Bio696: Deutschman

Syllabus

Spring 2004

Biology 696
ADVANCED TOPICS IN BiostatisticS

Instructor

Dr. Douglas Deutschman

Office

PS 150A (Physical Sciences)

Phone

594-5391

Email

ddeutschman@sciences.sdsu.edu

General Course Information

Prerequisites

One Semester of Biostatistics (500 Level or Higher)

Classroom

LS-126

Typical
Class
Schedule:
Tuesday: 10:00 – 12:20

10:00 – 11:00 Lecture
11:00 – 11:15 Break
11:15 – 12:20 Activity

Thursday: 11:00 – 12:20

11:00 – 11:50 Lecture/Activity
12:00 – 12:20 Discussion

Assignments
and Exams

In Class Assessments
Take Home Assignments
Group Projects and Presentations
Comprehensive Final

 

Office Hours

Tuesday               2:00 - 3:00
Wednesday               1:00 - 2:00

If the scheduled times are not possible for you, please arrange an appointment. The best way to reach me is via email, but feel free to talk with me after class or to phone me at my office.

 

Textbook

None:

The course will be taught with a mixture of chapters from statistics texts and articles from the primary literature. Each module will include a detailed handout with information on concepts, methods, examples, and links to further reading.

Grading and Assignments

The course will include 5 assignments (15% each) and a final exam (25%). Assignments will be open-ended and will focus on the analysis and interpretation of data using the concepts and methods from each module. The final exam will be comprehensive and will focus on concepts, interpretation of varied statistical analyses, and critical evaluation of peer-reviewed publications.

Missed Assignments and Exams

If illness or other serious problem beyond your control prevents you from completing an assignment or exam on time, you are expected to provide some kind of verification of the reason, such as a note from student health services.

Ethical Issues: Freeloading, Plagiarizing, and Cheating

I expect all students to participate in the class. I also expect students to give appropriate credit to ideas from others (group members or published articles and textbooks). I don’t expect any form of cheating to be a problem; so warning you about the consequences may seem unnecessary and perhaps even offensive. Nevertheless, to avoid any possibility of you not recognizing what the consequences are, this is my policy. If you are caught cheating/plagiarizing, you will certainly receive a zero on that particular assignment and you may receive an F in the course. In addition, the event may be reported to campus authorities and may lead to your suspension or even expulsion from the University.

Dropping

The last day to drop is Feb 2nd. After that you must have permission of Kathy Williams, Vice Chair of the Biology Department. Unfortunately, the last day to drop without the risk of penalty comes very early in the semester. If you are unsure what to do, please feel free to talk with me about your concerns.

Tentative Schedule

The General Linear Model - 3 weeks

Development of the matrix formulation of the GLM, the general form of ANOVA and regression models

Generalized Linear Models - 3 weeks

Extension of the GLM to non-gaussian response variables. Emphasis will be given to log-linear modeling and logistic regression as the two most important applications

Multivariate Statistics - 3 weeks

Analysis of multivariate data including multivariate extensions of the GLM (MANOVA), classification (Discriminant Function Analysis), clustering, and ordination (PCA and MDS).

Monte Carlo and Randomization Methods - 3 weeks

Use of bootstrap and jackknife methods for estimating standard errors of custom statistics. Randomization tests.

Space and Time - 3 weeks

Analysis of spatially or temporally structure data. Introduction to spatial statistics, semivariograms, and autocorrelation. Overview of time-series and repeated measures analyses.

 

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