Definition
A probability sampling technique that uses a two-step process to partition the population into subpopulations, or strata is known as stratified random sampling. Elements are selected from each stratum by a random procedure.
Explanation
Stratified Random Sampling emerges from the word Stratum. A Stratum in a population is a segment of that population having one or more characteristics. E.g. people in the age strata of 35-40, people in the income strata to Rs. 20000 p.m. etc
Stratified Sampling involves treating each stratum as a separate subpopulation for sampling purposes, and from each stratum sampling units would be drawn randomly.
The reasons for conducting Stratified Random Sampling are:
• To reduce sampling error by ensuring representation from the population.
• The required sample size for the same level of sampling error will usually be smaller.
As compared to other methods of sampling, in Stratified Random Sampling representativeness to a certain degree is forced.
The greater degree to which there is similarity within stratum, smaller is the sample size required to provide information about that stratum.
Thus the more homogeneous each stratum is with respect to the variable of interest the smaller is the sample required.
Example
If the head of the household age strata (18-34, 35-49, 50+) are of interest in a study on household spending habits on household furnishings, then each of these groups would be taken separately for sampling purposes. That is, the total population could be divided into age groups and a separate sample is drawn from each group.
A probability sampling technique that uses a two-step process to partition the population into subpopulations, or strata is known as stratified random sampling. Elements are selected from each stratum by a random procedure.
Explanation
Stratified Random Sampling emerges from the word Stratum. A Stratum in a population is a segment of that population having one or more characteristics. E.g. people in the age strata of 35-40, people in the income strata to Rs. 20000 p.m. etc
Stratified Sampling involves treating each stratum as a separate subpopulation for sampling purposes, and from each stratum sampling units would be drawn randomly.
The reasons for conducting Stratified Random Sampling are:
• To reduce sampling error by ensuring representation from the population.
• The required sample size for the same level of sampling error will usually be smaller.
As compared to other methods of sampling, in Stratified Random Sampling representativeness to a certain degree is forced.
The greater degree to which there is similarity within stratum, smaller is the sample size required to provide information about that stratum.
Thus the more homogeneous each stratum is with respect to the variable of interest the smaller is the sample required.
Example
If the head of the household age strata (18-34, 35-49, 50+) are of interest in a study on household spending habits on household furnishings, then each of these groups would be taken separately for sampling purposes. That is, the total population could be divided into age groups and a separate sample is drawn from each group.