An Introduction to Bayesian Computing and Techniques

Dr. Peter Congdon

Aim of Course:

Participants in this course will learn why Bayesian computing has gained wide popularity, and how to apply Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using WinBUGS software. Participants will learn how to use WinBUGS software, use it to estimate parameters of standard distributions, and implement simple regression models.

See also: Introduction to Bayesian Statistics (which ideally should precede this course) and Bayesian Regression Modeling via MCMC Techniques(which ideally should follow this course.)

Who Should Take This Course:

Statistical analysts and consultants who need to make decisions (or advise decision-makers) via a process that incorporates domain-specific information -- not simply abstract and arbitrary statistical rules.

For those enrolled in a Program of Advanced Statistical Studies, this is a required or elective course in the following Programs:

• Biostatistics (epidemiology) - elective
• Statistics for Social Sciences - elective
• Statistics for Environmental Science - elective

Course Program:

The course is structured as follows:

The Instructor:

Dr. Peter Congdon is a Research Professor in Quantitative Geography and Health Statistics at Queen Mary University of London. He is the author of Bayesian Statistical Modeling, Applied Bayesian Modeling, and Bayesian Models for Categorical Data, all published by Wiley, as well as numerous articles in peer-reviewed journals. His research interests include statistical modeling of spatial variations in health and health services.

Organization of the Course:

The course takes place over the internet, at statistics.com. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor. The course is scheduled to take place over 4 weeks, and typically requires 15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.

Certificates and Grades:

You may be interested only in learning the material presented, and not be concerned with grades or certificates. Or you may be enrolled in a statistics.com Program in Advanced Statistical Studies that requires demonstration of proficiency in the subject, in which case your work will be assessed for purposes of issuing a grade. Or you may require only a "Certificate of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's). As you begin the class, you will be asked to specify your category.

Credit:

This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a certificate will be issued by statistics.com, upon request.

Dates:

Sep. 24 - Oct. 22, 2010
Click here to be notified of future course offerings.

Participants gain access to the online materials on the first day of the course, and typically spend about 15 hours per week (at their convenience). You retain full access to course materials, including discussion board, for two weeks after the course closing date.

Level:

intermediate

Prerequisite:

The equivalent of Introduction to Statistics 1: Inference for a Single Variable, and Introduction to Statistics 2: Working with Bivariate Data (and, if necessary before these courses, Introduction to Statistics for Beginners or Survey of Statistics for Beginners).

For additional information about course prerequisites, click here. Participants should also be familiar with introductory Bayesian statistics, such as the material covered in "Introduction to Bayesian Statistics."

Course Text:

Extensive course notes are provided, and the course may be followed without purchasing a text. For a more in-depth experience, and for those who require a book for reference, we recommend Bayesian Data Analysis, by Gelman et al (2004), published by CRC Press. It can be ordered here or to receive a 20% discount from CRC Press, you must use this discount form.

If you already have Bayesian Modeling Using WinBUGS, by I. Ntzoufras (2008, Wiley), that book is also a useful companion to this course, especially for Lesson 2. It can be ordered from Wiley by clicking here. Wiley typically offers statistics.com customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount -- try calling your regional Wiley representative.)

Software:

The course will be based on the freeware WinBUGS, fitting distributions to datasets. Click here for more information.

Registration:

Register Online - $499
Register Online (academic) - $399 (you must be affiliated with a college, university or high school)

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Note: Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.

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