This article methodologically analyzes the problem of data representation in empirical research through the issues of sampling, bias, and generalization of results. The study aims to identify the main factors that determine the role and reliability of empirical data in scientific conclusions. The analysis results demonstrate that in empirical research, the robustness of sampling design, reduction of bias, and clear delineation of generalization boundaries ensure the validity of scientific conclusions. The article presents theoretical insights on improving the methodology of empirical research.

empirical data, sampling, representativeness, bias, generalization, external validity, methodology.

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83.

Murad, M. H., Katabi, A., Benkhadra, R., & Montori, V. M. (2018). External validity, generalisability, applicability and directness: A brief primer. BMJ Evidence-Based Medicine, 23(1), 17–19.

Tourangeau, R., Conrad, F. G., & Couper, M. P. (2013). The Science of Web Surveys. Oxford University Press.

Shodmonov Sh., Xo‘jayev B. Statistika nazariyasi. – Toshkent: Iqtisodiyot, 2016.

Federal Committee on Statistical Methodology. Best Practices for Nonresponse Bias Reporting. – Washington, 2023.

Shodmonov Sh., Xo‘jayev B. Statistika nazariyasi. – Toshkent: Iqtisodiyot, 2016.