In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The ...

In this section, you'll investigate the Bayesian statistical framework. Bayesian statistics are an alternative perspective to classical Frequentist approaches which you've seen thus far. Bayesian ...

Introduction to the Bayesian paradigm. Markov Chain Monte Carlo estimation using WinBUGS. Comparison with frequentist statistics. Noninformative and improper priors. Inference and model selection.

1 Department of Pharmaceutical Sciences and Technology, Institute of Chemical Technology, Mumbai 2 Department of Mathematics, Institute of Chemical Technology, Mumbai Bayesian statistical methods have ...

Inferring group norms is crucial for adapting behaviors in novel situations, but its underlying basis and computational account remain unclear. This study manipulated the prevalence of norm-consistent ...

This was perhaps my favourite chapter to work on in our book "Bayesian Meta-analysis: a practical introduction". I still see myself dreaming up a long list of tips and tricks while hiding out in the ...