Class Instructor

Name	:	Dr. Arne Bathke
Address	:	875 Patterson Office Tower (POT)
Telephone	:	257-3610
Email	:	arne@ms.uky.edu
Office Hours	:	2:00-4:00 AM on Mondays or by appointment.

Lab Instructor

Name	:	Bob Loos
Address	:	857 Patterson Office Tower (POT)
Telephone	:	257-9202
Email	:	loos@ms.uky.edu
Office Hours	:	2:00-4:00 PM on Mondays.

Course Information

Class time	:	March 7 - May 6, 2005, Lecture MWF 12:00 - 12:50 AM, Computer Lab W 2:00 - 3:50 PM
Class room	:	Lecture CB (Classroom Building) 235, Computer Lab CB (Classroom Building) 307
Textbook	:	G. Noether, Introduction to Statistics the Nonparametric Way, Springer.
Website	:	http://www.ms.uky.edu/~arne/sta673/
		This website will be updated regularly. Please keep checking it for announcements and homework information.

Course Policies Description: This is a 2 credit hour course about nonparametric statistical methods. These are methods that usually require less assumptions than their parametric counterparts, while being almost as powerful. More specifically, topics of STA 673 are envisioned to include inference for population quantiles, sign tests, Wilcoxon tests, Kruskal-Wallis and Friedman tests, Kendall and Spearman rank correlation; goodness-of-fit tests for completely and partially specified distributions, r x c contingency tables, McNemar and Cochran's Q tests for matched proportions; three dimensional tables and tests of partial and multiple associations. The use of computer library routines (SAS) will be discussed. Other special topics may be discussed according to the interests of the class and the available time. Prerequisites: STA 570 or STA 580. Learning Objectives: Upon successfully completing this course, you will be able to - articulate the role of nonparametric statistics in statistical science - apply binomial test methods and explain how the binomial test is the basis for simple nonparametric tests of hypotheses - apply contingency table methods and derive the exact distribution of simple tables - apply rank-based methods of correlation and hypothesis testing and articulate their relationship to better-known parametric methods - apply simple goodness-of-fit-tests - implement all supported methods in SAS Course Goals: Apart from the knowledge of the STA 673 topics mentioned above, the course is intended to enhance analytic and problem-solving skills and the capacity to make wise decisions. Attendance: Consistent attendance is strongly recommended. Each student is responsible for obtaining all material missed when absent. Grading: Your grade will be divided into three parts: Two exams (25% each), and homework (50%). The homework assignments, midterm exam and final exam must be your own work. Late homework will not be accepted (i.e., given full credit) without a university excused absence. Exams: The two exams are scheduled for April 15 and May 2 (Final Exam). Make-up exams will be allowed only in extreme circumstances and are subject to proper documentation. Unless it is an emergency situation, you need to notify me ahead of time either by phone or via email.

Syllabus