Math 563: Mathematical Statistics
Syllabus  Course Overview
Time&place 
The class meets 10am11:15am MW Location: 
Description  Theory of sampling distributions; interval and point estimation, sufficient statistics, order statistics, hypothesis testing, correlation and linear regression; introduction to linear models. 
Goals 
(1) Develop proficiency in the concepts listed above. (2) Develop good habits of understanding, communicating, and writing statistical analyses. 
Prerequisites 
MATH 475 Probability (or MATH 540 Probability).

Textbook 
Statistical inference, 2nd edition, by George Casella nad Roger L. Berger.

Software  Some of the assignments in this course will involve the use of statistical computing systems. No previous experience with computer programming is assumed, but I expect that you are able and willing to familiarize yourself with the use of the program of your choice.
You can use the JMP software which is available to students in IIT labs. The instructor's software of choice for this course will be R. 
Instructor  Sonja Petrović
Office: RE (formerly E1), 111a Office hours: Mondays and Wednesdays 11:45am12:45pm. econtact: The best way to ecommunicate with the instructor is via Piazza  it has already been set up so that you can log into it from Blackboard directly. After the initial setup, you will be able to log in to Piazza without going through Blackboard. If you must email, please use Sonja.Petrovic@iit.edu and put the course number in the subject line. Your message will generally be answered within 48 hours. 
Graduate assistant  The graduate assistant for this course is Xiao Huang, who will hold office hours Thursdays 3:304:30pm at the usual applied math graduate TA office E1129. econtact: The best way to contact the TA is to post a note on Piazza. For particular homework grading inquiries: xhuang23@hawk.iit.edu@hawk.iit.edu. 