Bayesian Training
Bayesian Training equips statisticians with skills to construct priors, calculate posteriors, interpret vaccine efficacy using credible intervals, perform robustness checks, and produce clear visual summaries for solid data-driven choices in vaccine trials.

flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
This course offers a practical guide to Bayesian analysis of vaccine trial data. Learners will define binomial models, create trial scenarios, develop priors for vaccine efficacy from experts, update Bayesian models, summarise posteriors, check robustness, dodge pitfalls, and share uncertainty with decision-makers in studies.
Elevify advantages
Develop skills
- Bayesian VE modelling: quickly build and analyse binomial vaccine efficacy models.
- Prior elicitation: convert expert views on VE into effective Beta priors.
- Posterior analysis: calculate VE means, credible intervals, and Pr(VE>50%).
- Robustness checks: conduct prior sensitivity, sceptical priors, and prior predictive checks.
- Communication: clearly present Bayesian VE findings to technical audiences.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...

Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.

André FelipePrompt Engineering Student
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