American University’s Master of Science in Statistics is an excellent way to further your mathematical education, prepare for a doctoral program, or gain the expertise to advance your career. In this program, you will develop proficiency in the development, research, and analysis of quantitative tools to turn ideas into intelligent, informed actions. We offer two different tracks to help you match your course of study to your intellectual and professional goals. The mathematical statistics track is for those intending to pursue a PhD in statistics, while the applied statistics track is perfect for those intending to use their statistical expertise in the workplace. Whichever track you follow, AU’s MS in Statistics is your key to success.
Academic Rigor with a Degree of Flexibility
The Master of Science in Statistics offers rigorous training in statistics while offering you the flexibility to select the program that suits your goals and interests. The 21-credit core will provide a solid statistical foundation in regression, generalized linear models, statistical software, statistical machine learning, and mathematical statistics. You will then pursue either a 9-credit thesis option focusing on research or a 12-credit non-thesis option with additional survey sampling and consulting coursework. Choose the program that fits your academic and professional aspirations.
Knowledgeable Faculty Dedicated to Your Success
The MS in Statistics program prides itself on providing close mentorship and dedicated, individual attention to each student throughout the program. Our experienced faculty members have a wide range of research interests, including the development of statistical methods for evolutionary biology and environmental science, computational statistics, statistics of genocide, and many others areas of specialization. This broad field of expertise will offer you many research options.
Make a Difference in Your Career and the World
Consistently ranked as one of the best cities for job seekers, Washington, DC, is the ideal city in which to study statistics. With job opportunities in the federal government and the private sector, a master’s degree in statistics will open doors for you in the DC area. You can get a head start on your career with an internship at one of the area’s many federal agencies, NGOs, companies, and research institutions. The department’s ties to the National Science Foundation, Environmental Protection Agency, Food and Drug Administration, National Institutes of Health, and other institutions will provide you with research opportunities and connections for future employment. The capital area has a wide array of intellectual and professional opportunities that make DC a great place to learn, work, and live.
Your Success is a Statistical Certainty
With an AU education and the demand for trained statisticians in the DC area, the region with the highest employment of statisticians in the US, your career success is certain. Those pursuing further education continue their studies in PhD programs at respected universities.
With positions available in incredibly diverse fields, you are sure to find a job that matches your skill set and your interests. Recent alumni are employed throughout the DC area and beyond in high-paid, rewarding careers with high-profile employers such as
- Freddie Mac
- Gryphon Scientific
- Marriott International
- US Census Bureau
The Bureau of Labo Statistics reports that Statisticians earn a median annual salary of $87,000.
Read more career informationabout AU's statistics alumni.
Meet An Alum
At American University, Cindy Cook had an internship with the Securities and Exchange Commission and worked on developing an algorithm to optimally predict Cox models for nonlinear survival analysis data. She won the Mathias Student Research Conference Award in 2013 for the Best Oral Presentation in the Sciences by a Graduate Student. Her goal was to pursue a PhD upon graduation. She is currently a PhD candidate in statistics at Pennsylvania State University, where she is studying computational statistics, causal inference, survey sampling, and spatial statistics.