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These instructional videos provide a guide and examples of how to apply stratified random sampling.
Stratified random sampling is a probabilistic sampling method in which the first step is to split the population into strata, i.e. sections or segments. The strata are chosen to divide a population into important categories relevant to the research interest.
For example, if interested in school achievement, we may want to first split schools into rural, urban, and suburban as school achievement on average may be quite distinct between these regions. The second step is to take a simple random sample within each stratum. This way, a randomised probabilistic sample is selected within each stratum. Each stratum should be mutually exclusive (i.e. every element in the population can be assigned to only one stratum), and no population element can be excluded in strata construction.
Stratified random sampling video
This video explains the process of creating a stratified random sample.
Stratified random sampling Stata walkthrough
This video describes how to use the software program Stata to create a stratified random sample.
Sources
IDinsight. (2021). Stratified random sampling and Stratified random sampling in Stata. Retrieved from: https://sites.google.com/idinsight.org/bootcamp/lessons/7-sampling-for-surveys
This is part of a series
You can find all videos and additional materials in the Sampling for Surveys lesson on the IDinsight website.
'Sampling for surveys: Stratified random sampling' is referenced in:
Framework/Guide
- Rainbow Framework :
Method
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