Audience:
Professionals involved in research, risk assessment, quality control and other areas that deal with uncertainty. Representative businesses include health care, pharmaceuticals, insurance, manufacturing, marketing and engineering.

Objectives:
Learn the fundamental concepts of probability and distributions
Understand uncertainty and bias in estimation procedures
Learn the basics of hypothesis testing including power, type I and type II errors
Understand the concepts, capabilities and limitations of correlation and regression

Topics:
Day 1:
Probability and distributions
Estimation of location and variability
Confidence intervals and test of hypothesis
One- and two-sample tests of location for binomial and normal distributions
Distribution free tests

Day 2:
Two sample test of variability
Correlation
Statistical models including simple linear regression
Diagnostic assessments of regression assumptions
Estimation and prediction including confidence intervals

Faculty:
David Morris, Ph. D. , Virginia Tech. Statistical consulting includes agricultural research, food science, exercise physiology, and coal mining. With 14 years of pharmaceutical experience, David is currently Assistant Director of Statistics at Abbott Laboratories and Adjunct Associate Professor of Statistics at Northern Illinois University. He received the Jesse C. Arnold Teaching Excellence Award at Virginia Tech, currently teaches clinical statistics for the Graham School at University of Chicago, and coordinates the Abbott Statistical Fellowship at the University of Cincinnati.

Balakrishna Hosmane, Ph.D., University of Kentucky, associate professor, the Division of Statistics at Northern Illinois University. In addition to statistical consulting on campus, he continues his thirteen-year relationship with Abbott Laboratories. This relationship includes statistical consulting and training for Abbott scientists. He has over 25 publications in statistical journals.