BMI 531 Probability & Statistical Inference

Credits: 3
This course will introduce fundamental concepts underlying statistical data display, analysis, inference and statistical decision making. The topics include presentation and description of data, basic concepts of probability, Bayes theorem, discrete and continuous probability distributions, estimation, sampling distributions, classical tests of hypotheses on means, variances and proportions, maximum likelihood estimation, Bayesian inference and estimation, linear models, examples of nonlinear models and introduction to simple experimental designs. One of the key notions underlying this course is the role of mathematical modeling in science and engineering with a particular focus on the need for an understanding of variability and uncertainty. Examples are chosen from a wide range of engineering, clinical and social domains.

Graded: A-F
May be taken only once for credit
Also offered as: BMI 631