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BTRY6520/STSCI6520 Fall, 2012 Department of Statistical Science Cornell University BTRY6520/STSCI6520: Fall 2012 Computationally Intensive Statistical Methods Instructor: Ping Li Department of Statistical Science Cornell University 1 BTRY6520/STSCI6520 Fall, 2012 Department of Statistical Science Cornell University General Information • Lectures: Mon, Wed 2:55pm - 4:10pm, Hollister Hall 362 • Instructor: Ping Li, [email protected] Office Hours: TBA, Comstock Hall 1192. • TA: No TA for this course • Textbook: No textbook for this course • Homework – About 5-7 homework assignments. – No late homework will be accepted. – Before computing your overall homework grade, the assignment with the lowest grade (if ≥ 40%) will be dropped. – It is the students’ responsibility to keep copies of the submitted homework. 2 BTRY6520/STSCI6520 Fall, 2012 Department of Statistical Science Cornell University • Course grading: 1. Homework: 80% 2. Class Participation: 20% • Computing: All the homework assignments will be programming in matlab. The students who register for the class should be willing to learn matlab. The programming assignments will be graded on correctness, efficiency (to an extent), and demos. Questions will be asked during the (one-to-one) demos • Labs: In additional to regular lectures, several computing labs will be provided, usually in the evenings. Note that, as there is no TA, this is additional time the instructor will offer to help students. Due to the conflicts with several conferences, a small number of regular lectures will be canceled. 3 BTRY6520/STSCI6520 Fall, 2012 Department of Statistical Science Course Material • Matlab programming. • Basic numerical optimization. • Contingency table estimation. • Linear regression and Logistic regressions. • Clustering algorithms. • Random projection algorithms and applications. • Hashing algorithms and applications. • Other topics on modern statistical computing, if time permits. Cornell University 4 BTRY6520/STSCI6520 Fall, 2012 Department of Statistical Science Cornell University Prerequisite This is a first-year Statistics Ph.D. course. Students are expected to be well-prepared: probability theory, mathematical statistics, some programming experience, basic numerical optimization etc. Nevertheless, the instructor is happy to accommodate motivated graduate students whose are willing to quickly learn the prerequisite material. The instructor will often review relevant material, at a fairly fast pace. 5
