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Questions and Answers
What is the key difference between simple random sampling and systematic random sampling?
When is stratified random sampling preferred over other sampling methods?
In cluster sampling, why are clusters formed with heterogeneous individuals?
What characteristic makes systematic random sampling a suitable choice when stratification with numerous data is used?
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Why is it essential for samples within strata to be homogenous in stratified random sampling?
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When is simple random sampling more appropriate than systematic random sampling?
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Study Notes
Types of Sampling Methods
- Simple Random Sampling vs Systematic Random Sampling: The key difference lies in the selection process; simple random sampling involves randomly selecting units from the population, whereas systematic random sampling involves selecting every nth unit from the population list.
Stratified Random Sampling
- Preferred over other methods: When the population is heterogeneous and consists of distinct subgroups, and the researcher wants to ensure each subgroup is adequately represented in the sample.
- Importance of homogeneous strata: Samples within strata must be homogeneous to ensure that the sample accurately represents the population, and to minimize bias and variability.
Cluster Sampling
- Forming clusters with heterogeneous individuals: Clusters are formed with heterogeneous individuals to increase the representativeness of the sample and to reduce selection bias.
Systematic Random Sampling
- Suitable choice with numerous data: Systematic random sampling is suitable when stratification is used with numerous data, as it ensures representation of all strata and helps to reduce selection bias.
Sampling Methods Comparison
- Simple Random Sampling vs Systematic Random Sampling: Simple random sampling is more appropriate when the population is homogeneous, while systematic random sampling is more suitable when the population is heterogeneous and has distinct subgroups.
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Description
Test your knowledge on different sampling methods such as simple random sampling, systematic random sampling, and stratified random sampling. Learn how each method is used to select samples from a population.
