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Stratified sampling is a statistical method used to create a representative sample by dividing a population into homogeneous subgroups, or strata, based on shared characteristics. This technique is particularly useful in heterogeneous populations and allows for detailed subgroup analysis. It ensures precision in research outcomes by minimizing sampling error and bias, and is crucial for studies that require analysis across diverse groups.
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Stratified sampling is a statistical technique used to construct a representative sample of a population
Strata
Researchers divide the population into homogeneous subgroups, known as strata, based on shared attributes
Characteristics
Strata are based on shared attributes such as age, income, education level, or other relevant criteria
Stratified sampling aims to enhance accuracy and representativeness of research findings by mirroring the population's structure in the sample
Defining the Target Population
Researchers begin by clearly defining the target population
Identifying Strata
Researchers identify the strata based on characteristics pertinent to the research objectives
Allocating Sample Sizes
Researchers determine the total sample size required and allocate sample sizes to each stratum
Random Selection
A random selection process is then employed within each stratum to assemble the final sample
A study examining dietary preferences across different age groups within a community can use stratified sampling by defining the population as all residents of the community and identifying age groups as the strata
Stratified sampling can present challenges in accurately defining and segregating the population into distinct, non-overlapping strata
Stratified sampling minimizes sampling error and bias, enhances accuracy and representativeness of research findings, and allows for more detailed analysis of subgroup characteristics
Complex Characteristics
Ambiguities may arise in strata definition, particularly with complex characteristics such as cultural identity
Diversity
Stratified sampling may not fully capture the diversity within a population, especially when the population exhibits a vast array of characteristics and subgroups
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In ______ sampling, researchers create a sample mirroring the population by dividing it into ______ based on common characteristics.
Stratified
strata
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Definition of stratified sampling
Sampling method dividing population into subgroups, ensuring each is represented.
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Impact of stratified sampling on sampling error
Reduces sampling error by proportionally representing all segments of population.
