Abstract:
This paper introduces Bayesian analysis and demonstrates its application to parameter estimation
of the logistic regression via Markov Chain Monte Carlo (MCMC) algorithm. The Bayesian logistic regression
estimation is compared with the classical logistic regression. Both the classical logistic regression and the
Bayesian logistic regression suggest that higher per capita income is associated with free trade of countries.
The results also show a reduction of standard errors associated with the coefficients obtained from the
Bayesian analysis, thus bringing greater stability to the coefficients. It is concluded that Bayesian Markov
Chain Monte Carlo algorithm offers an alternative framework for estimating the logistic regression mode
