Learn Bayesian Computational Analyses using R software
Geoffrey Hubona <[email protected]>
| Newsgroups | gmane.comp.hci.acm-sigchi.resources |
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| Message-ID | <CAKRFP85xCUKJpxpwmPPRcgc1PqqUR_jog1K8hcptGn7Ms=qofw@mail.gmail.com> |
Live, online workshop classes begin January 22 AM and PM.
Visit: http://tinyurl.com/mybayesian
Live, online, interactive 8-session course begins January 22 with AM and PM
sessions to reach everyone. HD audio and video recordings of live workshop
sessions provided to all participants afterwards.
Learn to conduct: Prediction; Dealing with proportions; Discrete priors;
Beta priors;
Single-parameter, normally distributed models with known means and unknown
variance; Bayesian robustness; Mixtures of conjugate priors;
Multi-parameter models: Normal data with 2 unknown parameters; Multinomial
models; Comparing two proportions;
Bayesian computation: Computing integrals; Monte carlo simulation.
Hierarchical modeling: Model comparisons; Comparing hypotheses.
Regression models: Normal linear regression; Prediction of future
observations.
Visit: http://tinyurl.com/mybayesian
Geoff Hubona
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