5/30/2023 0 Comments Random sampling![]() ![]() ![]() There are a couple different types of stratified random sampling. The advantage of this approach is that it reduces sampling variability because the researcher uses the same sample for every subgroup. The researcher can also use cluster sampling to select the sample, which means he can survey households or geographical areas instead of a sample of individuals. This means members of the first subgroup have a greater chance of selection than members of the other two subgroups because there are fewer people in the first subgroup. He then divides the population of the country according to these subgroups and randomly selects a sample from each stratum. He has identified three mutually exclusive and collectively exhaustive subgroups: income less than $25,000, $25,000-$50,000, and $50,000 or more. Imagine a researcher is conducting a survey to learn about the income levels of various groups in the country. To understand how a stratified random sampling formula works, let’s take a look at an example. This type of probability sampling helps avoid disproportionate sampling in your stratum sample size. In stratified random sampling, members of the population belonging to each stratum have a greater chance of selection than those who do not. In simple random sampling, all members of the population have an equal chance of selection, regardless of the characteristics they possess. A stratified random sample differs from simple random sampling in that it first partitions the population into mutually exclusive and collectively exhaustive strata based on relevant identifiable characteristics and then selects a sample from each stratum through probability sampling. Probability sampling is then used to select the random sample from each stratum. Each possible sample is therefore equally likely.Ī stratified random sample is a type of statistical sampling in which a population divides into mutually exclusive and collectively homogeneous strata. It involves random selections of data from a whole population. Stratified random sampling is different from simple random sampling.Stratified random sampling is the division of a population into homogeneous strata.Researchers can use stratified random sampling to get a representative sample of the entire population under study.
0 Comments
Leave a Reply. |