Research Methods in Sampling
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Questions and Answers

What is the main goal of probability sampling?

  • To include every individual in the population.
  • To examine non-representative elements of populations.
  • To examine representative elements of populations. (correct)
  • To eliminate the need for sampling frames.
  • Which of the following procedures is NOT a type of probability sampling?

  • Systematic random sampling
  • Judgmental sampling (correct)
  • Stratified random sampling
  • Cluster random sampling
  • In systematic random sampling, how is the first sample member selected?

  • It is selected by using the highest number in the population.
  • It is chosen using a simple random sampling method. (correct)
  • It is randomly selected from a non-ordered list.
  • It must be the first member of the population list.
  • What is a characteristic of stratified random sampling?

    <p>It ensures that each subgroup is adequately represented.</p> Signup and view all the answers

    Which sampling method is best when the population is geographically spread out?

    <p>Cluster random sampling</p> Signup and view all the answers

    What is a population in research?

    <p>The entire group of subjects being studied</p> Signup and view all the answers

    Which of the following describes the target population?

    <p>It encompasses the entire group to which findings are generalized.</p> Signup and view all the answers

    What is the primary advantage of sampling in research?

    <p>It reduces costs and manpower while gathering data quickly.</p> Signup and view all the answers

    Which statement best describes the accessible population?

    <p>It is the group of subjects that can actually be studied by the researcher.</p> Signup and view all the answers

    What is the purpose of using a sample in research?

    <p>To create a subset that accurately reflects the larger population</p> Signup and view all the answers

    Study Notes

    Sampling and Population

    • A representative sample is crucial for valid research findings.
    • Populations consist of all subjects under study, which can include varied entities like hospitals or schools.
    • A sample is a subgroup selected from a population for analysis.
    • Populations can be categorized into two groups: Target population and Accessible population.

    Target vs. Accessible Population

    • Target population: The entire group to which a researcher seeks to generalize findings (e.g., all institutionalized individuals with psychiatric issues).
    • Accessible population: The actual group available for study, such as pregnant women in a specific clinic.

    Sample Selection

    • A sample represents the population and aids in making generalizations about the larger group.
    • Conducting a census includes studying every member of a population.

    Advantages of Sampling

    • Reduces costs and manpower requirements.
    • Facilitates quicker data collection.
    • Allows for more comprehensive data and potentially greater accuracy.

    Sampling Methods

    • Two main sampling procedures: Probability sampling and Non-probability sampling.

    Probability Sampling

    • Involves random selection, ensuring each member of a population has a chance to be included.
    • Aims to examine representative elements of populations.
    • Types of probability sampling include Simple Random Sampling, Systematic Random Sampling, Stratified Random Sampling, Cluster Random Sampling, and Multistage Sampling.

    Simple Random Sampling (SRS)

    • Every member has an equal chance of selection.
    • Requires a sampling frame (list of the population) with unique identifiers.
    • Selection methods include shuffling cards or using random number generators.

    Systematic Random Sampling

    • Involves selecting members based on a calculated sampling proportion (e.g., 1 in 10).
    • Begin with a random starting point and select every nth individual.

    Stratified Random Sampling

    • Best for heterogeneous populations with significant variability.
    • The population is divided into strata, and simple random samples are drawn from each to ensure representation.

    Multistage Random Sampling

    • Utilizes multiple stages for selection, ideal for entire communities (e.g., regions to households).
    • Each stage involves random sampling on different levels.

    Cluster Random Sampling

    • Effective for geographically dispersed populations.
    • Clusters may be formed by drawing samples from broader regions, then narrowing down to specific groups.

    Conclusion

    • Proper sampling techniques are vital in research to ensure that findings reflect the true characteristics of a population.

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    Description

    This quiz covers the essential concepts of sampling methods and sample size in research. It emphasizes the importance of selecting a representative sample from a population to effectively answer research questions. Understanding these fundamentals is crucial for conducting valid and reliable studies.

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