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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Este proyecto es presentado por la Network for Pluralist Economics (Netzwerk Plurale Ökonomik e.V.) y socios internacionales.  Está comprometida con la diversidad y la independencia y depende de las donaciones de personas como tú. Donaciones regulares o puntuales serán muy apreciadas!

 

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