Advanced statistical theory and methodology.

Cornell's Ph.D. in Statistics prepares future leaders in statistical research and innovation. Students develop comprehensive expertise in creating and implementing novel statistical methods, proving mathematical properties of statistical approaches, collaborating with researchers across disciplines, and solving complex real-world problems. 

Our graduates excel in academia, industry, and government, combining theoretical depth with practical application. 

Choosing your path: Statistical Sciences at Cornell

Statistics uniquely bridges theory, application, and computation. Our field demands mastery of statistical theory, research design, data analysis, and mathematical principles, alongside strong communication skills. 

The ideal candidate is passionate about statistics and eager to translate complex problems into statistical frameworks while effectively collaborating across disciplines. If you're driven by statistical thinking and its real-world impact, the Field of Statistics offers the rigorous training you seek.

The program provides a 5-year funding package covering tuition, health insurance, and stipend, along with teaching and research assistantship opportunities. Students can join the Statistics Graduate Society and receive regular progress reviews and mentorship to support their academic success.

Building future statistical leaders.

As a TA at Cornell, I have been given opportunities to lead my own Lab/recitation sections, host office hours, and sometimes even guest lecture. Those experiences in interacting with students and their feedback really helped me develop as a teacher.

Irina Gaynanova, Ph.D. ’15
Associate Professor, Department of Biostatistics, University of Michigan

The path to your Ph.D.

Our Ph.D. program in Statistics prepares students for successful careers in academia, industry, and government through a comprehensive curriculum that balances theoretical foundations with practical applications. The program develops statisticians who can collaborate effectively with researchers across disciplines while advancing statistical theory and methods.

Requirements include:

  • Complete required core courses and electives
  • TA for at least two semesters
  • Form a special committee consisting of a chair, field member, and at least one external minor member
  • Fulfill minimum four semesters of residency
  • Pass A and B exams, Q exam if required
  • Submit a dissertation

ACADEMIC PLANNING

While our program has standard course requirements, we recognize and value students' prior academic preparation. With approval from the Director of Graduate Studies, relevant graduate-level coursework from other institutions may fulfill specific requirements, allowing for customized academic paths.

General course requirements: 

Year 1: Fall
STSCI 7170: Linear Models
MATH 6710: Probability I
STSCI 6520: Statistical Computing I

Year 1: Spring
STSCI 6730: Mathematical Statistics I
MATH 6720: Probability II or STSCI 6750: Adv. Prob. for Statisticians

Year 2: Fall
MATH 6740: Mathematical Statistics II or MATH 7740: Statistical Learning Theory

In addition, four (4) elective courses that will need to be approved by their Special Committee Chairperson.

 

ACADEMIC PLANNING

Concentrations Available:

• Biometry

• Decision Theory

• Econometrics

• Engineering Statistics

• Experimental Design

• Mathematical Statistics

• Probability

• Sampling

• Social Statistics

• Statistical Computing

• Stochastic Processes

Student Resources and Support

Our mission is to help you succeed so you can fully participate in the Cornell Bowers experience.

 

Current Student Resources

Program Office

Hear from Alumni

Alumni Perspectives: Sharon Lawner Weinberg ’68, Ph.D. ’71
Alumni Perspectives: Irina Gaynanova, Ph.D. '15
Alumni Perspectives: Charles McCulloch, PhD '80, 2017 Distinguished Alumni