How to do cluster random sampling | DoRK#10 #research #sampling #clustersampling

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This video is a quick demonstration on how to do cluster random sampling for research using our trusty coin population.

Cluster random sampling is another example of probability sampling wherein the population is divided into different clusters. We can define a cluster as a collection of elements, in this case sampling units, based on a particular feature. The most commonly used theme to cluster a population is geographic location, such as country or city of residence. We use cluster random sampling if we think that each cluster is composed of different elements which are more or less a microcosm representation of the entire population.

Timestamps:
00:00:17 Definition of cluster random sampling
00:00:50 Step 0: get to know our scenario and coin population
00:01:40 Step 1: define the cluster
00:02:07 Step 2: adjust for effective sample size
00:02:28 Step 3: assign a number to each sampling unit in each cluster
00:02:41 Step 4: perform SRS to select a cluster then select ALL units within that cluster
(not explicitly stated in video) Step 5: repeat Step 4 until you get to at least your effective sample size

Enjoy!

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Link to other videos in the series:
- Definitions of study population, sampling frame, sampling unit and sample - https://youtu.be/5qO3EDInPLE
- Simple random sampling (SRS) - https://youtu.be/cFfe4ciRiaU
- Systematic random sampling - https://youtu.be/omLGZK0u_1Y
- Stratified random sampling - https://youtu.be/wgzobNjvTlc
- Stratified vs Cluster sampling - https://youtu.be/T5tc7jaGpgI