D R A F T
February 11, 2004
Department of Bioinformatics and Biostatistics
MPH Concentration in Biostatistics
Goal
Students completing the MPH with a concentration in Biostatistics will be trained to coordinate research activities involving public health investigators and biostatisticians.
Learning Objectives
Students should develop the ability to:
- Assist in the design of research studies
- Advise on appropriate data collection and data management techniques (storage, retrieval, manipulation, quality control)
- Prepare research data for statistical analysis
- Perform basic statistical data analysis using statistical software
- Facilitate communication between researchers and statisticians with regard to interpretation of data analyses and research findings
- Assist in the preparation of technical papers and research proposals
MPH Courses in Biostatistics
The core on-line course is currently under development (3 credit hours):
- Introduction to Biostatistics (3)
Three additional required courses (9 credit hours):
- Introduction to Statistical Computing (3)
- Applied Statistical Models (3)
- Statistical Methods for Research Design in Health Studies (3)
Electives (6 credit hours), subject to approval of advisor and chair; other SPHIS courses may be used with approval of advisor and chair:
- Probability (PHDA 661)
- Mathematical Statistics (PHDA 662)
- Survival Analysis (PHDA 683)
- Categorical Data Analysis (PHDA 684)
- Clinical Trials I (PHCI 624)
Description of Courses
PHDA 601 - Introduction to Biostatistics (3)
This course is an introduction to descriptive and inferential statistics including descriptive methods and graphing, binomial and Gaussian probability theory, estimation, confidence intervals, hypothesis testing, correlation, and regression. One-, two-, and multi-group parametric and nonparametric methods will be introduced. Sampling distributions covered include the Z, t, F, and Chi-squared distributions.
PHDA new - Introduction to Statistical Computing (3)
This course addresses computational aspects of statistical methods as implemented in commonly used software tools, primarily SAS, but also including SPSS, EPI INFO, and other software as needed. It emphasizes research data management, carrying out and interpreting basic statistical procedures in practice, and how to provide thorough, accurate, and comprehensive documentation of the work performed. Students completing this course will develop the ability to prepare and manage research data for statistical analysis and to perform basic statistical data analyses using statistical software.
PHDA new - Applied Statistical Models (3)
Topics will include linear and multiple regression, analysis of variance, analysis of covariance, logistic regression, survival analysis using Cox regression, and repeated measures. These will be addressed from a practical standpoint, without derivations or other theoretical development. Emphasis will be placed on appropriate use of the different models and interpretation of parameter estimates, etc. Students completing this course will develop the ability to apply statistical methods as implemented in commonly used statistical software and facilitate communication between health sciences researchers and statisticians with regard to interpretation of data analyses and research findings. Pre-requisite: Introduction to Statistical Computing.
PHDA new - Statistical Methods for Research Design in Health Studies (3)
Topics in this course will include sample size calculation, power analysis, randomization, and common prospective and retrospective study designs (including cohort studies, case-control studies, clinical trials, and observational studies), with applications in health studies. Students completing this course will develop the ability to assist in the design of research studies, and assist in the preparation of technical papers and research proposals.