The Basics of Bayesian Approach to Quantitative Analysis (at the Example of Euroscepticism)

This article attempts to identify the main assumptions, prerequisites and techniques of the methods developed by some modern statisticians on the basis of T. Bayes' theorem for the purposes of social variables interactions assessment. The author underlined several advantages of the given approach as compared to more traditional quantitative methods and highlighted key research areas subject to evaluation by Bayesian estimates. First of all, this approach is compatible with game and decision theory, event analysis, hidden Markov chains, prediction using neural networks and other predictive algorithms of artificial intelligence. The Bayesian approach differs significantly from traditional statistical methods (first of all, it is focused on finding the most probable, rather than the only true value of the feature coupling coefficient), hence a graphical interpretation was provided for such basic concepts and techniques as probabilistic inference, maximum likelihood estimation and Bayesian confidence network. The described tools were used to test the hypothesis about the impact of life quality decrease on rise in Euroscepticism of EU citizens. ANOVA and correlation analysis of 27 thousand people’s responses to Eurobarometer questions addressed in November-December 2019 attributed strong likelihood to this assumption. Moreover, Bayesian approach allowed for a probabilistic conclusion that this hypothesis is more plausible than the link between Euroscepticism and respondents’ current financial situation (explanatory power of comparison to the past is relatively greater).