THE GRADUATE SCHOOL

Degree Types: PhD in Statistics, MS in Statistics, Ad Hoc MS in Applied Statistics, BA/MS Combined Degree

The Doctoral Program in Statistics and Data Science provides students with comprehensive training in statistical theory, methodology, and the application of statistical methods to problems in a wide range of fields.

Faculty have specialties in diverse areas including statistical machine learning, experimental design, linear models, sample surveys, statistical theory, computational Bayesian inference, bioinformatics and computational biology, and analysis of qualitative data. They have interest and broad experience in the application of statistics to the biomedical sciences, social sciences, law, and public policy.

Students can tailor the program to meet academic interests and career goals, and cross-disciplinary work is encouraged. The program prepares students for careers as university teachers and researchers and as research statisticians in industry, government, and the non-profit sector.

The Department also has a Master’s Program in Statistics and Data Science, for students interested in earning a professional degree or who want to prepare for doctoral study in statistics, data science, or another field with a connection to statistics.

Additional resources:

• Department website
• Program handbook(s)

The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.

The Department offers an Ad Hoc MS degree in Applied Statistics for Northwestern doctoral students in other disciplines including (but not limited to) Economics, Political Science, Sociology, Psychology, Learning Sciences, and Human Development & Social Policy who wish to establish their qualifications in statistics and quantitative research methodology. To participate, students must meet The Graduate School’s eligibility requirements to pursue an ad hoc combined degree, complete the Master of Science in Applied Statistics Degree Program Application, and receive approval from their home department, the Department of Statistics & Data Science, and The Graduate School.

Degree Requirements

Accepted students are expected to take a total of 9 approved courses in a program and complete a culminating project. The 9 courses must be unique from the 9 courses the student will use to satisfy the TGS requirements for the PhD. Double counting is not permitted when satisfying The Graduate School requirements for each credential.

Coursework: Students are typically required to take STAT 320-1 Statistical Theory & Methods 1 and STAT 320-2 Statistical Theory & Methods 2 to provide a foundation in statistical theory. Students with advanced mathematics may take STAT 420-1 Introduction to Statistical Theory & Methodology-1 and STAT 420-2 Introduction to Statistical Theory & Methodology-2 instead with department approval. The remaining 7 courses are selected with the advice and approval of the student’s home department and the Applied Statistics MS program director. Note that the program may be completed entirely from courses taught in the Department of Statistics & Data Science, but may include up to 3 courses from departments other than Statistics. Courses from outside the department must be approved by the Applied Statistics MS program director.

Culminating Project: All Applied Statistics MS candidates are required to complete a culminating activity project using statistics. This project is typically work that will be included in the student’s PhD dissertation, but can also be a stand-alone project. After completing the coursework, students submit a proposal for a culminating project that is reviewed and approved by the Applied Statistics MS program director. Submission of a satisfactory culminating project completes the student’s degree work for the Applied Statistics MS.

Degree Requirements

Statistics MS

Total Units Required: 12-16

Required Coursework

Other MS Degree Requirements

• Examination: pass qualifying examination at MS degree level

Degree Requirements

The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.

PhD

Total Units Required: 15

Required Coursework

Course List

Course	Title
STAT 344-0	Statistical Computing
STAT 350-0	Regression Analysis
STAT 353-0	Advanced Regression
STAT 415-0	Introduction to Machine Learning
STAT 420-1 & STAT 420-2 & STAT 420-3	Introduction to Statistical Theory & Methodology-1 and Introduction to Statistical Theory & Methodology-2 and Introduction to Statistical Theory & Methodology-3
STAT 430-1 & STAT 430-2	Probability for Statistical Inference 1 and Probability for Statistical Inference 2
STAT 440-0	Applied Stochastic Processes for Statistics
STAT 457-0	Applied Bayesian Inference
Electives (300- and 400-level graduate courses in Statistics): at least 4, among which 2 must be 400 level

Other PhD Degree Requirements

• Examinations: qualifying examination taken at the beginning of the second year; prospectus completed by the end of third year
• PhD Dissertation: based on independent research
• Final Evaluations: oral defense of dissertation

En Route Master's

Optional MS Degree for Statistics PhD Students

Students admitted to the PhD program can obtain an optional MS (master of science) degree en route. The MS degree requires 12 courses. Students choose from 300 and 400 level courses offered by the Statistics Department. Required are:

Course List

Course	Title
STAT 350-0	Regression Analysis
STAT 353-0	Advanced Regression
STAT 415-0	Introduction to Machine Learning
STAT 420-1 & STAT 420-2 & STAT 420-3	Introduction to Statistical Theory & Methodology-1 and Introduction to Statistical Theory & Methodology-2 and Introduction to Statistical Theory & Methodology-3
at least 6 more courses approved by the program , among which two must be 400 level STAT elective courses, no more than 3 can be non-STAT courses

For the optional MS degree, students must also pass the qualifying exam offered at the beginning of the second year at the MS level.