Statistics 453/553: Biostatistics / Bioinformatics



Last Update:    September 13, 2002 at 11:00 a.m.


Time & Location:    MWF 9:00-9:50 pm, in DH1075

Biostatistics Instructor:
                     Dr. Kenneth R. Hess
Office:          MD Anderson Faculty Center, FC2.3030
Phone:          713-794-4157
Email:          khess@odin.mdacc.tmc.edu

Main Text:   Woodward M. Epidemiology: Study Design and Data Analysis. Boca Raton: Chapman & Hall / CRC, 1999.
Suppl Text:   Venables WN, Ripley BD. Modern Applied Statistics with S-Plus. 3rd ed. Springer, 1999.

Bioinformatics Instructor:
                      Dr. Marek Kimmel
Office:
Phone:
Email:          kimmel@stat.rice.edu

Main Text:   Ewens WJ, Grant GR. Statistical Methods in Bioinformatics. Boca Raton: Springer, 2001.
 

Teaching Assistants:
                      Jason Gershman
Office:           DH 1041
Phone:           6057,    (713-348-6057)
Email:          jgersh@stat.rice.edu

                      Meichun Ding
Office:           DH 2089
Phone:           3684,    (713-348-3684)
Email:          meichund@stat.rice.edu
 


Course Description:  This course is designed to provide an introduction to the analysis of biomedical and epidemiological data.
It will focus on univariate and bivariate analyses for one sample and two sample problems.  Because this is primarily a course for
statistics majors, the applied methods will be related to theory whenever practical.  Emphasis will be placed on the similarity
between various forms of analysis and reporting results in terms of measures of effect or association.  Emphasis will also be given
to identifying statistical assumptions and performing analyses to verify these assumptions.  Because effective communication is
essential to effective collaboration, students will gain experience in presenting results for statistically naïve readers.

Course Prerequisites:  STAT 310 or equivalent (undergraduate probability and statistics)


Computing:  Weekly homework will involve statistical analyses that will often require access to sophisticated statistical software.
In general, students may use the software of their choice.  However, a few assignments may require S-PLUS, and computing
instructions, when given, will be in S-PLUS.

Assignments:  Weekly homework will be a mix of data analysis, computer simulations, report writing, and answering questions
relating to relevant statistical theory and methods.  Some homework will be individual assignments and some group assignments.
Students are encouraged to seek help from the instructor or other students as to the methods of solution, but the submitted report
should reflect only the students' work.  Reports will be written legibly (or typed), understandable to a statistically naïve reader, and
grammatically correct.


Grading:

 60 %    Homework

 30 %    Final

 10 %    Oral Participation


S-Plus Functions:

blip

dist.expl

dot.plot

 ztest1

 perm.test.2

 bootstrapping code

 binom.ci

 prop.est, prop.est2

 sm.survival

 pehaz

 kernhaz

 glm.sum

 event.chart.lite


Datasets:

Homework 2:  Scottish Heart Health Study


Misc. Links:

 Schedule of Topics

 List of Errata from Woodward's Text
 


Any student with a disability requiring accommodations in this course is encouraged to contact the professor after class or during office hours.  Additionally, students should contact Disability Support Services in the Ley Student Center.

Send problems or suggestions to mlecocke@stat.rice.edu