BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -Stratified sampling-where one samples specific proportions of individuals from various subpopulations (strata) in the larger population-is meant to ensure that the subjects selected will be representative of the population of interest.

Detailed explanation-2: -Stratified random sampling is a method of sampling that involves the division of a population into smaller subgroups 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.

Detailed explanation-3: -Many surveys use this method to understand differences between subpopulations better. Stratified sampling is also known as stratified random sampling. The stratified sampling process starts with researchers dividing a diverse population into relatively homogeneous groups called strata, the plural of stratum.

Detailed explanation-4: -When using stratified sampling, the population is divided into homogeneous, mutually exclusive groups called strata, and then independent samples are selected from each stratum. Any of the sampling methods mentioned in this section can be used to sample within each stratum.

Detailed explanation-5: -This has to be accounted for when we select a sample from the population in order that we obtain a sample that is representative of the population. This is achieved by stratified sampling. A non-stratified sample does not take separate samples from strata or sub-groups of a population.