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Stratified Random Sample Definition

Probability samples that force sample to be more representative of the population. It is obtained by dividing the population into groups called strata, then simple random samples are taken from each of the strata.

A stratified random sample is a sampling technique used in market research. It involves dividing the population into distinct subgroups based on certain characteristics that are relevant to the research objective. Random samples are then drawn independently from each stratum, ensuring representation from all subgroups. This approach helps improve the accuracy and representativeness of the sample.

Who relies on stratified random sample in market research?

Market researchers, data analysts and organizations conducting market research studies rely on stratified random sampling. This method is particularly beneficial when the population exhibits significant diversity and researchers want to ensure that each subgroup's characteristics are captured adequately.

Why should I care about stratified random sample?

If you're involved in market research or decision-making based on research outcomes, stratified random sampling matters. It enhances the credibility of your findings by reducing bias and increasing the likelihood that your sample accurately represents the entire population. This leads to more reliable insights and better-informed business choices.

Why is stratified random sample important in market research?

• The importance of stratified random sampling lies in its ability to provide a more comprehensive view of a population.
• Stratafied random sample. ensures that both major and minor subgroups are accounted for, minimizing the risk of overlooking crucial variations within the population.
• This method enhances the statistical validity of results, reinforcing the foundation of sound decision-making.