New - Ch 7 (NoteLM)

Question 1

Population

Answer 1

The entire group of individuals or objects that a researcher is interested in studying

Question 2

Sample

Answer 2

A subset of individuals or objects selected from the population to represent the whole

Question 3

Census

Answer 3

A study that includes data from every member of the population.

Question 4

Population of Interest

Answer 4

The specific population to which the researcher wants to generalize their findings.

Question 5

Generalizability

Answer 5

The extent to which findings from a sample can be applied to the population of interest

Question 6

Biased Sample
(Unrepresentative Sample)

Answer 6

A sample that does not accurately reflect the characteristics of the population of interest.

Question 7

Unbiased Sample

(Representative Sample)

Answer 7

A sample that accurately reflects the characteristics of the population of interest

Question 8

Probability Sampling

(Random Sampling)

Answer 8

A sampling method where every member of the population has an equal and known chance of being selected.

Question 9

Nonprobability Sampling

(Non-random Sampling)

Answer 9

A sampling method where not every member of the population has an equal chance of being selected, leading to potential bias.

Question 10

Simple Random Sampling

Answer 10

A probability sampling method where each individual is randomly selected from the population

Question 11

Systematic Sampling

Answer 11

A probability sampling method where individuals are selected at regular intervals from a list of the population.

Question 12

Cluster Sampling

Answer 12

A probability sampling method where the population is divided into clusters, and some clusters are randomly selected to represent the whole.

Question 13

Multistage Sampling

Answer 13

A probability sampling method that involves selecting a sample in stages, with each stage involving random sampling from the previous stage.

Question 14

Stratified Random Sampling

Answer 14

A probability sampling method where the population is divided into subgroups (strata) based on shared characteristics, and a random sample is drawn from each stratum.

Question 15

Oversampling

Answer 15

A sampling technique where a specific subgroup is intentionally overrepresented in the sample to ensure adequate data is collected from that group.

Question 16

Convenience Sampling

Answer 16

A nonprobability sampling method where individuals are selected based on their easy availability.

Question 17

Purposive Sampling

Answer 17

A nonprobability sampling method where researchers select participants based on their specific knowledge or characteristics.

Question 18

Snowball Sampling

Answer 18

A nonprobability sampling method where existing participants recruit future participants from their own networks.

Question 19

Quota Sampling

Answer 19

A nonprobability sampling method where researchers set quotas for different subgroups in their sample to ensure representation.

Question 20

Margin of Error

Answer 20

A statistic expressing the amount of random sampling error in the results of a survey.

Question 21

Differentiate between a sample and a population.

Answer 21

A population refers to the entire group of interest in a study, while a sample is a smaller, representative subset selected from that population.

Question 22

What is the key difference between probability sampling and nonprobability sampling?

Answer 22

Probability sampling uses random selection, giving every member of the population an equal chance of inclusion, while nonprobability sampling does not, potentially leading to biased samples.

Question 23

Describe two advantages of using stratified random sampling.

Answer 23

Stratified random sampling ensures representation from key subgroups and allows for comparisons between these subgroups.

Question 24

Why is convenience sampling generally considered a weaker sampling method than random sampling?

Answer 24

Convenience sampling often leads to biased samples because it does not use random selection and tends to overrepresent easily accessible individuals.

Question 25

Explain how oversampling can be useful in research, even though it creates a non-representative sample.

Answer 25

Oversampling a small or underrepresented group helps to gather sufficient data from that group for analysis, even if it means the sample is not perfectly representative of the overall population.

Question 26

What is the difference between cluster sampling and multistage sampling?

Answer 26

Cluster sampling involves randomly selecting entire groups (clusters), while multistage sampling involves random selection at multiple stages, potentially sampling both clusters and individuals.

Question 27

Why is a large sample size not always a guarantee of generalizability?

Answer 27

A large sample size does not guarantee generalizability if the sample is not representative of the population of interest. A large, biased sample is still biased.

Question 28

Describe a research scenario where purposive sampling would be an appropriate method.

Answer 28

Purposive sampling would be appropriate when studying a specific group with unique expertise or experiences, such as cancer survivors or expert chess players.

Question 29

What is the relationship between sample size and margin of error?

Answer 29

As sample size increases, the margin of error decreases, meaning that larger samples tend to provide more precise estimates of population parameters.

Question 30

A researcher wants to study the political attitudes of college students in the United States. Describe a sampling method that would be likely to produce a representative sample for this study.

Answer 30

A stratified random sampling approach could be used, where the researcher first stratifies by college type (e.g., 2-year, 4-year), then randomly selects students within each strata to ensure representation from different college types.