 | |
| STAT0725-1 | Statistique bayésienne
 |
|
| Duration : | 30h Th, 30h Pr |
|
| Credits/ECTS : |
|
|
| Holder(s) : | Philippe Lambert |
|
| Language : | Langue française |
|
| Course contents : | This course consists of about ten theoretical lectures describing the core of the Bayesian paradigm. We first show how the basic problems tackled in a frequentist setting can be solved in a Bayesian framework. Then, we explain how problems difficult to treat using a frequentist approach can be solved in a Bayesian way. The presented techniques will be systematically illustrated with examples involving algorithms or the computer code necessary to obtain a practical solution. Practicals will also be organized to further illustrate the theory. |
|
| Course objective : | To provide the key elements of the Bayesian paradigm ; to show how classical problems studied in an ad hoc way with frequentist statistics can easily and systematically be solved in a Bayesian framework ; to explain and use Monte Carlo algorithms to sample from a posterior distribution ; to show how challenging problems without a workable solution in a frequentist framework can be solved using Bayesian arguments. |
|
| Prerequisites : | The course is organized during the 2nd semester on a weekly basis according to a timetable distributed at the beginning of the academic year. |
|
| Workshops : | These will consists of about ten hours of ex-cathedra courses, the other scheduled hours being devoted to the resolution of exercises under the supervision of an assistant and to an individual project which report will serve as a starting point for the oral evaluation. |
|
| Organization : | The course is organized during the 2nd semester on a weekly basis according to a timetable distributed at the beginning of the academic year. |
|
| Written notes : | The slides used during the course will be made available with the associated list of references. |
|
| Assessment : | An oral exam with as starting point the written report describing the solutions given to the problems involved in the above mentioned individual project. The report is expected before the start of the exam session. |
|
