Instructor:
Jean Gao

Email:
gao@ uta.edu

Office:
ERB 538, phone: 817-272-3628.

Office
Hour: Tue
and Thu, 12:30 - 1:30 pm or by appointment.

TA Info:
Please check the blackboard

The objective of this course is to provide
students the basic data analysis and modeling concepts and
methodologies using probability theory. Basic statics concepts and
probability concepts will be covered. Fundamental data analysis
and hypothesis techniques will be covered. Further data modeling
methodologies such as Hidden Markov Models and Bayesian networks
will be introduced.

Students
successfully completing this course will have gained a solid
understanding of probabilistic data modeling, interpretation, and
analysis and thus have formed an important basis solve practical
statistics and data analysis related problems arising in broad
computer science and engineering, and daily life.

**Prerequisites:**

All
students are expected to have a background in basic probability,
Calculus, and Algebra before attending this course.

*Probability and Statistics
for Computer Scientists*, by Michael Baron, Chapman and
Chapman and Hall/CRC; 2 edition (August 5, 2013), ISBN-10: 1439875901.

1. *Art of Computer Systems
Performance Analysis: Techniques For Experimental Design
Measurements Simulation and Modeling*, Raj Jain (Wiley; 2
edition, 2015), ISBN:
978-1118858424.

*2. **A Concise Course in Advanced
Level Statistics with worked examples** *(Oxford University
Press; 4th Revised edition, 2014), ISBN:
1408522292.

3. Additional course
materials will be available electronically through the course
website.

Homework (10%): There will be about 5~6
HWs. Some of the homework assignments may include small computer
projects. You are free to choose your most comfortable
programming language.

Hardcopy of handwritten or typed HWs are collected physically in
or before class on the due date. Late submissions will not be
accepted.

Exams (75%): There will be three mid-terms, each will cover
approximately one-third of the course materials.

Quizzes (15%): There
will be three 15-minute quizzes .

**Tentative
Major Topics to Be Covered (subjective to change based on
course progress):**

1. Basic probability:

Discrete and
continuous random variables, independence, covariance, central
limit theorem, Chebyshev inequality, diverse continuous and
discrete distributions.

2. Statistics, Parameter Estimation, and
Fitting a Distribution:

Descriptive
statistics,
graphical statistics, method of moments, maximum likelihood
estimation

3. Random Numbers and
Simulation:

Sampling of
continuous distributions, Monte Carlo methods

4. Hypothesis Testing:

5. Stochastic
Processes and Data Modeling:

**Course
Policy:**

Class
Attendance is required.

Cooperative
efforts at understanding the material and the assignments are
encouraged. However, you are required to present your work
that you have completed individually. There will be no make-up
exams or quizzes for this course unless the instructor is notified
IN ADVANCE under extenuating
circumstances.

There will be
extra credit assignments.

**Disabilities Act**

**
**The University of Texas at Arlington is on record as
being committed to both the spirit and letter of federal equal
opportunity legislation; reference Public Law 93112 -- The
Rehabilitation Act of 1973 as amended. With the passage of new
federal legislation entitled Americans With Disabilities Act -
(ADA), pursuant to section 504 of The Rehabilitation Act, there is
renewed focus on providing this population with the same
opportunities enjoyed by all citizens. As a faculty member, I am
required by law to provide "reasonable accommodation" to students
with disabilities, so as not to discriminate on the basis of that
disability. Student responsibility primarily rests with informing
faculty at the beginning of the semester and in providing
authorized documentation through designated administrative
channels.

**Academic Dishonesty**

**
**It is the philosophy of The University of Texas at
Arlington that academic dishonesty is a completely unacceptable
mode of conduct and will not be tolerated in any form. All persons
involved in academic dishonesty will be disciplined in accordance
with University regulations and procedures. Discipline may include
suspension or expulsion from the University. "Scholastic
dishonesty includes but is not limited to cheating, plagiarism,
collusion, the submission for credit of any work or materials that
are attributable in whole or in part to another person, taking an
examination for another person, any act designed to give unfair
advantage to a student or the attempt to commit such acts."
(Regents’ Rules and Regulations, Part One, Chapter VI, Section 3,
Subsection 3.2, Subdivision 3.22)

**Student Support Services Available**

**
**The University of Texas at Arlington supports a
variety of student success programs to help you connect with the
University and achieve academic success. These programs include
learning assistance, developmental education, advising and
mentoring, admission and transition, and federally funded
programs. Students requiring assistance academically, personally,
or socially should contact the Office of Student Success Programs
at 817-272-6107 for more information and appropriate referrals.