Statistics 566

Theory of Statistics

Spring 2020

Course Homepage


Course syllabus.


Theory of Statistics is a core course for the Graduate Interdisciplinary Program in Statistics and Data Science.



In the Theory of Statistics, we shall continue both calculus and linear algebra along with our background in the Theory of Probability to engage in the coherent body of knowledge provided by statistical theory having an eye consistently on the application of the subject. This approach will allow you to extend your ability to use methods in modern data science beyond those given in the course.


Learning Outcomes.

·      Have a clear understanding of the modern issues that underlay the theory of statistics, both in the classical and the Bayesian approach.

·      Formulate, analyze, and solve problems through analytical and computational techniques and apply them to other disciplines when appropriate.

·      Become capable in the ability to turn the theory of statistics into computational tools for practical application.

·      Understand first steps toward the fundamental questions in modern data science, e.g., for prediction and classification in machine learning

·      Communicate the concepts and the methods developed by the theory of statistics to appropriate external audiences.



Day to Day Operations. 

The class meets both online and on Tuesdays and Thursdays from 12:30 PM to 1:45 PM in room 501 of the Mathematics Building. Our text is Statistical Inference (Second Edition) by George Casella and Roger L. Berger. We will cover most of the material in chapters 6 through 10 of the textbook plus some supplementary material. A summary of the class notes will be available to the students. The schedule of topics, the class notes and the assignments are given in the course syllabus.


The lectures will be capture using zoom technology. Lecture will be both streamed live and recorded with a link on the course syllabus page. The zoom meeting ID is 897 361 7174.


Feel free to stop by my offices, room 522 of the Mathematics building and room S321 of the ENR2 building, calling me at 621-5245 or writing me – jwatkins at


The class has a teaching assistant Zhaoying Lu. Zhaoying's office is room 502 of the Mathematics Building.





office hours


Joe Watkins

jwatkins at

11:00-12:30 Wednesdays

2:00-3:30 Thursdays

522 Mathematics

522 Mathematics

Zhaoying Lu

zhaoyinglu at

2:30-4:00 Tuesdays

2:30-4:00 Fridays

513 Mathematics

513 Mathematics



Use of Software.

We will be doing some software computation using R.  R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R, please choose your preferred CRAN mirror. Other options for software assistance can be found on the resource webpage.


Evaluation of Students.

We shall have 2 proctored midterm exams and a comprehensive final exam on Wednesday, May 13 from 1:00PM to 3:00PM.


Homework is an essential part of any mathematics or statistics course. Homework will be collected weekly. The homework grade will be based on the top 12 homework scores. For the assignment, complete the assigned problems plus at least one of the challenging problems. The Tuesday office hour will be a session to review the challenging problems.


Permission to turn in late homework for credit must be arranged in advance. The grading scheme is






problem sets




midterm exams




final exam









Grades will be given on the usual scale A is 90%-100%, B is 80%-89%, C is 70%-79%, D is 60%-69%, and E is below 60%. If you fail to complete the course due to circumstances unforeseen, then you may qualify for a grade of I, "incomplete'" if all of the conditions are met:



Students should take the time to become familiar with policies and codes of the University, notably the academic integrity policy and student code of conduct. Student with special needs should contact SALT - Strategic Alternative Learning Techniques Center or the Disability Resources Center.


Best wishes to you for a good semester in this course and in all your other activities.


  - Joe Watkins