exercises for Wed Sep 8

1. On Wed Sep 1 we did Nils Exercises 1, 2, with the Master Recipe, and the book's 2.10. We also went through general aspects of Bayesian setups, loss functions, the prior to posterior computations, etc., correlated with the first half of Ch 2. 

2. I will place my simple R programme "com26a" on the website, for Nils Exercise 1. Play a bit with the parameters (a,b) of the gamma prior, and be sure to include a "silly prior"; play also with n, the number of data points. 

3. Election day is September 13. I gave this course in 2017, but was away for one day. My PhD student Emil Stoltenberg was vikar in loco parentis for me that day, and used the occasion to write up and teach from the interesting note "Emil Stoltenberg 7-Sep-2017 predicts 11-Sep-2017 elections", available at the course website. It uses only Ch 2 methods, but there's a certain amount of Bayesian work to get the posterior going. It's also instructive for applications in front of us (and feel free to repeat his work, with 2021 data, before you place your vote).

4. For Wed Sep 8, read through Ch 2 to see what goes on and what is at stake.

5. Work through Nils Exercise 12, and then extend the San Francisco exercise 2.10 in two directions: (a) keep the same prior as in the book, but assume you have 3 numbers, namely 203, 157, 222; (b) invent your own prior. For each case, compute posterior mean, posterior standard deviation, and the 0.05, 0.50, 0.95 posterior quantiles. Then do exercises 2.9, 2.13.