Types of Sampling and Qualitative Sampling Methods: 46 MCQs with answers

Selecting a small group from a larger population

Sampling is the process of selecting a small group (sample) from a larger group (population) to study and draw conclusions about the whole.

A known, non-zero chance of being selected

Probability sampling requires that every member has a known, non-zero chance of selection, which makes the sample representative.

Systematic sampling

Systematic sampling selects every $k$-th item, where $k = \text{population} / \text{sample size}$.

Convenience sampling

Convenience sampling picks whoever is easiest to reach. It is quick but biased.

Depth, meaning, and rich understanding

Qualitative research aims for depth and meaning, not statistical generalisation. Samples are small but information-rich.

True

In **stratified sampling**, the sample size from each stratum is proportional: $n_h = n \times \frac{N_h}{N}$, where $N_h$ is the stratum size and $N$ is the population size.

Selecting a small group from a larger population.

The correct option defines sampling as the process of selecting a small group from a larger population to study.

Every member has a known chance of selection.

Probability sampling ensures that every member of the population has a known chance of being selected, making it representative.

To choose participants who meet specific criteria.

Purposive sampling is used to deliberately select participants who fit specific criteria relevant to the research.

Participants referring other participants.

Snowball sampling involves existing participants referring new participants, making it useful for reaching hidden populations.

Systematic sampling

Systematic sampling is characterized by selecting every k-th individual from a list, ensuring a structured approach.

To understand depth and meaning.

Qualitative research sampling aims to understand depth and meaning rather than generalizing findings.

Stratified sampling

Stratified sampling involves dividing the population into strata and sampling from each to ensure representation.

It selects participants who are easiest to reach.

Convenience sampling selects participants who are easiest to reach, making it quick but potentially biased.

Extreme/deviant case sampling

Extreme/deviant case sampling focuses on studying unusual cases to gain insights into their unique characteristics.

Stratified sampling takes some from every group.

Stratified sampling takes some individuals from every group, while cluster sampling takes everyone from a few selected groups.

Stratified sampling

Stratified sampling divides the population into strata (groups) and randomly samples from each stratum.

Cluster sampling

Cluster sampling randomly selects whole clusters and studies everyone inside them. Stratified takes some from every group; cluster takes all from some groups.

Theoretical sampling

Theoretical sampling is unique to grounded theory — data collection and analysis happen simultaneously, and emerging theory decides who to sample next.

Purposive sampling

Purposive sampling deliberately chooses participants who fit the research purpose — here, people who can tell the richest story about grief.

Cluster sampling — probability sampling

Cluster sampling is a probability method. Snowball, quota, and purposive are non-probability methods; stratified is probability.

Purposive sampling

Purposive sampling is designed to select participants who meet specific criteria, making it suitable for qualitative research.

Systematic sampling

Systematic sampling involves selecting every k-th person from a list, ensuring a structured approach to sampling.

To understand depth and meaning

Qualitative sampling focuses on understanding depth and meaning rather than generalizing to a population.

Stratified sampling takes some from all groups, while cluster sampling takes all from some groups.

Stratified sampling involves taking a sample from every group, while cluster sampling involves taking a sample from entire groups.

It is based on the researcher's judgment and ease of access.

Convenience sampling is characterized by selecting participants based on their availability and ease of access, not random selection.

Snowball sampling

Snowball sampling is effective for reaching hidden populations as existing participants can refer others within their networks.

It is based on the proportion of each stratum in the population.

In stratified sampling, the sample size from each stratum is determined proportionally based on the size of the stratum relative to the total population.

Theoretical sampling

Theoretical sampling is used in grounded theory to select participants based on data analysis and emerging theories.

It allows for statistical generalization to the population.

Probability sampling allows for statistical generalization because every member of the population has a known chance of being selected.

Quota sampling

Quota sampling involves pre-determining the number of participants from each category to ensure representation of specific groups.

60

Using $n_h = n \times \frac{N_h}{N}$: arts gets $100 \times \frac{600}{1000} = 60$ students.

Maximum variation sampling

Maximum variation sampling deliberately chooses very different cases to capture the full range of experience.

Extreme/deviant case sampling

Extreme/deviant case sampling studies unusual cases to learn what makes them different from the norm.

Snowball sampling

Snowball sampling uses existing participants to refer new ones, making it ideal for hidden or hard-to-reach populations.

Probability sampling, for generalisation

Counting questions need probability sampling for a trustworthy number that can be generalised to the population.

Maximum variation sampling

Maximum variation sampling is designed to include a diverse range of cases to capture the full spectrum of experiences, making it ideal for studying socioeconomic diversity.

Cluster sampling

Cluster sampling involves selecting entire groups (clusters) and studying all individuals within those groups, which aligns with the described approach.

Purposive sampling

Purposive sampling is used to select participants who meet specific criteria relevant to the research question, making it suitable for in-depth qualitative studies.

Theoretical sampling

Theoretical sampling is a hallmark of grounded theory, where sampling decisions are made based on the analysis of data to refine emerging theories.

Quota sampling

Quota sampling involves setting specific quotas for different groups within the population, ensuring representation of each group in the sample.

Purposive sampling

Purposive sampling is used here as the researcher selects participants based on their specific characteristics related to the research question.

Snowball sampling

Snowball sampling is characterized by existing participants referring new participants, which is effective for reaching hidden populations.

Systematic sampling

Systematic sampling involves selecting every k-th individual from a list, which is exactly what the researcher is doing.

Maximum variation sampling

Maximum variation sampling aims to capture a wide range of experiences by deliberately selecting diverse cases, such as urban and rural students.

Convenience sampling

Convenience sampling involves selecting participants based on their availability and ease of access, which is what the researcher is doing.