06
Jan
What Is Stratified Sampling In Research. Once divided each subgroup is randomly sampled using another probability sampling method. The 7 th MAC 2016 Proceeding. Stratification of target populations is extremely common in survey sampling. Stratified random sampling usually referred to simply as stratified sampling is a type of probability sampling that allows researchers to improve precision reduce error relative to simple random sampling SRS.
Stratified random sampling is a method for sampling from a population whereby the population is divided into subgroups and units are randomly selected from the subgroups. This subset represents the larger population. In stratified sampling researchers divide subjects into subgroups called strata based on characteristics that they share eg race gender educational attainment etc. By strategically forming these groups called strata stratification becomes a feature of sample designs that can improve. This sampling strategy is suitable when youre dealing with a heterogeneous population that has several groups in it they dont overlap but together represent the population in its entirety. But the formula mentioned below is used widely.
While sampling these groups can be organized and then draw a sample from each group separately.
A stratified sample is one that ensures that subgroups strata of a given population are each adequately represented within the whole sample population of a research study. Stratified Sampling Formula. The 7 th MAC 2016 Proceeding. E is the margin of error the level of precision or the risk the researcher is willing. It is used when the population is heterogeneous. Stratified random sampling is a method of sampling which is when a researcher selects a small group as a sample size for study.