Model Classification, Estimation As an Optimization, Errors And Residuals, Standard Statistical Assumptions, Linear Regression - Ordinary and Weighted Least Squares Estimators, Expectation And Variance For Parameters and Predictions, Multiple Linear Regression, Multicolinearity - Detection and Treatment, Non-linear Regression-search Methods, Constraints. Standard Dynamic Models - Sensitivity Equations. Optimal Experimental Design. Interpretation Of The Estimates.

Faculty: Biomedical Engineering
|Undergraduate Studies |Graduate Studies

Pre-required courses

94423 - Introduction to Statistics or 334023 - Int. to Statistics For Biomedical Eng.


Semestrial Information