Survey Sampling
Introduction
Survey sampling is a statistical method used in the collection of data from a subset, or sample, of a larger population. It is a fundamental aspect of survey methodology, which is the study of methods for collecting, analyzing and interpreting survey data. Survey sampling is used in a wide range of fields, including sociology, psychology, political science, and market research.
Principles of Survey Sampling
Survey sampling is based on the principle of inferential statistics. This means that conclusions about the entire population are drawn based on data collected from a sample. The key to effective survey sampling is to ensure that the sample is representative of the population. This is achieved through various sampling techniques, which are categorized into two main types: probability sampling and non-probability sampling.
Probability Sampling
Probability sampling is a type of sampling method where every member of the population has a known, non-zero chance of being selected in the sample. This method is preferred when the objective of the study is to make statistical inferences about the population. There are several types of probability sampling methods, including simple random sampling, systematic sampling, stratified sampling, and cluster sampling.
Simple Random Sampling
Simple random sampling is the most basic form of probability sampling. In this method, every member of the population has an equal chance of being selected. This method is most effective when the population is homogeneous, meaning that the characteristics of the individuals are similar.
Systematic Sampling
Systematic sampling is a method where every nth member of the population is selected. The starting point is chosen at random and then every nth member is selected. This method is often used when a complete list of the population is available.
Stratified Sampling
Stratified sampling is a method where the population is divided into non-overlapping groups, or strata, and a simple random sample is drawn from each stratum. This method is used when the population is heterogeneous and the researcher wants to ensure representation from all the strata.
Cluster Sampling
Cluster sampling is a method where the population is divided into groups, or clusters, and a random sample of clusters is selected. All members of the selected clusters are included in the sample. This method is often used when the population is spread over a large geographic area.
Non-Probability Sampling
Non-probability sampling is a type of sampling method where the selection of members is not based on a known probability of selection. This method is often used when the objective of the study is exploratory in nature. There are several types of non-probability sampling methods, including convenience sampling, quota sampling, purposive sampling, and snowball sampling.
Convenience Sampling
Convenience sampling is a method where the sample is selected based on ease of access. This method is often used in preliminary research to gather a quick sample.
Quota Sampling
Quota sampling is a method where the researcher decides on the desired proportions of the sample for certain characteristics and then selects respondents based on those characteristics. This method is often used in market research.
Purposive Sampling
Purposive sampling is a method where the researcher selects individuals who are considered to be typical of the population. This method is often used in qualitative research.
Snowball Sampling
Snowball sampling is a method where initial respondents are selected at random and then additional respondents are selected based on referrals from the initial respondents. This method is often used when the population is hard to reach or identify.
Sample Size Determination
The determination of sample size is a crucial aspect of survey sampling. The sample size is determined based on the level of precision required, the confidence level desired, and the variability in the population. There are various formulas available for calculating the sample size.
Sampling Errors
Sampling errors occur when the sample selected does not accurately represent the population. There are two types of sampling errors: systematic errors and random errors. Systematic errors occur when there is a consistent, repeated deviation from the true value. Random errors occur due to chance and are unpredictable.
Conclusion
Survey sampling is a fundamental aspect of survey methodology. It involves the selection of a subset of a population to collect data. The key to effective survey sampling is to ensure that the sample is representative of the population. This is achieved through various sampling techniques, including probability sampling and non-probability sampling.