random sampling?
Understand the Problem
The question is asking about the process of selecting samples in stratified random sampling, specifically how samples are chosen from different groups.
Answer
Population is divided into strata and each stratum is randomly sampled.
In stratified random sampling, the population is divided into subgroups called strata based on shared characteristics. Each subgroup is then randomly sampled using a method like simple random sampling or systematic sampling to ensure representation from all subgroups.
Answer for screen readers
In stratified random sampling, the population is divided into subgroups called strata based on shared characteristics. Each subgroup is then randomly sampled using a method like simple random sampling or systematic sampling to ensure representation from all subgroups.
More Information
Stratified random sampling helps to ensure that specific subgroups are adequately represented in the sample. This can lead to more accurate and reliable statistical results compared to simple random sampling, particularly when dealing with diverse populations.
Tips
One common mistake is failing to properly identify and define strata, which can lead to bias if the strata aren't representative of the population.
Sources
- Stratified Random Sampling: Definition & Guide - Qualtrics - qualtrics.com
- How Stratified Random Sampling Works, With Examples - investopedia.com
- Types of sampling methods | Statistics (article) - Khan Academy - khanacademy.org
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