Sampling Techniques

Summary

This video explains various sampling techniques used in research, divided into two main categories: probability and non-probability sampling. Probability sampling includes methods like simple random sampling, systematic sampling, stratified sampling, and cluster sampling, all based on random selection for quantitative research. Non-probability sampling includes snowball, convenience, purposive, and quota sampling, which are based on convenience or researcher judgment, typically used for qualitative research. The video emphasizes the importance of selecting the right sample size and participants to ensure accurate and representative research findings.

Takeaways

• 😀 Probability sampling involves random selection, allowing each member of the population to have a known chance of being selected.
• 😀 Non-probability sampling involves non-random selection, based on convenience or other criteria set by the researcher.
• 😀 Probability sampling is also known as statistical sampling, while non-probability sampling is referred to as non-statistical sampling.
• 😀 Simple random sampling gives every member of the population an equal chance of being selected, often using methods like drawing names or assigning numbers.
• 😀 Systematic sampling selects participants at regular intervals (e.g., every nth member), which ensures a structured approach to selection.
• 😀 Stratified sampling divides the population into subgroups (strata) based on shared characteristics, ensuring equal representation from each subgroup.
• 😀 In stratified sampling, the sample size from each subgroup can be proportional to its representation in the overall population.
• 😀 Cluster sampling divides the population into clusters, and participants are selected from these clusters. It can be a single-stage or two-stage process.
• 😀 Snowball sampling is a non-probability technique where participants nominate others to be part of the study, useful when hard-to-reach populations are involved.
• 😀 Convenience sampling selects participants based on availability and willingness, making it quick but potentially biased.
• 😀 Quota sampling ensures that a sample reflects the proportion of various characteristics within the population, helping to achieve specific research goals.

Q & A

What is the primary difference between probability and non-probability sampling techniques?

Probability sampling involves random selection, allowing each member of the population to have a known chance of being selected, while non-probability sampling involves non-random selection based on convenience or researcher-defined criteria.

What is an example of probability sampling?

An example of probability sampling is simple random sampling, where each member of the population has an equal chance of being selected, such as assigning numbers to participants and selecting randomly.

What is the main purpose of using probability sampling in research?

Probability sampling is primarily used in quantitative research to ensure statistical representation and minimize bias in the sample selection.

How is systematic sampling different from simple random sampling?

In systematic sampling, participants are selected at regular intervals from the population, while in simple random sampling, participants are chosen entirely at random, with each member having an equal chance.

What is stratified sampling used for, and how does it work?

Stratified sampling is used to ensure that subgroups of a population are represented proportionally. The population is divided into strata based on shared characteristics, and participants are randomly selected from each stratum.

How does cluster sampling differ from stratified sampling?

In cluster sampling, the population is divided into clusters, and either all members of selected clusters or a random sample from those clusters are chosen. Stratified sampling, on the other hand, ensures proportional representation from different subgroups or strata.

What is the snowball sampling technique and when is it used?

Snowball sampling is a non-probability technique where initial participants nominate other participants who meet the criteria for the study. It is often used when participants are difficult to identify or when the population is hidden.

What is the main advantage of convenience sampling?

The main advantage of convenience sampling is that it is easy to implement and inexpensive, as participants are selected based on their availability and willingness to participate.

How does quota sampling ensure that the sample reflects the population?

Quota sampling ensures that the sample reflects specific characteristics of the population by setting quotas for different groups based on predefined criteria. The researcher continues to collect data until the quotas are met.

Why is purposive sampling often used in qualitative research?

Purposive sampling is used in qualitative research to select participants based on specific criteria relevant to the study, ensuring that the participants can provide detailed and relevant information for the research.