Podcast
Questions and Answers
What is a sample in the context of research?
What is a sample in the context of research?
Probability sampling methods involve random selection of individuals from a population.
Probability sampling methods involve random selection of individuals from a population.
True
What is the main purpose of stratified sampling?
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 ______.
In systematic sampling, researchers select members of the population at a regular ______.
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Match the probability sampling method with its description:
Match the probability sampling method with its description:
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What is sampling?
What is sampling?
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Define probability sampling.
Define probability sampling.
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Explain non-probability sampling.
Explain non-probability sampling.
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_______ sampling involves dividing the population into groups based on shared characteristics.
_______ sampling involves dividing the population into groups based on shared characteristics.
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Match the sampling method with its description:
Match the sampling method with its description:
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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.
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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
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Convenience Sampling: Select individuals who are most accessible to the researcher.
- Example: Surveying fellow students in classes.
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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.