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Stratified sampling is a statistical sampling concept used to draw a representative sample from an entire population. In stratified sampling, the total population is divided into different subgroups, or strata, based on certain common characteristics or criteria. A subset is then randomly selected from each stratum to form the sample.
The main goal of stratified sampling is to ensure that each subgroup is adequately represented in the sample, especially when certain subgroups are less common in the general population. Dividing the population into strata and selecting samples from each stratum ensures that each portion of the population is represented in the sample in proportion to the total population.
The process of stratified sampling typically includes the following steps:
Identification of the relevant characteristics: First, the characteristics are identified by which the population is to be divided into strata. This can be demographic, geographic or other relevant criteria, depending on the research objective.
Stratum definition: The strata are defined on the basis of the identified features. Each element of the population is assigned to a specific stratum.
Determining sample size: The total sample size is determined, taking into account how many observations from each stratum should be included. The sample size can be proportional to the size of each stratum or based on other criteria.
Random sampling: Random sampling is performed within each stratum to select the required number of observations. This can be done, for example, by simple random sampling or another suitable method.
Data Analysis: After the sample has been collected, statistical analysis can be performed to draw conclusions about the overall population. Weights can be applied to combine the results from the different strata according to their relative size.
Stratified sampling allows for better sample accuracy and representativeness, especially when certain subgroups of the population are of particular interest. By taking into account the heterogeneity of the total population, this method can lead to more meaningful and reliable statistical statements.