STATS 607 - Programming and Numerical Methods in Statistics
Section: 001
Term: WN 2018
Subject: Statistics (STATS)
Department: LSA Statistics
Credits:
1.5
Waitlist Capacity:
99
Advisory Prerequisites:
STATS 425, STATS 426. Computer Programming experience recommended.
Repeatability:
May be elected twice for credit.

This course is ad advanced introduction to modern programming (Part I) and numerical analysis (Part 11) techniques used in statistics, modeling and data analysis. Part I course topics include: basic data structures, structured data formats, iteration and recursion, functional programming, classes and object-oriented programming, memory management, strategies for documenting and debugging code. This part of the course will cover programming fundamentals relevant for research on statistical methodology, and for working with large and complex data sets. Part II course topics include: sorting and binary searches, root finding in one dimension, interpolation techniques, low-dimensional numerical integration, solving triangular systems, basic matrix factorizations (LU, Cholesky, QR), Schur and singular value decompositions, sparse matrices. This part of the course will cover elementary algorithms that are useful for numerical analysis and programming with data.

STATS 607 - Programming and Numerical Methods in Statistics
Schedule Listing
001 (LEC)
P
23454
Open
21
21STATS PhD only
-
MW 4:00PM - 5:30PM
NOTE: Data maintained by department in Wolverine Access. If no textbooks are listed below, check with the department.


ISBN: 9781421407944
Matrix computations, Author: Gene H. Golub, Charles F. Van Loan., Publisher: Johns Hopkins Univ Press Fourth edi 2013
Required
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