Sampling Methods

Question 1

What is the difference between simple random sampling and systematic sampling?

Answer 1

Simple random sampling involves selecting subjects purely by chance, while systematic sampling selects every nth item in a list.

Question 2

How do you perform stratified sampling?

Answer 2

Stratified sampling involves dividing the population into strata and sampling from each stratum proportionally or equally.

Question 3

What is cluster sampling, and when is it used?

Answer 3

Cluster sampling groups subjects into clusters and randomly selects entire clusters, used for efficiency in large populations.

Question 4

Explain the concept of multistage sampling.

Answer 4

Multistage sampling involves multiple levels of sampling, such as selecting clusters first and then subjects within those clusters.

Question 5

What are the advantages of using probability sampling methods?

Answer 5

Probability sampling methods ensure that every member of the population has a known and non-zero chance of being selected.

Question 6

What is non-probability sampling, and when might it be used?

Answer 6

Non-probability sampling does not give all members of a population a chance to be included and is used when probability sampling is not possible.

Question 7

How do you calculate the sample size for a survey?

Answer 7

Sample size is calculated based on the desired level of precision, confidence level, and the variability in the population.

Question 8

What are the potential biases in convenience sampling?

Answer 8

Convenience sampling can lead to underrepresentation or overrepresentation of particular groups within the sample.

Question 9

How does purposive sampling differ from random sampling?

Answer 9

Purposive sampling involves selecting subjects based on specific characteristics, differing from random sampling which does not consider the characteristics of the subjects.

Question 10

What is snowball sampling, and in what types of research is it useful?

Answer 10

Snowball sampling involves existing study subjects recruiting future subjects from among their acquaintances, useful in hard-to-reach populations.

Question 11

Why is sampling important in research?

Answer 11

Sampling allows researchers to make inferences about a larger population without needing to survey everyone.

Question 12

What methods can be used to ensure representativeness in a sample?

Answer 12

Representativeness can be ensured by using random sampling methods and by stratifying the sample to reflect population characteristics.

Question 13

How can sampling error be minimized?

Answer 13

Sampling error can be minimized by increasing the sample size and using efficient sampling techniques.

Question 14

What is quota sampling, and how does it work?

Answer 14

Quota sampling involves selecting people to meet certain quotas on characteristics, ensuring the sample reflects certain features of the population.

Question 15

What role does sampling frame play in sampling?

Answer 15

The sampling frame is a list from which the sample is drawn, and its quality can significantly affect the sample’s accuracy.

Question 16

How do you handle non-response in surveys?

Answer 16

Non-response can be handled by follow-ups, incentives, and adjusting the weights in the analysis to account for the missing responses.

Question 17

What is the impact of sample size on survey accuracy?

Answer 17

A larger sample size generally increases the accuracy of survey results, reducing the margin of error.

Question 18

How do you determine the appropriate sampling technique for a study?

Answer 18

The appropriate technique depends on the research objectives, population structure, and resource constraints.

Question 19

What is judgment sampling, and how is it performed?

Answer 19

Judgment sampling selects subjects based on the judgment of the researcher, who uses their expertise to pick representative participants.

Question 20

What are the ethical considerations in sampling?

Answer 20

Ethical considerations include ensuring fairness in selection, respecting privacy, and avoiding harm to participants.

Question 21

Why is random digit dialing considered a probability sampling method?

Answer 21

Random digit dialing gives each phone number in the target population an equal chance of being selected.

Question 22

What is theoretical sampling in qualitative research?

Answer 22

Theoretical sampling involves selecting cases that can help the researcher develop and refine their theories, typical in grounded theory research.

Question 23

How does sample size affect the generalizability of study findings?

Answer 23

A larger sample size can enhance the generalizability, allowing more confident extrapolations to the whole population.

Question 24

What are the challenges associated with sampling in qualitative research?

Answer 24

Qualitative sampling challenges include ensuring depth and breadth in data while managing resource constraints.

Question 25

How do you avoid bias in random sampling?

Answer 25

Bias in random sampling can be avoided by ensuring each individual has an equal chance of selection and by using appropriate randomization methods.

Question 26

What is the difference between sampling and census?

Answer 26

Sampling involves studying a portion of the population, whereas a census attempts to include every member.

Question 27

Why is oversampling used, and how can it impact results?

Answer 27

Oversampling targets specific, often smaller, groups to ensure adequate representation, which can affect the weighting of results.

Question 28

What is respondent-driven sampling?

Answer 28

Respondent-driven sampling lets sampled subjects recruit others, useful for reaching specific, often hidden populations.

Question 29

How does the law of large numbers apply to sampling?

Answer 29

The law of large numbers states that as a sample size increases, the sample mean gets closer to the population mean.

Question 30

How do you validate the reliability of a sample?

Answer 30

Reliability can be validated through consistency checks and replication studies.

Question 31

How do you use sampling weights in analysis?

Answer 31

Sampling weights adjust the influence of observations to reflect their proportion in the total population.

Question 32

What is the importance of sample diversity in research studies?

Answer 32

Sample diversity ensures that the results are applicable to all segments of the population, enhancing the study’s external validity.

Question 33

What are the risks of under-sampling certain groups in population studies?

Answer 33

Under-sampling can lead to biased results and a lack of insight into the affected groups’ characteristics and needs.

Question 34

How do you ensure ethical transparency in the sampling process?

Answer 34

Ethical transparency involves clearly communicating the sampling process, criteria, and any compensation to participants.

Question 35

What are the common sampling techniques used in market research?

Answer 35

Common techniques include random sampling, stratified sampling, and cluster sampling, depending on the research goals and population.

Question 36

How does the selection of a sampling method affect data quality?

Answer 36

The choice of sampling method directly impacts the representativeness and reliability of the collected data.

Question 37

What is the importance of pilot testing in sampling design?

Answer 37

Pilot testing helps identify potential problems in the sampling framework and data collection methods before the full-scale study.

Question 38

How do researchers deal with sampling bias?

Answer 38

Sampling bias is addressed by carefully designing the sampling procedure and frequently reviewing and adjusting the methodology as necessary.

Question 39

What are the implications of a high variance in sample estimates?

Answer 39

High variance indicates that the results are spread out over a wide range, which can complicate drawing firm conclusions.

Question 40

What strategies can researchers use to increase response rates in surveys?

Answer 40

Increasing response rates can be achieved through follow-ups, simplifying survey processes, and providing incentives to participants.