STAT 460
Experimental Design & Advanced Data Analysis

First exposure to inferential statistical techniques, in the first statistics course, often leaves the student with a mass of formulas and procedures but only an uncertain sense as to how all these pieces fit into a coherent whole. The primary aim of this course is a deep and practical understanding of the conceptual framework underlying statistical methods. We will cover the traditional topics of the introductory course (one- and two-sample inference), and will expand upon those topics (distributional assumptions, nonparametric alternatives, robustness, power analysis). In the last portion of the course we will introduce the foundational procedures in the Analysis of Variance ("ANOVA"). Pedagogical level of the course is roughly that of a graduate-level research methods course for non-majors.

Daily Review Assignments

The purpose of daily review assignments is to provide timely review and feedback on the basic course concepts and computational mechanics covered each day in class.  This structured regular review facilitates mastery of course material.  Review assignments are due at the beginning of the following class.  They are checked simply for reasonable effort, not accuracy. Daily assignments in this course are more extensive that those in the introductory course (STAT 301). Accordingly, completing them is worth a measurably large portion of the course grade. Daily review assignments are distributed in class.  They are also available from the links below. (Some of the review assignment webpages have links to more detailed solutions, in case you run into difficulty while working on them.)

Homework Assignments

These assignments are longer and more involved than daily review assignments.  Their purpose is to take the basic concepts and calculations of the course (which are reinforced by the daily review) and to apply them to "real world" situations, so you may be able to use the material in the course in your professional and personal life. Homework will not normally be accepted late.