Question
match the following sample methods
1. Simple random sampling 2.stratified sampling 3. systematic sampling 4. cluster sampling
A type of sampling in which every kth unit in a list is selected for inclusion in the sample—for example, every 25th student in the college directory of students. You compute k by dividing the size of the population by the desired sample size; k is called the sampling interval. Typically, the first unit is selected at random. A type of sampling in which units are selected for a sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied. A type of sampling involving the grouping of the units composing a population into homogeneous groups before sampling. This procedure improves the representativeness of a sample.
A type of sampling in which the units composing a population are assigned numbers. A set of random numbers is then generated, and the units having those numbers are included in the sample.
A sampling method, often employed in field research, whereby each person interviewed may be asked to suggest additional people for interviewing. A type of sampling in which the units to be observed are selected on the basis of the researcher’s judgment about which ones will be the most useful or representative.
1. Simple random sampling 2.stratified sampling 3. systematic sampling 4. cluster sampling
A type of sampling in which every kth unit in a list is selected for inclusion in the sample—for example, every 25th student in the college directory of students. You compute k by dividing the size of the population by the desired sample size; k is called the sampling interval. Typically, the first unit is selected at random. A type of sampling in which units are selected for a sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied. A type of sampling involving the grouping of the units composing a population into homogeneous groups before sampling. This procedure improves the representativeness of a sample.
A type of sampling in which the units composing a population are assigned numbers. A set of random numbers is then generated, and the units having those numbers are included in the sample.
A sampling method, often employed in field research, whereby each person interviewed may be asked to suggest additional people for interviewing. A type of sampling in which the units to be observed are selected on the basis of the researcher’s judgment about which ones will be the most useful or representative.
Answers
GPT-4o mini
Let's match the sample methods with their descriptions.
1. **Simple random sampling**: A type of sampling in which the units composing a population are assigned numbers. A set of random numbers is then generated, and the units having those numbers are included in the sample.
2. **Stratified sampling**: A type of sampling in which units are selected for a sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied.
3. **Systematic sampling**: A type of sampling in which every kth unit in a list is selected for inclusion in the sample—for example, every 25th student in the college directory of students. You compute k by dividing the size of the population by the desired sample size; k is called the sampling interval. Typically, the first unit is selected at random.
4. **Cluster sampling**: A type of sampling involving the grouping of the units composing a population into homogeneous groups before sampling. This procedure improves the representativeness of a sample.
The last two definitions mentioned (a sampling method employing field research and a sampling method based on the researcher’s judgment) do not match the traditional definitions provided for the listed sampling methods. These would be more aligned with **snowball sampling** (for the suggestion of additional people) and **purposive sampling** (for judgment-based sampling), which were not in the original list of methods you provided.
1. **Simple random sampling**: A type of sampling in which the units composing a population are assigned numbers. A set of random numbers is then generated, and the units having those numbers are included in the sample.
2. **Stratified sampling**: A type of sampling in which units are selected for a sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied.
3. **Systematic sampling**: A type of sampling in which every kth unit in a list is selected for inclusion in the sample—for example, every 25th student in the college directory of students. You compute k by dividing the size of the population by the desired sample size; k is called the sampling interval. Typically, the first unit is selected at random.
4. **Cluster sampling**: A type of sampling involving the grouping of the units composing a population into homogeneous groups before sampling. This procedure improves the representativeness of a sample.
The last two definitions mentioned (a sampling method employing field research and a sampling method based on the researcher’s judgment) do not match the traditional definitions provided for the listed sampling methods. These would be more aligned with **snowball sampling** (for the suggestion of additional people) and **purposive sampling** (for judgment-based sampling), which were not in the original list of methods you provided.