Porovnat metody

	Bayesovský výzkum v průzkumech	Výzkum pomocí dotazníkového šetření
Obor	Design výzkumu	Design výzkumu
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	1980s–2000s (modern applied development)	Late 19th century; methodologically systematised 1940s–1960s
Tvůrce	Thomas Bayes (theorem, 1763); applied to survey methodology by Donald Rubin, Andrew Gelman, and others (1980s–2000s)	Francis Galton, Charles Booth, and early social statisticians; systematised by Paul Lazarsfeld and colleagues at Columbia in the 1940s
Typ	Quantitative observational research design with Bayesian inference	Quantitative (and mixed) non-experimental design
Původní zdroj	Gelman, A., & Carlin, J. B. (2007). Some issues on the foundations of statistics. In A. Gelman & J. B. Carlin (Eds.), Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. ISBN: 978-0521686891	Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000
Další názvy	Bayesian survey analysis, Bayesian survey methodology, Bayesian polling, Bayesian questionnaire analysis	survey methodology, questionnaire research, survey design, survey study
Příbuzné	4	4
Shrnutí	Bayesian survey research applies Bayesian statistical inference to survey data, combining prior knowledge or beliefs about population parameters with observed questionnaire responses to produce posterior probability distributions. Unlike null-hypothesis significance testing, this approach quantifies uncertainty directly, incorporates prior evidence, and yields probabilistic statements about parameters of interest — making it especially powerful for small samples, sequential data collection, and contexts where substantive prior knowledge exists.	Survey research is a quantitative (and sometimes mixed-methods) design in which a researcher collects standardised self-report data from a sample drawn from a defined population, using a questionnaire or structured interview. It is the dominant non-experimental strategy for describing population characteristics, estimating prevalence, mapping attitude distributions, and testing bivariate or multivariate associations across social, behavioural, and health sciences.