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Graduate Degree Programs

These course descriptions are not being updated as of August 1, 2016. Current course descriptions are maintained in LionPATH.

Statistics (STAT)

STAT 440 Computational Statistics (3) Topics related to computing in statistics, including numerical linear algebra, optimization, simulation, numerical integration, and bootstrapping.

STAT 440 Computational Statistics (3)

This course introduces many important ideas in statistical computing. Students are expected to possess knowledge of mathematical statistics at the level of STAT 415 and matrices at the level of MATH 220. Students will learn the statistical computing environment called R and use R to implement many of the theoretical computing topics, which include numerical linear algebra, optimization, numerical and Monte Carlo integration, random number generation and simulation, and bootstrapping. Other statistical and mathematical software may be treated briefly, including symbolic mathematics environments like Mathematics and Maple.

General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Spring 2006
Prerequisite: STAT 200 or equivalentSTAT 415, MATH 220

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.


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