Mathematics
Statistics 566
Theory of Statistics
Spring 2020
Course Homepage
Theory
of Statistics is a
core course for the Graduate Interdisciplinary Program in Statistics and Data
Science.
Overview.
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 6215245 or writing me – jwatkins at
math.arizona.edu.
The
class has a teaching assistant Zhaoying Lu. Zhaoying's office is room 502 of the Mathematics Building.
instructor 
email 
office hours 
location 
Joe
Watkins 
jwatkins
at math.arizona.edu 
11:0012:30 Wednesdays 2:003:30 Thursdays 
522 Mathematics 522 Mathematics 
Zhaoying Lu 
zhaoyinglu at email.arizona.edu 
2:304:00 Tuesdays 2:304:00 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

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