Instructor: |
Merlise Clyde |
---|---|

Email: |
clyde@stat.duke.edu |

Office: |
223E Old Chemistry Building |

Office Hours: |
Mon 11-12 or by appointment |

Teaching Assistant |
Debdeep Pati |
---|---|

Email: |
db55@stat.duke.edu |

Office Hours: |
211A Old Chem, see SECC Schedule for times |

**Lecture**: M W 2:50 -4:05 SocSci 111

**Lab**: Tu: 1:15-2:30 Old Chem 01

**Course Description:** Principles of data analysis and advanced
statistical modeling. Bayesian inference, prior and posterior distributions, hierarchical models, model checking and selection, missing data, stochastic simulation
by Markov Chain Monte Carlo using WinBugs and R.

**Prerequisites:** Statistics 104, Statistics 114, and Statistics
121/Economics 139D or the equivalent.

**Texts:**

*Bayesian Statistics: An Introduction*(2004) Peter M. Lee (3rd Edition, Publisher Arnold, ISBN 13 9780340814055)*An Introduction to Generalized Linear Models*(2008) Annette J Dobson and Adrian G. Barnett (3rd Edition, Publisher CRC Press, ISBN 978-1-58488-9502)

**Grading:** Course Grades will be based on a Class
Project & Presentation.(30%), Midterm (30%) and Homework (40%). Students are expected
to participate in class discussions based on readings and assignments.

Updated 1/6/2008