08
Nov
Stratified Random Sampling Definition. Stratified Random Sampling Definition. Take a look at this chart. In stratified sampling the population is partitioned into regions or strata and a sample is selected by some design within each stratum. Stratified random sampling is a random sampling method where you divide members of a population into strata or homogeneous subgroups.
In stratified sampling the population is partitioned into regions or strata and a sample is selected by some design within each stratum. 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 Definition. Stratified random sampling refers to a sampling technique in which a population is divided into discrete units called strata based on similar attributes. Random samples can be. This chapter first explains estimation of the population total and population mean.
What Is Stratified Random Sampling.
Stratified random sampling is a method of sampling that involves the division of a population into smaller sub-groups known as strata. Stratified random sampling is an extremely productive method of sampling in situations where the researcher intends to focus only on specific strata from the available population data. For example you want to find out whether workers who did a lot of overtime work had higher performance scores. The design is called stratified random sampling if the design within each stratum is simple random sampling. In stratified random sampling or stratification the strata are formed based on members shared attributes or characteristics such as income or educational attainment. A stratified random sample is a population sample that requires the population to be divided into smaller groups called strata.