Course syllabus
Course PM
This page contains the program of the course: lectures and computer labs. Other information, such as learning outcomes, teachers, literature and examination, are in a separate course PM.
The schedule of the course is in TimeEdit.
Minutes of the mid-course meeting held on 24 September 2019.
Lectures
None of the lectures or computer lab sessions are mandatory to attend. However you are strongly encouraged to attend as we have limited resources to provide help outside teaching hours.
See the section Examination in the course PM for deadlines of mandatory hand-ins.
| Day | lecturer | Topics | code and data files |
slides and notes |
| Wed 4 Sept | Umberto Picchini |
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| Wed 11 Sept | Umberto Picchini | More R, intro to LaTeX, more linear regression, underfitting/overfitting |
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| Wed 18 Sept | Umberto Picchini | Bootstrap |
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| Wed 25 Sept | Petter Mostad | Reliability and survival. |
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| Wed 2 Oct | Petter Mostad | Bayesian decision theory. |
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| Wed 9 Oct | Annika Lang | Intro to Python, Monte Carlo methods |
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| Wed 16 Oct | Annika Lang | Simulation of stochastic processes |
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| Monday 21 Oct | Umberto Picchini |
extra office hours: Umberto: 16.00-17.00 |
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| Wednesday 23 Oct | Annika Lang |
extra office hour: Annika: 11.00-12.00 |
Computer labs
Teaching assistants will be available for answering questions. There will not be any formal class.
| Day | Main topic |
| Thur 5 Sept | A1 |
| Mon 9 Sep | A1 |
| Thur 12 Sep | A2 + possibly complete A1 |
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Mon 16 Sep |
A2 |
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Thur 19 Sep |
A2 |
| Mon 23 Sep | A2 |
| Thur 26 Sep | A3 (or finish A2) |
| Mon 30 Sep | A3 |
| Thur 3 Oct | A3 |
| Mon 7 Oct | A4 |
| Thur 10 Oct | A4 |
| Mon 14 Oct | A5 |
| Thur 17 Oct | A5 |
| Mon 21 Oct | A6 |
| Thur 24 Oct | A6 |
Course summary:
| Date | Details | Due |
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