What is meant by stratified sampling?
A stratified random sampling involves dividing the entire population into homogeneous groups called strata (plural for stratum). A random sample from each stratum is taken in a number proportional to the stratum’s size when compared to the population. These subsets of the strata are then pooled to form a random sample.
How do you do stratified sampling?
To create a stratified random sample, there are seven steps: (a) defining the population; (b) choosing the relevant stratification; (c) listing the population; (d) listing the population according to the chosen stratification; (e) choosing your sample size; (f) calculating a proportionate stratification; and (g) using …
What is stratified and non stratified sampling?
A sampling technique where a group of subjects (a sample) for study is selected from a larger group (a population). This is achieved by stratified sampling. A non-stratified sample does not take separate samples from strata or sub-groups of a population.
When should stratified sampling be used?
Stratified sampling is used when the researcher wants to understand the existing relationship between two groups. The researcher can represent even the smallest sub-group in the population.
What is the first step in conducting stratified sampling?
The first step in stratified random sampling is to split the population into strata, i.e. sections or segments. The strata are chosen to divide a population into important categories relevant to the research interest.
What is the difference between stratified and random sampling?
Stratified random sampling is different from simple random sampling, which involves the random selection of data from the entire population so that each possible sample is equally likely to occur. In contrast, stratified random sampling divides the population into smaller groups, or strata,…
When is it appropriate to use stratified random sampling?
Stratified random sampling is used when the researcher wants to highlight a specific subgroup within the population. This technique is useful in such researches because it ensures the presence of the key subgroup within the sample.
Why is the method of stratified random sampling used?
The principal reasons for using stratified random sampling rather than simple random sampling include: Stratification may produce a smaller error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are very homogeneous.