Students in WPI’s PhD in statistics program tackle the deeper problems in statistics and apply them to real-world applications in academic settings and in industries as diverse as banking and healthcare.

 

As the need for skilled statisticians increases, WPI’s PhD in statistics program offers a rigorous plan for students who enjoy the field’s challenges, who want to forge new paths, and who anticipate solving original problems. The program offers advanced coursework and research in statistics while imparting critical-thinking and problem-solving skills.

Students in this interdisciplinary program work closely with accessible faculty and often collaborate with researchers in data science, bioinformatics and computational biology, engineering, and business. Students demonstrate their competency at gathering vast amounts of numerical facts (data), evaluating it, and translating or presenting the findings and results for applications in various fields.

The knowledge gained in this program provides real-world opportunities for careers in data-driven industries. Companies use enormous amounts of data to help develop more targeted products. The healthcare industry has great need for statisticians who can help develop new drug technologies or conduct clinical trials. Students are supported in research that will solve puzzles and patterns in big data.

Statistics PhD

Curriculum

Students entering the program with a BS must successfully complete 90 semester hours of graduate work (students with an MS must complete 60 semester hours). At least 30 semester hours must be spent in dissertation research. Full-time residency at WPI is required for at least one continuous academic year of graduate work. 

  • General Courses (credited for students with MS), 30 credits
  • Research Preparation Phase, 24-30 credits
  • Research-related Courses or Independent Studies, 9-18 credits
  • PhD Project, 1-9 credits
  • Extra-departmental Studies, 6 credits
  • Dissertation Research, at least 30 credits
  • General Comprehensive Exam
  • PhD project
  • Preliminary Examination
  • PhD Dissertation

Students entering with a BS must choose six statistical and mathematical courses from those listed below:

Statistical Courses

MA540 Probability and Mathematical Statistics I

MA541 Probability and Mathematical Statistics II

MA542 Regression Analysis

MA543 Statistical Methods for Data Science

MA546 Design and Analysis of Experiments

MA547 Design and Analysis of Observational and Sampling Studies

MA548 Quality Control

MA549 Analysis of Lifetime Data

MA550 Time Series Analysis

MA552 Distribution-free and Robust Statistical Methods

MA554 Applied Multivariate Analysis

MA556 Applied Bayesian Statistics

MA584 Statistical Methods in Genetics and Bioinformatics

Mathematical Courses

MA502 Linear Algebra

MA503 Lebesgue Measure and Integration

MA510 Numerical Methods

MA514 Numerical Linear Algebra

MA528 Measure Theoretic Probability Theory

You may consider completing approved independent studies work in advanced mathematical statistics, advanced multivariate statistics, advanced survey sampling, advanced linear model, generalized linear model, advanced Bayesian statistics, advanced time series, advanced measure-theoretical probability, or advanced statistical genetics.

Research

Faculty Profiles

Zheyang Wu
Associate Professor
Mathematical Sciences

Professor Wu's research interest lies in applying the power of statistical science to promote biomedical researches. In statistical genetics, he is developing novel statistical theory and methodology to analyze genome-wide association (GWA) data and deep (re)sequencing data to hunt new genetic factors for complex human diseases. In epigenetics, he is studying gene expression regulation mechanisms through chromatin interaction, and RNA silencing pathways in the developmental stages of germ-line cells.

Jian Zou
Associate Professor
Mathematical Sciences

Professor Zou's research focuses on financial time series and spatial statistics with applications to epidemiology, public health and climate change. His most recent research on statistical theory and methodology addressed a wide range of challenges including high dimensionality, complex dependencies, and space and time variations. His research in high-frequency financial data tackled problems with high dimensionality, which is currently a hot topic in statistics.

Buddika Peiris
Assistant Teaching Professor
Mathematical Sciences

Teaching is an art. It is something you develop within yourself. It needs hard work, time, creativity and dedication. Giving clear and understandable lectures, facilitating group activities, and interacting with students are all important parts of my teaching. My objectives as a statistics educator are: (1) to teach students about statistical tools and how to use them correctly, (2) to expose students to the structure of statistical analysis, and (3) to teach students how to communicate statistical results and concepts to a variety of audiences.

Getting Involved

Getting Involved

Graduate students find a welcoming, diverse, and active community at WPI. The vibrant graduate student government acts as the voice of grad students, whether they are taking courses on campus or from a remote location.

WPI Walkway

After Graduation