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INTRODUCTION TO BIOENGINEERING STATISTICS
Statistical Methods in Biomedical Engineering
Distributions and Models, Inference, Fundamentals of Regression and Experimental
Design, Bayesian Approach
 Philosophy

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
 Agenda
 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 TwoWay ANOVA. Block Design. Examples of
more complex experimental designs.
 Some Nonparametric Procedures
 Tables and ChiSquare Theory
 Regression Linear, Logistic and Poisson
 Case studies
