Math 5080-2: Statistical Inference I. Fall 2015



Schedule: Meets 6:00--7:30 MW, 8/24 to 12/9 except for 9/7, 10/12, and 10/14 in LCB 225. PhD students may want to register under the number 6824.

Instructor: S. Ethier (Prof.), 581-6148, ethier@math.utah.edu.

Instructor office hours: 2:00--2:50 and 4:35--5:00 MW, JWB 119. Other times are available by appointment.

Prerequisite: Math 5010, Introduction to Probability. (This is essential!)

Text: Introduction to Probability and Mathematical Statistics, 2nd Ed., by Bain and Engelhardt.

Topics covered: Estimation theory. We will review some probability topics (Chapters 6 and 7) and cover sampling distributions, point estimation, sufficiency and completeness, and interval estimation (Chapters 8-11). Math 5090 will deal with hypothesis testing and linear models.

Grades: Based on weekly 15-minute quizzes (20%), two one-hour midterm exams (25% each), at about 6 and 12 weeks, and a final exam (30%). The dates of the midterms will be confirmed at least a week in advance and posted on this page. The final exam is scheduled for Monday, Dec. 14, 6--8 pm. Early exams are never given.

Homework/Quizzes: Assigned problems will be posted on this webpage on Thursdays with solutions posted on Canvas by the following Tuesday. Because these solutions can probably be found on the Internet, you will not have to turn in your work. But you should attempt these problems before looking at the solutions, because a quiz will be given on Wednesday to test your understanding of the material. Your two lowest quiz scores will be dropped before averaging, to allow for up to two absences. There are no make-up quizzes.

Exams: Exams can be made up if there is a very good justification and if arrangements are made in advance, but this is rare. (Phone the department office before the exam begins to give notification if the instructor is not available; 581-6851.) Students with disabilities can take exams at the CDS the next day.

Expected learning outcomes: The student who successfully completes the course will be conversant with the basics of estimation theory, including such topics as transformations of densities, order statistics, asymptotic normality, sampling distributions, chi-squared, t, and F distributions, maximum likelihood estimation, sufficiency, minimum variance unbiased estimation, and interval estimation. This will provide enough preparation for Math 5090 (Statistical Inference II, mainly hypothesis testing).


Monday, December 21, 7:30 pm. Grades have been posted to CIS.