Research Methods: Sampling and Population
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Questions and Answers

What is a sample in the context of research?

  • A random selection of individuals
  • A small portion chosen to represent a larger group (correct)
  • A representation of the entire population
  • A way of getting a numerical measurement
  • Probability sampling methods involve random selection of individuals from a population.

    True

    What is the main purpose of stratified sampling?

    To ensure diverse subgroups are represented in the sample

    In systematic sampling, researchers select members of the population at a regular ______.

    <p>interval</p> Signup and view all the answers

    Match the probability sampling method with its description:

    <p>Simple Random Sampling = Every sample has an equal probability of being chosen Stratified Sampling = Dividing population based on characteristics and sampling each subgroup Systematic Sampling = Selecting members at regular intervals Cluster Sampling = Selecting entire subgroups with similar characteristics</p> Signup and view all the answers

    What is sampling?

    <p>A way of selecting a subset of individuals from a larger population to study</p> Signup and view all the answers

    Define probability sampling.

    <p>Probability sampling involves random selection of individuals from a population.</p> Signup and view all the answers

    Explain non-probability sampling.

    <p>Non-probability sampling involves non-random selection based on convenience or other criteria.</p> Signup and view all the answers

    _______ sampling involves dividing the population into groups based on shared characteristics.

    <p>Stratified</p> Signup and view all the answers

    Match the sampling method with its description:

    <p>Simple Random Sampling = Randomly selecting individuals with equal probability Stratified Sampling = Dividing subjects into subgroups based on characteristics and sampling each subgroup Systematic Random Sampling = Selecting members at regular intervals from a population Cluster Sampling = Randomly selecting entire subgroups with similar characteristics</p> Signup and view all the answers

    Study Notes

    Sampling

    • Researchers use sampling to study a small portion of a large population to make estimates about the entire group.

    Types of Sampling

    • Probability Sampling: Involves random selection, where every individual has an equal chance of being chosen.
    • Non-Probability Sampling: Involves non-random selection, where not every individual has an equal chance of being chosen.

    Probability Sampling Methods

    • Simple Random Sampling: A basic method where each member of the population has an equal chance of being selected.
    • Stratified Sampling: Divide the population into subgroups (strata) based on shared characteristics, then randomly sample each subgroup.
      • Useful when the population has diverse subgroups that need to be represented.
    • Systematic Sampling: Select members of the population at a regular interval (e.g., every 15th person on a list).
    • Cluster Sampling: Divide the population into subgroups, then randomly select entire subgroups.

    Non-Probability Sampling Methods

    • Convenience Sampling: Select individuals who are most accessible to the researcher.
      • Example: Surveying fellow students in classes.
    • Voluntary Response Sampling: People volunteer to participate (e.g., responding to an online survey).
      • May not be representative of the entire population, as participants are self-selected.

    Sampling Methods

    • Researchers use sampling to study a smaller portion of a larger population, making it easier to conduct accurate studies.
    • Sampling allows researchers to make estimates of the larger population by studying characteristics of the small group.

    Types of Sampling Methods

    • Probability Sampling: involves random selection, where every individual has a chance of being included.
    • Non-Probability Sampling: involves non-random selection based on convenience or other criteria, where not every individual has a chance of being included.

    Probability Sampling Methods

    • Simple Random Sampling: each sample has an equal probability of being chosen, and each member of the subset carries an equal opportunity of being chosen.
    • Stratified Sampling: researchers divide subjects into subgroups based on characteristics, and then randomly sample each subgroup to ensure representation of all groups.
    • Systematic Sampling: researchers select members of the population at a regular interval, such as selecting every 15th person on a list.
    • Cluster Sampling: involves dividing the population into subgroups, and then randomly selecting entire subgroups instead of individuals.

    Non-Probability Sampling Methods

    • Convenience Sampling: includes individuals who are most accessible to the researcher, but may not be representative of the entire population.
    • Voluntary Response Sampling: people volunteer themselves, but may not be representative of the entire population, as they may have strong opinions on the topic.

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    Description

    Learn about the importance of sampling in research, how it helps study large populations, and its role in making estimates about the larger group.

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