Spring 2013:
CSE 5301: Data Analysis and Modeling Techniques

Location: NH 203

Time: Tues/Thursday 2:00 - 3:20pm.

First class: Tuesday , Jan 18
Final exam: Tuesday, May 10th, 2-4:30pm, NH203.

Instructor: Dr. Chris Ding, 529 ERB. Phone: 817-272-7041. Email: chqding@uta.edu
Office Hours: TuTh, 1:00 - 2:00pm (and by appointment).

TA: Miao Zhang, Email: Zhangmiao97@gmail.com
Office Hours: Thuesday/Thursday, 3:30-5:00, ERB 407
All homework/exam grades are checked and given by TA.

Contents and Objectives: This course will cover statistics and data modeling at intermediate level. Contents include probability, random variables, discrete distributions, continous distributions, parameter estimation, compution simulations techniques, stochastic processes: Markov models and Poisson process.

In Spring 2013, about half of time, we will cover advanced topics: hidden Markov model, Bayesian Network and Random Markov Fields.

This course teaches sufficient concepts and skills for students to solve practical statistics and data analysis related problems arising in computer science and engineering, and daily life. This course builds a solid foundation for students later CSE courses such as Artificial Intelligence, Data Mining, Machine Learning, Bioinformatics, Image Processing, Computer Vision, etc.

Prerequisites:
  One semester of probability and/or statistics. One semester of linear algebra.

Course Schedule

Homework

Course Projects

Textbook & References:
Probability and Statistics for Computer Scientists, by Michael Baron, Chapman and Hall/CRC, 2006.
Grades
  • Homework --- 20%
  • Midterm and Final Exams --- 60%
  • Class project and presentation (2-person team) --- 20%

Attendance
  Attendance though not mandatory, but is HIGHLY encouraged. Class participation is important to your grade in the 'Quizzes and Class Participation' component

Americans With 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.