Sampling Methods in Statistics

What does a population in statistical studies refer to?

• A group of randomly selected individuals

• The entire group of individuals, objects, or events a researcher is studying

• A subset of individuals selected from a larger group

• The number of participants in a sample

What is a key characteristic of a sample?

• It always includes the entire population

• It should represent a small portion of the population

• It should accurately reflect the characteristics of the population

• It should be larger than the population

Why is sampling often preferred over studying the entire population?

• Sampling is more precise than population studies

• It saves time and resources

• Population studies have too many biases

• It is easier to control the results

Which of the following is NOT a benefit of a larger sample size?

• Reduced margin of error

• Increased statistical power

• More accurate point estimates

• Larger sampling error

Which sampling method ensures that every individual in the population has an equal chance of being selected?

• Stratified sampling

• Cluster sampling

• Random sampling

• Convenience sampling

What is the main disadvantage of convenience sampling?

• It is time-consuming

• It does not represent the population well

• It is complex to implement

• It increases the margin of error

What is the purpose of stratified sampling?

• To simplify the sampling process

• To ensure that different subgroups are properly represented

• To randomly select individuals from a population

• To select only a few clusters for sampling

Which of the following is true about systematic sampling?

• It selects individuals at random

• It selects individuals based on convenience

• It selects individuals at regular intervals from a list

• It selects entire clusters instead of individuals

What does a larger sample size reduce in statistical studies?

• Generalizability

• Sampling error

• Variability in the population

• The cost of the study

What is the main advantage of cluster sampling?

• Reduces bias

• Simplifies sampling for geographically dispersed populations

• Increases accuracy in small populations

• It ensures random selection of individuals