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Probability models and decision analysis : introduction

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1 Probability models and decision analysis : introduction
Samu Mäntyniemi Biotieteellinen tiedekunta / Samu Mäntyniemi/Probability models and decision analysis

2 Introduction Contents of the course Type and amount of work
Course material Passing the course Introduction of participants Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

3 Contents Probability models for Bayesian inference: ”science of knowing” Describe a problem mathematically Commonly used building blocks for case specific models How to criticize and compare models? Decision analysis : ”science of doing” Analytical decision making under uncertainty Value of Information: what data to collect Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

4 Probability models: example I Linear regression
Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

5 Probability models: example II Logistic regression
Released Survived Temp. 10 5 7 12 1 100 25 30 Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

6 Decision analysis: How to make money by sports betting?
Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

7 Decision analysis: example 2 Seal hunting
Conflicting interests Increasing grey seal population causes damage to fishery Too intensive hunting may cause the population to crash again How to find a balance between conservation and negative impacts to fishery profits? Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

8 Types of work Lectures Demonstrations Experiment: Skype video
Exercises Homework exercises Exam Homework project Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

9 Amount of work 8 – 12 credits = 216 – 324h of work
Lectures, demonstrations & exercises 10 x 8h =80h Homework exercises & project h Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

10 Passing the course Grading 1-5 based on exercises and exam
Homework project : accept/reject Homework exercises 3 sets, 4 points/set Exam 12 points, minimum of 4 points to pass the course At least 12 points from homework exercises and exam + accepted homework = course passed 8-12 credits: Small/Medium/Large homework project Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

11 Homework project Analyse a research problem of your interest
Write a report describing what you did A data analysis, modelling of expert knowledge, decision analysis or a combination of all these Return by the end of January 2011 Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

12 Course material Wiki Bayesian Methods for Ecology Course programme
Powerpoint and other files Exercises Bayesian Methods for Ecology Not necessary, but helpful Examples with BUGS code Includes some errors: I will point these out Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

13 Software Hugin OpenBUGS MS Excel
OpenBUGS ile&do=get&target=OpenBUGS312Esetup.exe MS Excel Biotieteellinen tiedekunta / Henkilön nimi / Esityksen nimi


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