M.S. in Applied Statistics
Syracuse University - College of Arts and Sciences
2 - 3 years
USD 30,294 / per year *
Earliest start date
* additional fees may apply. Cost subject to change
Created in 1989, the Applied Statistics Program at Syracuse University is an interdisciplinary program within the College of Arts and Sciences that includes faculty from computer and information science, management, mathematics, psychology, and the social sciences, among others. The program offers an undergraduate concentration in applied statistics, sponsors a speakers series that hosts visiting statisticians and scientists, and offers a master’s degree in applied statistics.
The Master of Science program in Applied Statistics is a professional degree program administrated by the Interdisciplinary Statistics Program based in the College of Arts & Sciences. The program prepares students to apply cutting-edge statistical methodologies and theory in making meaningful inferences on the measurements obtained from the government, health science and services, industry, and management.
Why do you come to Syracuse University for this degree?
Since our program includes professors from computer and information science, education, engineering, management, mathematics, psychology, and the social sciences, among others, the program is interdisciplinary in nature and it is distinguished from other graduate programs in statistics by its emphasis on applications. By learning a variety of statistical software and through proper training in statistical consulting, our graduates will be able to analyze real-world data correctly and efficiently.
The program is intended for quantitatively oriented students with bachelors' degrees in agriculture, biological sciences, business and management, computer science, engineering, mathematics, physical or social sciences or a related field. This program is also suitable for professionals who handle data in their current positions, and who are mostly interested in the practical side of 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.
The master’s degree in applied statistics requires the 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):
- MAT 521 - Introduction to Probability 3 credit(s) (students with a strong mathematics background are to take MAT 651).
- MAT 525 - Mathematical Statistics 3 credit(s) (students with a strong mathematics background are to take MAT 652).
- STT 750 - Statistical Consulting 3 credit(s) or
- MAT 750 - Statistical Consulting 3 credit(s) For those students who do not include STT 750/MAT 750 in their programs of study, STT 690 should be taken and it should have a significant consulting component.
Any one of the following courses in regression Analysis:
- MAT 654 - Linear Models 3 credit(s)
- PSY 757 - Multiple Correlation and Regression 3 credit(s)
- MAS 766 - Linear Statistical Models I: Regression Models 3 credit(s)
- APM 630
- SOC 714 - Intermediate Social Statistics 3 credit(s)
- ECN 621 - Econometrics I 3 credit(s)
- PPA 810
Four graduate courses (12 credits) are to be chosen from the following list:
Design of Experiments
- PSY 756 - Experimental Design and Statistical Methods II 3 credit(s)
- PSY 853 - Experimental Design and Statistical Tests 3 credit(s)
- APM 620
- PSY 857 - Multivariate Analysis 3 credit(s)
- APM 635
- SOC 813 - Advanced Social Statistics 3 credit(s)
- PAI 721 - Introduction to Statistics 3 credit(s)
- PAI 722 - Quantitative Analysis 3 credit(s)
- PAI 730 - Problems in Public Administration 1-3 credit(s)
- PSC 794 - Advanced Quantitative Political Analysis 3 credit(s)
- MAT 755 - Multivariate Statistical Analysis 3 credit(s)
Time Series Modeling and Analysis
- MAS 777 - Time Series Modeling and Analysis 3 credit(s)
Stochastic Processes/Markov Processes
- MAT 526 - Introduction to Stochastic Processes 3 credit(s)
- ECE 756 - Random Processes 0 credit(s)
Statistical Simulation and Nonstandard Data Analysis
- MAT 653 - Statistical Simulation and Nonstandard Data Analysis 3 credit(s)
Topics in Statistics
- MAT 850 - Topics in Statistics 3 credit(s)
Advanced Probability I and II
- MAT 721 - Probability I 3 credit(s)
- MAT 722 - Probability II 3 credit(s)
Statistical Ranking, Selection, and Multiple Comparisons
- MAT 752 - Statistical Ranking, Selection, and Multiple Comparisons 3 credit(s)
- GEO 686 - Quantitative Geographic Analysis 3 credit(s)
- ECN 620 - Foundations of Econometrics 3 credit(s)
- ECN 622 - Econometrics II 3 credit(s)
- ECN 720 - Topics in Econometrics 3 credit(s)
- STT 750 - Statistical Consulting 3 credit(s)
- MAT 750 - Statistical Consulting 3 credit(s)
The remaining 9 credits, selected in consultation with the student’s advisor, should:
- emphasize statistical applications, or
- involve consulting or advisement about statistical applications.
Upon completion of the program, students will be able to:
- Implement trending statistical methods to solve problems;
- Analyze large data set using various statistical packages;
- Participate and work in problem-solving teams;
- Present results verbally and in writing.
Applied statisticians are highly sought in diverse fields like government agencies, pharmaceutical companies, consulting firms and financial companies. Two recent articles revealed the fact that applied statisticians are in great demand:
- April 8, 2010, Wall Street Journal: New Hiring Formula Values Math Pros: Region's Employers Seek Statistical Experts Over Computer-Science Generalists
- August 5, 2009, New York Times: For Today’s Graduate, Just One Word: Statistics.
Vast career opportunities can be found at:
- Sloan Career Cornerstone Center: Career planning resources in statistics
- American Statistical Association: Career in Statistics