Mathematics

Statistics 564

Theory of Probability

Fall 2019

Course Homepage

 

Course syllabus.

 

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

 

Overview.

In the Theory of Probability, we shall be using our previous knowledge of calculus and linear algebra to consider the central issues in the "science of uncertainty". The mathematical development of these ideas will be useful in a variety of human endeavors and serve as essential background for productive work in statistics – probability's sister discipline.

 

Goals.

 

 

Day to Day Operations. 

The class meets both online and on Tuesdays and Thursdays from 11:00 AM to 12:15 AM in room 404 of the Physics Building. Our text is Statistical Inference (Second Edition) by George Casella and Roger L. Berger. We will cover most of the material in the first 5 chapters 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 907 541 7171.

 

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 math.arizona.edu.

 

The class has a teaching assistant Sara Bredin. Sarah's office is room 723 of the Mathematics building and her email is bredins at email.arizona.edu

 

 

instructor

email

office hours

location

Joe Watkins

jwatkins at math.arizona.edu

Tuesdays 1:30 to 3:00

Thursdays 1:30 to 3:00

522 Mathematics

522 Mathematics

Sara Bredin

bredins at

email.arizona.edu

Mondays 9:00 to 10:30

Wednesdays 9:00 to 10:30

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 Tuesday, December 17 from 10:30AM to12:30PM.

 

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 Monday 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

 

 

number

points

total

problem sets

12

25

300

midterm exams

2

100

200

final exam

1

200

200

total

 

 

700

 

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