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Statistics 212 –
Statistical Methods III |
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Instructor: |
Dan Gillen Assistant Professor Department of Statistics Office: 2226 Computer Science III Telephone: 949.824.9862 E-mail: dgillen@uci.edu WebPage: http://www.ics.uci.edu/~dgillen Office hours: Tuesday
& Wednesday11:00-12:00, and by appointment |
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Lectures: |
Monday and Wednesday, 3:30-4:50, Room: ICS 243 |
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Discussion: |
Tuesday, 2:00-2:50, Room: BH 1423 |
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Prerequisites: |
Statistics 211
(Statistical Methods I) or equivalent; or permission of instructor |
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Description: |
This course will provide cover regression methods (theory
and application) for correlated data, with an emphasis on longitudinal data.
Correlated data occurs extensively in both observational and experimental
studies, as well as in industrial applications. The course will focus on both
theory and application of methods for data analysis. Problems will be
motivated from a scientific perspective. |
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Required
Text: |
Applied Longitudinal Data Analysis by Fitzmaurice G., Laird,
L., and Ware J. Wiley Series in Probability and Statistics. 2004. |
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Recommended
texts: |
(On reserve in the science library) á
Analysis
of Longitudinal Data by Diggle, P, Heagerty, P, Liang, KY, and Zeger, S. (2nd
edition). Oxford University Press, 2002. á
Linear
Mixed Effects Models for Longitudinal Data by Verbeke, G and Molenberghs, G. Springer-Verlag, 2000. á
Mixed
Effects Models in S and Splus by Bates, DM and Pinheiro, JC. Springer-Verlag, 2000. |
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Software/Computing: |
Examples that are presented in class are primarily
done using the R statistical package, and it is recommended that R be used
for homework assignments and exams. R is free software which can be
downloaded from the web at http://www.r-project.org/. R can be installed onto Windows, Mac,
or Unix machines. In addition, the student computer lab in CS 364 will have R
loaded onto all Windows machines.
The website also offers many tutorials regarding the use of R. If you wish, it is possible to use
other commercially available software packages such as Splus, Stata, Matlab,
or SAS. |
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Homework: |
There will be
a total of 7 to 8 homework assignments.
Assignments will typically be due 1 to 1.5 weeks from the day they are
handed out. |
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Midterm
Exam: |
Tentatively scheduled for Monday, May 14th. The exam will be in-class
(closed-book, closed-note), and
will cover material through the Thursday, February 15th lecture. |
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Final
Exam: |
The final exam is scheduled for Monday, June 11th. The final exam will be take-home and
will consist of two portions.
The first portion of the exam will consist of short answer questions
similar to a comprehensive homework assignment. The second portion of the exam will be a complete
statistical analysis and report pertaining to a particular scientific
question. The final exam will be
handed out on Wednesday, May 30th and due on Monday, June 11th
by 6pm. |
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Grading: |
Homework: Midterm: Final: |
30% 30% 40% |
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Course
Links: |
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