A Socially Significant Master's Degree

According to the National Center for Education Statistics, the number of jobs in statistics and data science has nearly tripled in the past five years – and the American Statistical Association says there are still not enough statistics graduates to meet this demand. As a student in this program, you will acquire highly marketable advanced analytic skills for a wide range of challenging and rewarding data-intensive careers in the social, behavioral, and health sciences. In particular, students in this program will:

  • Build a strong foundation in statistical research techniques and apply them to address critical issues in contemporary social, behavioral, health science and policy research.
  • Prepare for a career as an applied statistician and data scientist in the private or public sector, working in fields such as psychology, education, political science, public policy, media research, or healthcare.
  • Prepare for further academic study in a variety of disciplines that require or focus on quantitative analysis.

Key Program Features

Students in this program will have the opportunity to tailor their studies in one of the following three concentrations:

  • Data Science for Social Impact, one of the first degree programs in the world to focus on the real-world challenges of using data to inform policy and practice, prepares students to build research-practice partnerships, become knowledgeable of ethical concerns surrounding data collection and use, and communicate effectively and succinctly research findings and their implications. Students will be well-positioned to work in a wide variety of careers at the intersection of data and society or to pursue doctoral studies in the social, behavioral, or health sciences.

  • Computational Methods provides more rigorous training in methodological theory and development and is particularly appropriate for students who wish to progress to Ph.D. programs in statistics, economics, or computer science.

  • General Applied Statistics offers maximal flexibility, allowing students to customize their programs of study by selecting from a broad set of statistics and related courses. Students from this track will be well-positioned to pursue careers in industry, research, and doctoral programs that are consistent with their coursework and internship experiences.

How you'll learn

Flexible Study

You can complete the degree in three or four semesters of full-time study or up to six semesters of part-time study. If you are entering the program with prior statistical training, you may choose to pursue the accelerated, lower-credit option and enroll in advanced courses at the beginning of the program. Your status as an accelerated student will be determined by transcript review and/or placement exam. Other students with considerable professional experience may be able to reduce or waive the internship requirement with advisement approval.

Rigorous Courses

Courses consist of theoretical foundations, statistical inference, and generalized linear models, causal inference, survey research methods, multilevel modeling, applied statistics electives, and a small number of unrestricted electives. Data analysis projects prepare you to undertake research and make data-based decisions and assessments.

Specialized Concentrations

You will choose course work that prepares you for your career, with specific credits dedicated to thematic concentrations in Computational Methods, Data Science for Social Impact, or General Applied Statistics.

Practical Learning Experiences

You will be able to apply the skills you learn to address policy issues and social problems through an internship and the consulting research seminar. You also will work closely with faculty on research projects.

An Emphasis on Social Change

Our faculty members have worked in policy and advocacy organizations in fields including public health, politics, psychology and psychometrics, demography, sociology, labor markets, and education. They care about using Data Science for Social Good. They are applying data analysis methods and strategies to questions such as:

  • What is the effect of gifted and talented and charter school programs on student achievement?
  • What is the relationship between diet and certain forms of cancer?
  • Do student curricular pathways matter for degree attainment and subsequent labor market outcomes?
  • What are effective strategies for the rehabilitation of stroke patients?
  • What is the effect of maternal employment on children's developmental outcomes?
  • How effective are collaborative learning environments?

What can I do with an MS degree in Applied Statistics?

Our curriculum prepares you for a career as an applied statistician and data scientist in the private or public sector, working in fields such as psychology, education, political science, public policy, media research, and healthcare. You'll also be prepared for further academic study in a variety of academic disciplines that require quantitative analysis.

Program benefits for international students

If you’re an international student, you may be able to work in the United States after graduation for an extended period of time. Most students studying on F-1 visas will be eligible for 12 months of Optional Practical Training (OPT) off-campus work authorization. F-1 students in this program may also be eligible for STEM (Science, Technology, Engineering, or Mathematics) OPT extension, allowing you to extend your time in the United States to pursue degree-related work experience for a total of 36 months or 3 years.

Program taught in:
  • English

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Last updated August 6, 2019
This course is Campus based
Start Date
Sep 2020
Duration
3 - 6 semesters
Part-time
Full-time
Price
1,795 USD
Tuition per point/credit in 2019-20 academic year
Deadline
Feb 1, 2020
Late applications may be accepted if space is available.
By locations
By date
Start Date
Sep 2020
End Date
Application deadline
Feb 1, 2020
Late applications may be accepted if space is available.

Sep 2020

Location
Application deadline
Feb 1, 2020
Late applications may be accepted if space is available.
End Date

Marc Scott, Associate Professor of Applied Statistics