Bayesian Statistics

Mine Çetinkaya-Rundel; David Banks; Colin Rundel; Merlise A Clyde
Level: beginner
University: Duke University
Platform: Coursera
Recurrence: flexible
Language: English
Discipline: Economics
Attendance: free
Certificate: 71.00 EUR
Workload per week: 5.0 h

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution. Additionally, the course will introduce credible regions, Bayesian comparisons of means and proportions, Bayesian regression and inference using multiple models, and discussion of Bayesian prediction.

 

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Ce projet est le fruit du travail des membres du réseau international pour le pluralisme en économie, dans la sphère germanophone (Netzwerk Plurale Ökonomik e.V.) et dans la sphère francophone (Rethinking Economics Switzerland / Rethinking Economics Belgium / PEPS-Économie France). Nous sommes fortement attachés à notre indépendance et à notre diversité et vos dons permettent de le rester ! 

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