Poststratifikációval

Poststratifikációval, also known as post-stratification, is a statistical technique used to improve the accuracy of survey estimates. It is applied after data collection, hence the term "post." The core idea is to adjust survey results to better match known population characteristics. This is particularly useful when the sample used for the survey is not perfectly representative of the target population.

The process begins with a survey sample where respondents are classified into various subgroups or strata based on demographic or other relevant characteristics, such as age, gender, race, or education level. After the survey data has been collected and analyzed, the researcher obtains external data that provides precise figures for the same strata within the overall population. These external figures are often derived from census data or other reliable sources.

Poststratifikációval then involves weighting the survey responses. If a particular subgroup is underrepresented in the sample compared to its known proportion in the population, the responses from that subgroup are given a higher weight. Conversely, if a subgroup is overrepresented, its responses receive a lower weight. This weighting scheme ensures that the final estimates reflect the actual composition of the population more accurately, thereby reducing non-response bias and sampling error. It is a valuable tool for enhancing the precision of survey findings when sampling frames are imperfect or response rates are uneven across different population segments.