Statistics Courses

taught by Professor Carl N. Morris
Fall 2002


Statistics 210.
Probability Theory and Statistical Inference I.

Catalog number: 2487
Half course (fall term): Tu., Th., 10 - 11:30 a.m.
EXAM GROUP:

Text: by Gut

Course Description: Random variables, their distributions and densities. Families and exponential families of distributions. Expectation. Independence, product spaces, and joint distributions. Types of convergence. Limit theorems (weak and strong laws, central limit problem). Conditional probability and expectation, multivariate Normal distribution, particular examples of conjugate, marginal, and conditional distributions. Inequalities, approximations, and stochastic simulation. Sampling distributions, likelihood function, sufficiency, and information.

Prerequisite: A course in probability and statistics at least at the level of Statistics 110, 111.




Quantitative Reasoning 32, QR-32.
Uncertainty and Statistical Reasoning.

Catalog Number: 2228
Half course (fall term). Tu., Th., 10-11:30, and a weekly section to be arranged.
EXAM GROUP: 12, 13

Text: Seeing Through Statistics by Jessica M. Utts, 2nd edition, University of California, Davis: Duxbury Press, 1999.

Course Description: Individuals continually must make decisions under uncertainty in their personal and in their professional lives. This course develops probability as the appropriate language for describing uncertainty, and it shows how statistical data and planned studies are crucial to evaluating probabilities and associated risks. Students will learn how others actually think about uncertainty and risk, and how better to assess uncertainties in their own lives. Statistical thinking too often is seen as based on arcane jargon and formulae. Students who expect formulas to replace hard, critical thinking will be disappointed in this course. The course introduces basic concepts and the language of probability and statistics, with emphasis on its relationship to quantifying uncertainty for use in daily life, on applying the ideas to real examples, and on understanding statistical reasoning in the media, science, law, and medicine.

Note: Expected not to be offered in 2003-04.