Different Sampling Procedures (PR1)

In research, what does the term "sampling" primarily refer to?

• analysis of collected data

• method of selecting participants for a study

• development of research questions

• writing of the research report

In research, what do you call the larger group from which a sample is selected?

• Sample group

• Control group

• Population

• Variable

The term "sampling frame" refers to ________________.

• the method used to analyze the collected data

• the list of individuals from which a sample is drawn

• the overall research design of the study

• the conclusions drawn from the research findings.

In probability sampling, what is TRUE about the members of the sampling frame?

• They have an unequal chance of being selected.

• They are not representative of the population.

• They all have an equal chance of being selected.

• They are randomly chosen from a larger, unlisted population.

In Research, when does sampling error occur?

• The data analysis is flawed.

• The sample is perfectly representative of the population.

• The sample selection deviates from the planned method.

• The research questions are poorly defined.

In simple random sampling, each member of the population has ___________.

• no chance of being selected.

• an unequal chance of being selected.

• an equal chance of being selected.

• a predetermined chance of being selected.

Which of the following statements BEST describes "systematic random sampling"?

• Every member of the population is selected.

• Participants are selected based on convenience.

• Every n^th member of the population is selected after a random starting point.

• The population is divided into strata before sampling.

Stratified sampling involves __________________.

• selecting every nth person from a list.

• dividing the population into subgroups and then randomly sampling from each subgroup.

• selecting participants based on convenience.

• randomly selecting participants from the entire population without regard to subgroups.

What is a key difference between cluster sampling and stratified sampling?

• Cluster sampling is only used for large populations.

• Cluster sampling involves dividing the population into subgroups based on characteristics.

• Cluster sampling is less efficient than stratified sampling.

• Cluster sampling selects entire subgroups (clusters) for sampling, while stratified sampling selects individuals from each subgroup.

A key characteristic of non-probability sampling is that:

• it employs random selection of participants.

• it guarantees a representative sample of the population.

• every member of the population has a known chance of selection.

• participants are selected based on availability or researcher judgment.