Review:
Sampling Methods In Statistics
overall review score: 4.5
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score is between 0 and 5
Sampling methods in statistics refer to the techniques used to select a subset of individuals or items from a larger population for the purpose of making inferences about the population as a whole.
Key Features
- Random sampling
- Stratified sampling
- Cluster sampling
- Systematic sampling
- Convenience sampling
Pros
- Allows researchers to collect data efficiently and effectively
- Helps in reducing the cost and time required for data collection
- Provides a basis for making accurate statistical inferences
Cons
- Risk of selection bias if sampling method is not properly chosen
- May not always be representative of the entire population