This is the web page for AMS 206 (winter 2018). In what follows DD = David Draper (lecturer; email address draper@ucsc.edu), DK  = Daniel Kirsner (TA; email address dkirsner@ucsc.edu), and BE = Baskin Engineering.

The catalog description for AMS 206 is as follows:

Introduces Bayesian statistical modeling from a practitioner's perspective. Covers basic concepts (e.g., prior-posterior updating, Bayes factors, conjugacy, hierarchical modeling, shrinkage, ...), computational tools (Markov chain Monte Carlo, Laplace approximations), and Bayesian inference for some specific models widely used in the literature (linear and generalized linear mixed models). Prerequisite(s): course 131 or 203, or by permission of the instructor. Enrollment is restricted to graduate students.

• (8 Jan 2018) Announcements will be posted in this section. The first Attachment section below will contain (scanned) PDF copies of the lecture notes, document camera notes and extra notes, as well as case studies and R , Maple  and WinBUGS code; the second Attachment section will contain secure documents, available only by logging into the web page with your CruzID Blue password.
• (11 Jan 2018, revised 24 Jan 2018) Office hours for the class are as follows: M 5-6pm BE 119 (DK); Tu noon-1pm BE 358 (DD); W 5-6pm BE 119 (DK); Th noon-1pm BE 358 (DD); F 4-5pm BE 119 (DK). Please note that both the time and location of DD's office hours had to be changed, to ensure a big enough room (it may be necessary to change yet again for the same reason; watch your email).
• (13 Feb 2018) The new drop-dead due date for uploading your solutions to Take-Home Test 1 at canvas.ucsc.edu is 11.59pm on Tue 20 Feb 2018.
• (16 Feb 2018) The original version of Take-Home Test 1 had two typos in it: in problem 2(B)(iv), the likelihood should have been described as equivalent to a constant times the Γ^-1( n - 1, n y-bar ) distribution, not ( n, n y-bar ), and this resulted in another typo in the table in problem 2(B)(v)(b). This has been fixed in the PDF and LaTeX versions in the attachments below.
• (21 Feb 2018) I've added a Hint to the PDF and LaTeX versions of Quiz 4; the new files are in the attachments below.
• (1 Mar 2018) An example of a likelihood analysis (click on the link right before this parenthetical comment) treating the likelihood as a density, similar to the work in problem 2(B) in Take-Home Test 2, in a recently-published paper in the journal Nature that may offer new insights into the nature of dark matter.
• (2 Mar 2018) The original  version of Take-Home Test 2 had two typos in it -- there was an extra log in equation (6), and the y symbols in Table 1 should have been x -- and I've made the first Calculation problem easier by writing an rdirichlet function for you; the appropriate changes have been made in the PDF and LaTeX versions in the attachments below.
• (11 Mar 2018) If you've ever wondered how people use Bayesian data science to do something practical, such as predicting the results of the men's and women's NCAA basketball tournaments, check out this site (click on the link right before this parenthetical comment) at fivethirtyeight.com: the analysts there are what I would call pragmatic Bayesians, who combine likelihood information from models that predict the results of individual games with prior information based on human expert judgment. Based on your work in this course, you should be able to understand essentially all of the technical details behind how the 538 people make their predictions, which are (year in and year out) among the best available.
• (15 Mar 2018) A resource you may wish to make use of: with sponsorship from eBay and Google, in 2013 I gave a course on Bayesian modeling, inference, prediction and decision-making that consisted of about 60 hours of lectures, all of which were video recorded (you can watch the videos), together with all of the lecture notes, data sets and code: the web page where all of this is stored is here (click on the link right before this parenthetical comment). The eBay-Google course includes some of the material I covered this quarter and a lot of extra material, some of which would be natural in a next course after AMS 206.