The methods of sampling in social research primarily fall into two broad categories: probability sampling and non-probability sampling.
Probability Sampling
Probability sampling, also known as random sampling, uses random selection to ensure that each member of the population has a known, non-zero chance of being selected for the sample. This allows researchers to generalize the findings from the sample to the larger population with a certain degree of confidence. Types of probability sampling include:
- Simple Random Sampling: Every member of the population has an equal chance of being selected. This can be done using a random number generator or drawing names from a hat.
- Systematic Sampling: Selecting members of the population at regular intervals (e.g., every 10th person on a list). The starting point is usually selected randomly.
- Stratified Sampling: Dividing the population into subgroups (strata) based on shared characteristics (e.g., age, gender, education) and then randomly sampling from each stratum. This ensures representation from all subgroups.
- Cluster Sampling: Dividing the population into clusters (e.g., schools, neighborhoods) and then randomly selecting entire clusters to be included in the sample. This is often used when the population is geographically dispersed.
- Multi-Stage Sampling: Combining two or more of the above methods. For example, researchers might first use cluster sampling to select schools and then use simple random sampling to select students within those schools.
Non-Probability Sampling
Non-probability sampling techniques do not rely on random selection. This means that not every member of the population has a known chance of being selected, and it is more difficult to generalize findings to the larger population. However, non-probability sampling can be useful in situations where it is not feasible or necessary to use probability sampling. Types of non-probability sampling include:
- Convenience Sampling: Selecting participants who are easily accessible (e.g., students in a class, people on the street).
- Purposive Sampling: Selecting participants based on specific criteria or characteristics that are relevant to the research question.
- Quota Sampling: Similar to stratified sampling, but participants are not randomly selected from each stratum. Instead, researchers aim to recruit a specific number (quota) of participants from each stratum.
- Snowball Sampling: Using existing participants to recruit additional participants (e.g., asking participants to refer friends or family members who meet the study criteria). This is often used when studying hard-to-reach populations.
In summary, probability sampling methods allow for generalization to a broader population due to their random selection process, whereas non-probability sampling methods are used when generalizability is not a primary concern or when random selection is not feasible.
