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M.S. in Applied Statistics

General Information

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.

Master of Sciences 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 government, health science and services, industry, and management.

Applicants should apply for admission to the Applied Statistics Master’s degree program by March 15.


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.

Where are the career opportunities?

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:

Vast career opportunities can be found at:

Who will you become after?

Upon completion of 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.

What background is needed for the program?

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.

Masters of Science Requirements

Applicants not currently enrolled in any program at Syracuse should use the online application by March 15.

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, whose objective is to apply knowledge of statistics to some real world problem.

Core Courses (12 credits)

  • MAT 521: Introduction to Probability and Statistics
  • MAT 525: Mathematical Statistics (or MAT 652)
  • One of the following in regression analysis :
    • MAT 654
    • PSY 757
    • MAS 766
    • APM 630 [1]
    • SOC 714
    • ECN 621
    • PPA 810
  • STT 750 / MAT 750: Statistical Consulting [2]

[1] Courses with an APM prefix are offered by the SUNY College of Environmental Science and Forestry

[2] For those students who do not include STT 750/MAT 750 in their programs of study, they should take STT 690: Independent Study (to be taken toward the end of the program of study; its objective is to apply knowledge of statistics to some real world problem).

View the course catalog link in the Course Catalog link box to the right.

Previous and current students:

  • Jesse Lecy received our Master’s degree in Applied Statistics in 2009 and a Ph. D. degree in Social Sciences in 2010. He started a job in the Andrew Young School of Policy and Management at Georgia State University in Fall 2010.

Jesse said: “My undergraduate work was in critical studies so I did not have strong quantitative training, although I increasingly found myself confronted with literature in economics and policy that required a high degree of mathematical literacy. The Masters in Applied Statistics gave me a way to bring rigor to by studies and integrate my research interests in nonprofits and economic development. In many ways, statistics is the lingua franca of modern social sciences - if you understand statistics you can access research across a broad array of disciplines that is otherwise indecipherable. This is not to preference quantitative research over qualitative, but good qualitative research makes the subject accessible without specialized training whereas quantitative research becomes incomprehensible without a strong background in the subject. The degree has enhanced my research and has no doubt strengthened my profile as a job candidate. I believe that the masters in statistics set me apart from other similar candidates.”

  • Ying Lin received her Master’s degree in Applied Statistics and Ph. D. in Electrical Engineering from Syracuse University in 2006 and 2007, respectively. She was an Assistant Professor in the Department of Electrical and Computer Engineering at State University of New York at New Paltz from 2007 to 2009. She joined the faculty of Engineering Technology at Western Washington University in 2009 and she is an Assistant Professor there.

Ying said “The Applied Statistics course work at Syracuse University has been very beneficial to both my research and teaching. I currently teach Engineering Statistics and Wireless Communication Systems courses. The foundation built through my graduate study of Applied Statistics strengthens my understanding and delivering of the course materials. Statistics and probability theory are indispensible to my research work as well. My interest has been using classical and advanced statistical signal processing techniques to solve engineering problems in wireless sensor network and wireless communication systems.” She also said: “In summary, my education experience in Applied Statistics greatly facilitates my career.”

  • Mark Prince received the Master’s degree in Applied Statistics and a Ph. D. degree in Psychology in March 2014. He is currently a Postdoctoral Associate Research Institute on Addictions.

After receiving a BS degree in Psychology from Columbia University, he moved to San Diego, CA to work with professors at UC San Diego and San Diego State University in addictive behaviors. The completion of a Master's thesis at San Diego State gave him further insight into the necessity of advanced statistical training in his academic and career goals. Mark came to Syracuse University in 2007 and finds that the pairing of clinical psychology and applied statistics to be extremely beneficial for his goals. Mark said: "I believe that without adequate training in both fields my research would be lacking in depth and impact. Further, as many psychological constructs are difficult to measure and change often across time advanced statistical training is imperative to accurately capture and describe the phenomena of interest. Finally, I believe that my statistical training will set me apart from my peers in the Clinical Psychology program and help me to secure a job in my desired field of study."

Program Faculty