Wharton’s PhD program in Statistics provides the foundational education that allows students to engage both cutting-edge theory and applied problems. These include theoretical research in mathematical statistics as well as interdisciplinary research in the social sciences, biology and computer science.


This program trains students for academic research careers. The foundation is a sequence of courses in probability, mathematical statistics, linear models and statistical computing. The program also encourages study in a cognate area of application. Major areas of departmental research include: analysis of observational studies; Bayesian inference, bioinformatics; computational biology; decision theory; game theory; genomics; high dimensional inference; information theory; machine learning; model selection; nonparametric function estimation; and time series analysis.

Students typically have a strong undergraduate background in mathematics. Knowledge of linear algebra and advanced calculus is required, and experience with real analysis is helpful. Although some exposure to undergraduate probability and statistics is expected, skills in mathematics and computer science are more important.

Sample Program

Years 1 and 2
  • Coursework
  • Examination
  • Research Papers
  • Research Activities
  • Completion of Other Requirements by Field
Year 1

Fall: STAT 930, STAT 961, STAT 970

Spring: STAT 927, STAT 931, STAT 971

Summer: Qualifying Examination and First Year Paper

Year 2

Fall: STAT 972, Two Electives

Spring: Three Electives

Summer: Second-Year Paper

Year 3
  • Directed Reading & Research
  • Admission to Candidacy
  • Formulation of Research Topic
Fall: Directed Study Course, Two Electives, Oral Exam/Thesis Proposal

Spring: Electives or Directed Study Units

Year 4
  • Continued Research
  • Oral Examination
  • Dissertation
Directed Study and Dissertation Research

Electives must include suitable courses numbered 900 and above, when offered.

Core Courses

The program for the PhD Degree includes seven core courses in the 2017-2018 academic year.
STAT 927 Bayesian Statistics
STAT 930 Probability
STAT 931 Stochastic Processes
STAT 961 Statistical Methodology
STAT 970 Mathematical Statistics
STAT 971 Introduction to Linear Statistical Models
STAT 972 Advanced Topics in Mathematical Statistics (may be taken in year 2)

Get the Details.

Visit the Statistics website for details on program requirements and courses. Read faculty and student research and bios to see what you can do with a Statistics PhD.


Statistics Doctoral Coordinator for Enrolled Students
Dr. Paul R. Rosenbaum

Statistics Doctoral Coordinator for Admissions
Dr. Jian Ding

Faculty Members
PhD Students