Information

Statistics plays an important role in our lives. Successful statistical data analysis relies increasingly on using computers. As datasets and dimensionality increase in size the computational element of data analysis takes on a critical role. In these cases, statistical inference requires carefully crafted solutions that are computationally efficient and numerically accurate.

This is an introductory course in computational statistics. As such, it will cover basic concepts from both computer science as well as statistics. The course has several broad aims:

• Introduce the students to the algorithmic way of thinking.
• Teach the students basic data structures and algorithms.
• Introduce the students to C and R, basic programming tools that can be used to implement new statistical (and other!) algorithms from scratch or to incorporate them with already available routines.
  • Develop students' intuition for when each tool is appropriate.
• Expose students to statistical problems requiring significant computation.

In addition to the predetermined list of topics, students will have a chance to get additional experience by competing a medium-scale programming project.

47822 STAT 59800 - SK1 (598G Lecture)
47998 STAT 59800 - SK2 (598G1 Lab)

Monday, Wednesdays, and Fridays, 12:30-1:20pm, B286 Beering Hall

Monday 4:30-5:20pm, B282 Beering Hall

• Instructor Sergey Kirshner (email: skirshne)
• Teaching Assistant Ashwin Varma Anjeri (email: avarmaan)

• Sergey Kirshner: Mondays 3:30-4:30pm in HAAS 118 or by appointment
• Ashwin Varma Anjeri: Tuesdays 8:30-9:30am in HAAS 174 or by appointment

fall-2011-stat-59800-sk1@lists.purdue.edu

No required textbook. We will draw on several references throughout the course. In addition, material will be supplemented by lecture notes.

An introductory course on probability and inference (e.g., STAT 516 and STAT 517) is required; basic course on linear algebra (e.g., MATH 511) is required; some prior programming and debugging experience is required (not necessarily in C or R). Please see the instructor early if unsure of your preparation.

For grading, policies, and what to expect, please read the syllabus. Some of the additional questions are answered in FAQ.