2019-2020 Graduate Course Catalog [ARCHIVED CATALOG]
Applied Statistics, MS
Pinyuen Chen, Advisor
Eddie Bevilacqua, Pinyuen Chen, Peng Gao, Susan H. Gensemer, Vernon L. Greene, Chihwa (Duke) Kao, Hyune-Ju Kim, Yingyi Ma, Jan Ivar Ondrich, Steve Stehman, Raja Velu, William Volterman, Janet Wilmoth, Lianjun Zhang
A graduate program in applied statistics leading to a master’s degree is administered by the interdisciplinary Statistics Program. This program includes professors from computer and information science, education, engineering, management, mathematics, psychology, and the social sciences, among others. This program is distinguished from other graduate programs in statistics by its emphasis on applications. The interdisciplinary program in statistics is based in the College of Arts and Sciences, but welcomes students from all schools and colleges at Syracuse University. Included among these may be students who are pursuing other degrees, but might wish also to pursue the M.S. degree in statistics.
All applicants are expected to have a basic foundation in statistical training that includes one course in introductory statistics, one course in regression analysis, and four courses in applications areas. Graduate Record Examination scores, or their equivalent, and performance in a student’s undergraduate degree program will be carefully evaluated.
Applicants who are not currently enrolled in any program at Syracuse apply for admission to the Applied Statistics Master’s degree program by March 15. Students who are currently enrolled at Syracuse University should contact Professor Pinyuen Chen at email@example.com for further information.
Student Learning Outcomes
1. Basic Probability: Concepts and skills in working with basic probability formulas
2. Working knowledge of one computing technique from the list: MATLAB, MINITAB, R, SAS, and SPSS and the interpretation of its computing outputs
3. Data analysis ability in one of the following subjects: regression analysis, design of experiment, survey sampling, contingency table, engineering statistics, stochastic processing, and time series analysis.
4. Statistical application in one of the following areas: biology, computer science, earth science, environmental science, communications, economics, engineering, forestry, geography, public affairs, political science, management, psychology, sociology, and social work
The master’s degree in applied statistics requires completion of 33 graduate credits. Each candidate must submit a coherent program of 11 courses beyond the bachelor’s degree, subject to the following requirements.
Within the first semester after admission to the degree program, the students will plan their course of study in consultation with their advisors and submit it for approval to the Statistics Program Director.
In order to graduate, a student must earn (1) at least a 3.0 grade in each of the four core courses, (2) a GPA of 3.0 or better in this program of study leading to the M.S. in applied statistics, and (3) no more than two Cs in his/her statistics program coursework.
The absence of either a comprehensive final examination or a master’s thesis is compensated for by an additional 3 credits of coursework, represented by STT 690 or STT 750 / MAT 750 , whose objective is to apply knowledge of statistics to some real world problem.
Four Core Courses
All candidates for the degree program must complete the following set of four core courses (12 credits):
Any one of the following courses in regression Analysis:
Four graduate courses (12 credits) are to be chosen from the following list:
Time Series Modeling and Analysis
Stochastic Processes/Markov Processes
Statistical Simulation and Nonstandard Data Analysis
Advanced Probability I and II
Statistical Ranking, Selection, and Multiple Comparisons
The remaining 9 credits, selected in consultation with the student’s advisor, should:
- emphasize statistical applications, or
- involve consulting or advisement about statistical applications.
Master of Science in Applied Statistics