>Teaching>PHP 2510: Principles of Biostatistics & Data Analysis (Fall 2009)
PHP 2510: Principles of Biostatistics & Data Analysis
Update: The second exam will be on Nov 17th.
Course Info
Location: 121 South Main St, Room 241
Time: 9:00 – 10:20 am, Tuesday and Thursday
Instructors:
Tao Liu
Assistant Professor of Biostatistics
Office: 121 South Main St, Room 706
Office Hours: 3:30 - 5pm, Wednesday & by appointment
Joseph W. Hogan
Professor of Biostatistics
Office: 121 South Main St, Room 705
Teaching Assistant:
Jing Zhang
Graduate Student of Biostatistics
Office Hours: 10 - 11am, Wednesday @ 121 S Main St, Rm 231 & 9 - 10am, Friday @ 265 CIT.
Course description (from Banner).
This course is intended to provide a basic foundation in the methods and applications of biostatistics, and is geared toward those whose research or fields of study includes a substantial statistical or quantitative component. Ideally, this course is the first in a two-part sequence (the sequel being PHP 2511 Regression Modeling), designed to provide students in the public health, biological and life sciences with broad-based exposure to modern methods of biostatistical inference, in addition to an understanding of underlying mathematical principles and motivations.
Prerequisites.
No prior coursework in statistics or probability is needed, but working knowledge of collegelevel calculus (derivatives, integrals, exponential and log functions, summations, etc.) is required.
Method of evaluation.
There will be 7-10 homeworks (30%) and three exams (exam I 20%; exam II 20%; and exam III 30%). The lowest grade of homeworks will be dropped. Students should work independently on homework, but discussion on general aspect of the course content is encouraged.
Text books
1. Armitage P, Berry G, Matthews JNS (2002). Statistical Methods in Medical Research, 4th Edition. Blackwell.
2. Acock AC (2006). A Gentle Introduction to Stata. Stata Press.
3. Rice JA (2006). Mathematical Statistics and Data Analysis, 3rd Edition. Duxbury. Note: any edition of this book will be suffcient for the course.
Software Emphasis will be placed on computing with Stata, a statistical software package. Stata is available for those with a Brown account via http://software.brown.edu. Students can also use other software packages.