620-202 Statistics

Passing 620-202 precludes subsequent credit for 620-152 or 620-160.

620-201 or 620-205.

This subject introduces the theory necessary to understand modern statistical inference and statistical computation. It demonstrates how many commonly used statistical procedures arise as applications of a common theory. Students will develop the ability to fit probability models to data by both estimating and testing hypotheses about model parameters.

This subject demonstrates the importance of the underlying mathematical theory of statistics and the use of modern computer software. Topics include random samples and sample characteristics; desirable properties of estimators; methods for the estimation of parameters of probability distributions, including maximum likelihood estimation; confidence intervals and prediction intervals; theory and application of hypothesis tests; introduction to distribution free methods and goodness of fit tests, correlation and regression; the analysis of one-way and two-way classifications and introductions to experimental design and general linear models.

Up to 30 pages of written assignments due during the semester (20%); a 45-minute computer laboratory test held mid-semester (10%); a 3-hour written examination in the examination period (70%).