exercises Week 3 (Mon Sep 1 ff) and Week 4 (Mon Sep 8 ff)

Key words this Week 2: stories (Odin, antidepressant); simulation for gamma posteriors and Dirichlet posteriors (and mixtures thereof); approximate normality things; prior elicitation. 

We have been through (more or less): Ch7 exercises 1, 2, 3, 4, 5, 9, 12, 13, 15 (note the mixture prior), 16; then Stories #41 (Odin's children, Bayesian part), #13 (antidrepressant, Bayesian part). 

I've placed more Nils-R-code on the site; check e.g. com351a, with mixture prior things for 7.15 (see also 7.23). 

For Week 3 onwards: Story #54 (Star Trek, Bayesian part), MCMC 17, 18, 19. Extra: Suppose people in a city have iqs following the \N(100,\sigma^2) distribution, with \sigma = 15. You visit a special school, with \N(\xi,0.5 \sigma^2), and with the normal above as prior. How do you change your view about the pupils of this school, when the first pupil you test has iq = 130? 

Nex story (after this): Story #31 (deer in forest, Bayesian part).