Sampling Methods Quiz

What is the difference between a population and a sample?

• A population is a part of a sample.

• A population is the entire group of interest, while a sample is a subset of that population.

• A sample includes everyone in a population.

• A sample is larger than a population.

Which of the following is a type of probability sampling?

• Convenience sampling

• Snowball sampling

• Stratified sampling

• Judgmental sampling

Which of the following is a reason for sampling?

• To eliminate all errors

• To save time and resources

• To ensure bias in data collection

• To avoid statistical analysis

Which sampling method involves dividing the population into strata and randomly sampling from each stratum?

• Systematic sampling

• Stratified sampling

• Cluster sampling

• Convenience sampling

What is Slovin's formula used for?

• To calculate the margin of error

• To determine the sample size

• To select systematic samples

• To conduct hypothesis testing

Which of the following is an example of non-probability sampling?

• Simple random sampling

• Systematic sampling

• Snowball sampling

• Stratified sampling

In cluster sampling, how are samples selected?

• By selecting every kth individual from a list

• By dividing the population into clusters and randomly selecting entire clusters

• By selecting individuals based on their availability

• By selecting a simple random sample from each subgroup

What is a key feature of probability sampling?

• Samples are selected based on judgment

• Every member of the population has a known, non-zero chance of being selected

• Samples are chosen because they are easy to access

• Sampling is done without any randomization

Which of the following is true about sampling error?

• It can be completely eliminated with a large enough sample

• It occurs because we observe a sample instead of the full population

• It is unrelated to the size of the sample

• It is a type of non-sampling error

What is the role of a sample statistic?

• To describe a characteristic of the entire population

• To estimate a parameter of the population

• To represent the whole population without bias

• To ensure the entire population is studied