Stratified Sampling

Definition

Stratified sampling is a sampling method that involves dividing a population into distinct subgroups, or strata, that share similar characteristics. By selecting samples from each stratum, this method ensures representation from all segments of the population, leading to more accurate and reliable data collection.

5 Must Know Facts For Your Next Test

1. Stratified sampling can enhance the precision of survey estimates by ensuring that specific subgroups are represented in the sample.
2. The strata used in stratified sampling can be based on various characteristics such as age, gender, income, or education level.
3. This method can be either proportionate or disproportionate; in proportionate stratified sampling, the sample size from each stratum is proportional to its size in the population.
4. Stratified sampling is particularly useful when researchers are interested in comparing different groups within a population.
5. It reduces sampling error by allowing for more targeted analysis and can lead to more comprehensive insights compared to simple random sampling.

Review Questions

• How does stratified sampling improve data collection compared to other methods?
  • Stratified sampling improves data collection by ensuring that all relevant subgroups within a population are represented in the sample. This method reduces bias and variability by allowing researchers to make more accurate comparisons between different strata. In contrast to simple random sampling, which may overlook important groups, stratified sampling enhances the reliability of findings and leads to better-informed decisions based on the data collected.
• Discuss the advantages and disadvantages of using stratified sampling in research studies.
  • The advantages of using stratified sampling include increased accuracy and representativeness of the sample, especially when dealing with heterogeneous populations. By carefully selecting participants from each stratum, researchers can ensure that diverse perspectives are included. However, a disadvantage is that it requires detailed knowledge of the population characteristics and can be more complex and time-consuming to implement compared to simpler methods like simple random sampling.
• Evaluate how stratified sampling can impact the outcomes of a business decision-making process.
  • Stratified sampling significantly impacts business decision-making by providing insights that are reflective of various segments within a target market. When businesses utilize this method to gather data, they can uncover trends and preferences among different consumer groups, leading to more tailored marketing strategies and product development. This approach allows businesses to minimize risks and make informed decisions based on comprehensive data analysis, ultimately enhancing overall effectiveness in their strategic planning.

Related terms

Population: The entire group of individuals or instances about whom we are interested in making conclusions.

Sampling Frame: A list or database that includes all the members of the population from which a sample will be drawn.

Simple Random Sampling:

A sampling method where each member of the population has an equal chance of being selected, without regard to any specific characteristics.