Stratified Random Sample

Definition:
A stratified random sample is a sampling technique where the population is divided into distinct subgroups or strata, and then a random sample is taken from each stratum. The goal is to ensure that the sample is representative of the entire population.

Explanation:
- Stratified: The answer choice (a) stratified is incorrect because stratified random sampling is a method that involves dividing the population into different strata based on certain characteristics or variables.
- Purposive: The answer choice (c) purposive is incorrect because purposive sampling refers to a non-random sampling technique where the researcher selects specific individuals or cases that are deemed to be most relevant to the research question.
- None of the above: The answer choice (d) none of the above is incorrect because stratified random sampling is a specific sampling technique that falls under the larger umbrella of sampling methods. It is not a combination of the other options.

Reasoning:
The correct answer is option (b) representative. Here's why:

- Representative: A stratified random sample is considered more representative compared to other sampling techniques because it ensures that each subgroup or stratum within the population is represented in the sample proportionally to its size or importance. This helps to reduce the potential for bias and increase the generalizability of the findings.

- Random: The random component of stratified random sampling ensures that the selection of individuals within each stratum is based on chance. This helps to avoid any systematic bias that may arise if the researcher were to handpick individuals from each stratum.

- Sample: A sample is a subset of individuals or cases taken from a larger population. In the case of stratified random sampling, the sample is obtained by selecting individuals from each stratum based on randomization.

- Population: The population refers to the entire group of individuals or cases that the researcher wants to study. Stratified random sampling ensures that the sample is representative of the population by including individuals from different strata.

Overall, stratified random sampling is considered more representative because it takes into account the heterogeneity within the population and aims to capture the characteristics of each subgroup or stratum. This allows for more accurate generalizations and conclusions to be made about the entire population based on the sample.