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Which type of sampling method involves selecting population members based on the researcher's judgment?
- a)Snowball Sampling
- b)Cluster Sampling
- c)Non-probability Sampling
- d)Probability Sampling
Correct answer is option 'C'. Can you explain this answer?
Verified Answer
Which type of sampling method involves selecting population members ba...
Judgment Sampling is a type of non-probability sampling method where the researcher uses their judgment to select population members who are likely to provide accurate information. This method is commonly used in historical or descriptive research where the researcher's expertise plays a significant role in selecting the sample.
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Which type of sampling method involves selecting population members ba...
Non-probability Sampling:
Non-probability sampling methods involve selecting population members based on the researcher's judgment rather than random selection. This type of sampling does not guarantee that every individual in the population has an equal chance of being chosen.
Snowball Sampling:
Snowball sampling is a type of non-probability sampling where existing study subjects recruit future subjects from among their acquaintances. This method is often used when the population of interest is hard to reach or identify.
Cluster Sampling:
Cluster sampling is a probability sampling method where the population is divided into clusters, and a simple random sample of clusters is selected. This method differs from non-probability sampling as it ensures that every cluster has an equal chance of being selected.
In conclusion, non-probability sampling, including snowball sampling and cluster sampling, involves selecting population members based on the researcher's judgment rather than random selection. This method may be used when it is difficult or impossible to obtain a random sample, but researchers should be cautious of potential biases that could arise from non-probability sampling.
Non-probability sampling methods involve selecting population members based on the researcher's judgment rather than random selection. This type of sampling does not guarantee that every individual in the population has an equal chance of being chosen.
Snowball Sampling:
Snowball sampling is a type of non-probability sampling where existing study subjects recruit future subjects from among their acquaintances. This method is often used when the population of interest is hard to reach or identify.
Cluster Sampling:
Cluster sampling is a probability sampling method where the population is divided into clusters, and a simple random sample of clusters is selected. This method differs from non-probability sampling as it ensures that every cluster has an equal chance of being selected.
In conclusion, non-probability sampling, including snowball sampling and cluster sampling, involves selecting population members based on the researcher's judgment rather than random selection. This method may be used when it is difficult or impossible to obtain a random sample, but researchers should be cautious of potential biases that could arise from non-probability sampling.
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