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 random sampling is also called proportional random sampling or quota random sampling. When completing analysis or research on a group of entities with similar characteristics, a researcher may find that the population size is too large for which to complete research. To save time and money, an analyst may take on a more feasible approach by selecting a small group from the population. The small group is referred to as a sample size , which is a subset of the population that is used to represent the entire population.
Understanding types of variables
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In statistics , stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys , when subpopulations within an overall population vary, it could be advantageous to sample each subpopulation stratum independently. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. The strata should define a partition of the population.
In statistics , stratified randomization is a method of sampling which first stratifies the whole study population into subgroups with same attributes or characteristics, known as strata, then followed by simple random sampling from the stratified groups, where each element within the same subgroup are selected unbiasedly during any stage of the sampling process, randomly and entirely by chance. Stratified random sampling is sometimes also known as " quota random sampling ". Stratified randomization is extremely useful when the target population is heterogeneous and effectively displays how the trends or characteristics under study differ between strata. Stratified randomization decides one or multiple prognostic factors to make subgroups, on average, have similar entry characteristics.
Stratified random sampling is a method of sampling that involves dividing a population into smaller groups—called strata. The groups or strata are organized based on the shared characteristics or attributes of the members in the group. The process of classifying the population into groups is called stratification. Stratified random sampling is also known as quota random sampling and proportional random sampling. Stratified random sampling has numerous applications and benefits, such as studying population demographics and life expectancy.