Sampling Methods Quiz
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Questions and Answers

What is the key difference between simple random sampling and systematic random sampling?

  • Simple random sampling is used for large populations, while systematic random sampling is used for small populations.
  • Simple random sampling involves selecting individuals through a lottery, while systematic random sampling involves selecting individuals in a predetermined order. (correct)
  • Simple random sampling requires using a table of random numbers, while systematic random sampling requires using statistical software.
  • Simple random sampling involves dividing the population into clusters, while systematic random sampling involves dividing the population into strata.
  • When is stratified random sampling preferred over other sampling methods?

  • When the population is small and geographically clustered.
  • When the population is divided into clusters of the same size.
  • When all individuals in the population are similar.
  • When the population is very large and widely spread out. (correct)
  • In cluster sampling, why are clusters formed with heterogeneous individuals?

  • To minimize the need for stratification.
  • To simplify the data collection process within each cluster.
  • To make the sample more homogenous within clusters.
  • To ensure that each cluster is representative of the entire population. (correct)
  • What characteristic makes systematic random sampling a suitable choice when stratification with numerous data is used?

    <p>The ability to ensure representation from every stratum.</p> Signup and view all the answers

    Why is it essential for samples within strata to be homogenous in stratified random sampling?

    <p>To ensure that each stratum is representative of the population.</p> Signup and view all the answers

    When is simple random sampling more appropriate than systematic random sampling?

    <p>When dealing with geographically dispersed populations.</p> Signup and view all the answers

    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.

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