Question 1

What is not true about population sampling?&#10;A) Sampling technique will vary depending on the type of study.&#10;B) A relatively small sample size can still represent a population.&#10;C) It always accurately portrays the population.&#10;D) It can be used to make predictions about the population.

Accepted Answer

Sampling does not always accurately portray the population due to potential biases or errors in the sampling process.

Question 2

Generalizability means:&#10;A) conclusions made about one population can be applied to another.&#10;B) the study could not be specific about its conclusions.&#10;C) how well the sample represents the population it is taken from.&#10;D) None of these is correct.

Accepted Answer

C

Question 3

The strength or weakness of the generalizability yield can only be determined by what sampling method was used on the population.

Accepted Answer

The generalizability of a study's findings depends on the representativeness of the sample to the population. The sampling method used determines how well the sample represents the population, and thus the strength or weakness of the generalizability.

Question 4

What is not factored in a sampling frame?&#10;A) People&#10;B) Health departments&#10;C) Schools&#10;D) The health disparity

Accepted Answer

A sampling frame includes entities like people, health departments, and schools, but health disparity is a characteristic or outcome, not an entity to be included in a sampling frame.

Question 5

Simple random sampling is not:&#10;A) highly representative of the population.&#10;B) unbiased.&#10;C) very common.&#10;D) a probability sampling technique.

Accepted Answer

The answer of Simple random sampling is not:&#10;A) highly representative...

Question 6

Why would it benefit you to use systematic random sampling over simple random sampling?&#10;A) It could account for a pattern or sequence in your sampling that introduces a bias.&#10;B) It ensures that an element has a chance of not being selected.&#10;C) You know how to integrate a quotient into your sampling interval.&#10;D) It has a higher generalizability yield.

Accepted Answer

Systematic random sampling can help account for patterns or sequences in the population that might introduce bias, as it involves selecting samples at regular intervals, which can help ensure a more evenly distributed sample across the population.

Question 7

If selection sampling occurs proportionately in a study, it loses its randomness and can no longer be considered probability sampling.

Accepted Answer

Proportionate selection sampling can still be random and considered probability sampling if each member of the population has a known and equal chance of being selected.

Question 8

Multistage cluster sampling allows you to:&#10;A) group people into units or entities into clusters.&#10;B) maintain a sampling method that is still random.&#10;C) create as many stages as you deem necessary.&#10;D) All of these are correct.

Accepted Answer

Multistage cluster sampling involves grouping entities into clusters, maintaining randomness, and allowing for multiple stages in the sampling process.

Question 9

If you're allowed to sample pre-existing groups and exclude certain members from your pre-existing groups, and it is a form of nonprobability sampling, you are using:&#10;A) convenience sampling.&#10;B) purposive sampling.&#10;C) quota sampling.&#10;D) snowball sampling.

Accepted Answer

Purposive sampling involves selecting specific groups or individuals deliberately based on the purpose of the study, allowing for the exclusion of certain members, and is a form of nonprobability sampling.

Question 10

What is a reason why you would not use nonprobability sampling over probability sampling?&#10;A) You're interested in an immediate population.&#10;B) Your study includes a &#34;hidden&#34; population for which no sampling frame existed.&#10;C) You want to test an intervention for its internal validity.&#10;D) Specific demographic factors were necessary components to your research question's representativeness.

Accepted Answer

Probability sampling is preferred for testing internal validity because it allows for random selection, reducing bias and ensuring that the sample is representative of the population, which is crucial for establishing causal relationships.

Deck 10: Sampling Techniques