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The representativeness of research results in empirical social research is usually checked using statistical methods. Here are some steps used in practice to check representativeness:
Sample selection: A representative sample should be chosen at random to ensure that all members of the target group have an equal chance of being included in the study. There are different methods of sampling, such as random sampling, cluster sampling, or stratification, to cover a wide variety of characteristics.
Characteristics of the population: It is important to know the characteristics of the target group in order to adequately represent the sample. Demographics such as age, gender, ethnicity, and geographic distribution are often important. Existing data sources such as censuses or official statistics can help here.
Comparison groups: The collected data is often compared with known values from other sources in order to check the representativeness. If the distribution of characteristics in the sample is similar to that in the target group or other representative studies, this indicates good representativeness.
Weighting: In some cases it may be necessary to weight the sample results to compensate for inequalities in the sample. This may be necessary due to over- or under-representation of certain groups.
Statistical Tests: Various statistical tests can be performed to check representativeness. This often involves comparing results from the sample with the actual distribution in the target group or other recognized data sources.
It is important to note that despite careful methodology, no study can achieve complete representativeness. Representativeness is an ideal that often can only be approximated due to practical limitations. Therefore, it is important to recognize the limitations and uncertainties of the research results.