Stratified sampling

A method of sampling that involves dividing a population into subgroups

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Diagram illustrating stratified sampling

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. Stratified sampling is a method of probability sampling (e.g., simple random sampling) in which the population is divided into different "strata" and a sample is taken from each stratum.

Overview

Stratified sampling involves dividing the population into homogeneous subgroups before sampling. The strata should be mutually exclusive: every element in the population must be assigned to only one stratum. The strata should also be collectively exhaustive: no population element can be excluded.

Process

The process of stratified sampling involves several steps:

1. Identify the strata: Determine the characteristics that define the strata. These characteristics should be relevant to the research question.
2. Divide the population: Partition the population into strata based on the identified characteristics.
3. Sample from each stratum: Use a probability sampling method to select a sample from each stratum. This can be done using simple random sampling or systematic sampling.
4. Combine the samples: Combine the samples from all strata to form the complete stratified sample.

Advantages

Stratified sampling has several advantages:

• Increased precision: By ensuring that each subgroup is represented, stratified sampling can increase the precision of the overall sample.
• Reduced variability: Stratified sampling can reduce the variability of the sample estimates.
• Ensures representation: It ensures that all subgroups of interest are represented in the sample.

Disadvantages

Despite its advantages, stratified sampling also has some disadvantages:

• Complexity: The process of identifying strata and dividing the population can be complex and time-consuming.
• Requires detailed information: Detailed information about the population is required to effectively stratify it.

Applications

Stratified sampling is widely used in various fields such as:

• Market research: To ensure that different segments of the market are represented.
• Public health: To study different demographic groups within a population.
• Education: To assess the performance of different student groups.

Related pages

• Simple random sampling
• Systematic sampling
• Cluster sampling
• Sampling (statistics)

• Stratified sampling
  Stratified sampling