Age, socioeconomic divisions, nationality, religion, educational achievements and other such classifications fall under stratified random sampling. Let's consider a situation where a research team is seeking opinions about religion amongst various age groups.
Stratified random sampling is a method of sampling that involves the division of a population into smaller sub-groups known as strata. In stratified random sampling, or stratification, the strata are formed based on members' shared attributes or characteristics such as income or educational attainment.
Stratified simple random sampling is a variation of simple random sampling in which the population is partitioned into relatively homogeneous groups called strata and a simple random sample is selected from each stratum. The results from the strata are then aggregated to make inferences about…
Stratified random sampling is one common method that is used by researchers because it enables them to obtain a sample population that best represents the entire population being studied, making sure that each subgroup of interest is represented.
Stratified sampling is a probability sampling method that is implemented in sample surveys. The target population's elements are divided into distinct groups or strata where within each stratum the elements are similar to each other with respect to select characteristics of importance to the survey.Feb 15, 2017
Four main methods include: 1) simple random, 2) stratified random, 3) cluster, and 4) systematic. Non-probability sampling – the elements that make up the sample, are selected by nonrandom methods. This type of sampling is less likely than probability sampling to produce representative samples.