Simple Random Sampling (SRS) is a type of probability sampling technique used in selecting a sample from a larger population. It is a simple and commonly used sampling method, whereby each member of the population has an equal chance of being selected. The key principle behind SRS is that each member of the population is considered independent of every other member, meaning that the selection of any one member does not influence the selection of another. In SRS, each individual in the population has the same probability of being selected, and each selection is independent of every other selection. This ensures that the sample is representative of the population and provides an unbiased estimate of the population characteristics.
SRS is widely used in social science research due to its simplicity. It is often used when the population size is unknown or when the researcher does not have access to a sampling frame. SRS is also appropriate when the researcher wishes to compare subgroups within a population. Although SRS is easy to implement, there are some potential drawbacks. A major limitation is that, due to the random nature of the sampling method, some members of the population may be overrepresented in the sample, while other members may be underrepresented. This can result in an unrepresentative sample and can lead to inaccurate results.
In conclusion, Simple Random Sampling is a commonly used method of probability sampling that is simple to implement and provides a representative sample of a population. However, it is important to recognize its potential limitations in order to ensure accurate results.
References
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610.
Kish, L. (1965). Survey sampling. New York: John Wiley & Sons.
Lohr, S. L. (1999). Sampling: design and analysis. Pacific Grove, CA: Duxbury Press.