Quantitative Methods Questions
There are several different sampling techniques used in quantitative research. Some of the most common ones include:
1. Simple random sampling: This technique involves selecting a sample from a population in such a way that each individual has an equal chance of being chosen.
2. Stratified sampling: In this technique, the population is divided into different subgroups or strata, and then a random sample is selected from each stratum. This ensures representation from each subgroup in the final sample.
3. Cluster sampling: This technique involves dividing the population into clusters or groups, and then randomly selecting a few clusters to include in the sample. All individuals within the selected clusters are then included in the sample.
4. Systematic sampling: In systematic sampling, the researcher selects every nth individual from the population to be included in the sample. The starting point is randomly determined.
5. Convenience sampling: This technique involves selecting individuals who are readily available and accessible to the researcher. While convenient, this method may introduce bias as it does not ensure a representative sample.
6. Snowball sampling: This technique is often used when studying hard-to-reach populations. The researcher starts with a few initial participants and then asks them to refer other potential participants, creating a snowball effect.
7. Quota sampling: In quota sampling, the researcher sets specific quotas for different subgroups based on certain characteristics (e.g., age, gender, occupation). The sample is then selected to meet these quotas.
It is important for researchers to carefully consider the sampling technique that best suits their research objectives and the characteristics of the population they are studying.