Sampling Methods Flashcards
What is the difference between simple random sampling and systematic sampling?
Simple random sampling involves selecting subjects purely by chance, while systematic sampling selects every nth item in a list.
How do you perform stratified sampling?
Stratified sampling involves dividing the population into strata and sampling from each stratum proportionally or equally.
What is cluster sampling, and when is it used?
Cluster sampling groups subjects into clusters and randomly selects entire clusters, used for efficiency in large populations.
Explain the concept of multistage sampling.
Multistage sampling involves multiple levels of sampling, such as selecting clusters first and then subjects within those clusters.
What are the advantages of using probability sampling methods?
Probability sampling methods ensure that every member of the population has a known and non-zero chance of being selected.
What is non-probability sampling, and when might it be used?
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.
How do you calculate the sample size for a survey?
Sample size is calculated based on the desired level of precision, confidence level, and the variability in the population.
What are the potential biases in convenience sampling?
Convenience sampling can lead to underrepresentation or overrepresentation of particular groups within the sample.
How does purposive sampling differ from random sampling?
Purposive sampling involves selecting subjects based on specific characteristics, differing from random sampling which does not consider the characteristics of the subjects.
What is snowball sampling, and in what types of research is it useful?
Snowball sampling involves existing study subjects recruiting future subjects from among their acquaintances, useful in hard-to-reach populations.
Why is sampling important in research?
Sampling allows researchers to make inferences about a larger population without needing to survey everyone.
What methods can be used to ensure representativeness in a sample?
Representativeness can be ensured by using random sampling methods and by stratifying the sample to reflect population characteristics.
How can sampling error be minimized?
Sampling error can be minimized by increasing the sample size and using efficient sampling techniques.
What is quota sampling, and how does it work?
Quota sampling involves selecting people to meet certain quotas on characteristics, ensuring the sample reflects certain features of the population.
What role does sampling frame play in sampling?
The sampling frame is a list from which the sample is drawn, and its quality can significantly affect the sample’s accuracy.
How do you handle non-response in surveys?
Non-response can be handled by follow-ups, incentives, and adjusting the weights in the analysis to account for the missing responses.
What is the impact of sample size on survey accuracy?
A larger sample size generally increases the accuracy of survey results, reducing the margin of error.
How do you determine the appropriate sampling technique for a study?
The appropriate technique depends on the research objectives, population structure, and resource constraints.
What is judgment sampling, and how is it performed?
Judgment sampling selects subjects based on the judgment of the researcher, who uses their expertise to pick representative participants.
What are the ethical considerations in sampling?
Ethical considerations include ensuring fairness in selection, respecting privacy, and avoiding harm to participants.
Why is random digit dialing considered a probability sampling method?
Random digit dialing gives each phone number in the target population an equal chance of being selected.
What is theoretical sampling in qualitative research?
Theoretical sampling involves selecting cases that can help the researcher develop and refine their theories, typical in grounded theory research.
How does sample size affect the generalizability of study findings?
A larger sample size can enhance the generalizability, allowing more confident extrapolations to the whole population.
What are the challenges associated with sampling in qualitative research?
Qualitative sampling challenges include ensuring depth and breadth in data while managing resource constraints.
How do you avoid bias in random sampling?
Bias in random sampling can be avoided by ensuring each individual has an equal chance of selection and by using appropriate randomization methods.
What is the difference between sampling and census?
Sampling involves studying a portion of the population, whereas a census attempts to include every member.
Why is oversampling used, and how can it impact results?
Oversampling targets specific, often smaller, groups to ensure adequate representation, which can affect the weighting of results.
What is respondent-driven sampling?
Respondent-driven sampling lets sampled subjects recruit others, useful for reaching specific, often hidden populations.
How does the law of large numbers apply to sampling?
The law of large numbers states that as a sample size increases, the sample mean gets closer to the population mean.
How do you validate the reliability of a sample?
Reliability can be validated through consistency checks and replication studies.
How do you use sampling weights in analysis?
Sampling weights adjust the influence of observations to reflect their proportion in the total population.
What is the importance of sample diversity in research studies?
Sample diversity ensures that the results are applicable to all segments of the population, enhancing the study’s external validity.
What are the risks of under-sampling certain groups in population studies?
Under-sampling can lead to biased results and a lack of insight into the affected groups’ characteristics and needs.
How do you ensure ethical transparency in the sampling process?
Ethical transparency involves clearly communicating the sampling process, criteria, and any compensation to participants.
What are the common sampling techniques used in market research?
Common techniques include random sampling, stratified sampling, and cluster sampling, depending on the research goals and population.
How does the selection of a sampling method affect data quality?
The choice of sampling method directly impacts the representativeness and reliability of the collected data.
What is the importance of pilot testing in sampling design?
Pilot testing helps identify potential problems in the sampling framework and data collection methods before the full-scale study.
How do researchers deal with sampling bias?
Sampling bias is addressed by carefully designing the sampling procedure and frequently reviewing and adjusting the methodology as necessary.
What are the implications of a high variance in sample estimates?
High variance indicates that the results are spread out over a wide range, which can complicate drawing firm conclusions.
What strategies can researchers use to increase response rates in surveys?
Increasing response rates can be achieved through follow-ups, simplifying survey processes, and providing incentives to participants.
