Old Text (Retired)
INTRODUCTION TO BIOENGINEERING STATISTICS
Statistical Methods in Biomedical Engineering
Distributions and Models, Inference, Fundamentals of Regression and Experimental
Design, Bayesian Approach
This course is concerned with the use of statistical inference
for the modeling and analysis of data from a variety of sources under the umbrella of biomedical
engineering research. The orientation is
applied rather than theoretical, but such theory as is necessary for a proper understanding
of the methods will be covered.
Data from engineering, biology, and medical practice will be analyzed during the course.
Coverage will include: design of biomedical studies, sample size problem,
prediction via a statistical model, testing hypotheses, Bayesian methods, etc.
- Software Support
The course will be supported by MATLAB and WinBUGS
- Data and Descriptive Statistics
- Distributions as Models for Observations
- Normal Distribution and Relatives
- Estimation and Testing Statistical Hypothesis
- Bayesian Approaches
- Two Sample Problems
- One- and Two-Way ANOVA. Block Design. Examples of
more complex experimental designs.
- Some Non-parametric Procedures
- Tables and Chi-Square Theory
- Regression Linear, Logistic and Poisson
- Case studies