Graduate
M.S. Statistical Computing
The Master of Science degree program in Statistical Computing provides a sound foundation in statistical theory, statistical methods, and in the application of computer methodology to statistical analyses. The program is particularly well-suited for those individuals who have earned an undergraduate degree in mathematics, statistics, or computer science, but is also available to those in other disciplines who wish to develop an expertise in data analysis and statistical computing. The flexibility of the program allows the student to choose a more traditional graduate statistics program or one that is more heavily oriented toward computational statistics. This computing emphasis can be achieved by taking specially designed statistical computing courses offered by the Statistics Department along with selective computer science courses from the Department of Computer Science. A Ph.D. degree with an emphasis in statistics can be obtained through the Department of Computer Science of the Department of Mathematics.
Students entering the graduate program with regular graduate status should have a good working knowledge of at least one programming language, calculus, linear or matrix algebra, and have successfully completed two or more courses in statistical methods. Those students who are not adequately prepared in these areas may need to complete some undergraduate coursework before beginning their graduate work. Most of the graduate courses are offered during the late-afternoon or evening hours to accommodate part-time or working students.
Graduates of the program will be prepared for employment as applied statisticians in industry and government agencies, and as teachers in high school, community colleges or universities. Individuals with graduate degrees in statistics are in high demand and so graduates of our program have been very successful at finding employment immediately after graduation. The program also prepares students for further graduate work leading to a Ph.D. in statistics.
Course Catalog
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