Enhance your studies with a focus on data science.

The Ph.D minor in Statistics is designed for doctoral students seeking to develop strong theoretical and practical foundations in statistical methods and analysis. The Field of Statistics offers three distinct minor options for Ph.D. students.

Theory + Methods
Emphasizes theoretical foundations in probability, mathematical statistics, and advanced statistical theory.

Applied Statistics
Focuses on practical applications of statistical methods and data analysis across various fields.

Data Science
Combines statistical methodology with modern computational techniques and machine learning approaches.

Completing the minor.

The Field of Statistics offers three distinct minor options for Ph.D. students, each tailored to different academic focuses and career goals

Students outside statistics who wish to minor in Statistics must have a representative from the Field of Statistics on their committee. Coursework for a Ph.D. minor follows either a Theoretical Statistics or Applied Statistics track with specific course recommendations listed.

Students must complete the following:

  1. Field representation: a Field of Statistics member must be asked, and agree, to serve as a minor member on the Special Committee of a doctoral student at least 6 months prior to either the A or B exams.
  2. Coursework: The student must take, or demonstrate proficiency in, a minimum of five courses in Statistics (letter grades only), achieving above a B average. Specifically, the following graduate-level coursework is required:
    1. Probability: ORIE 6510 or equivalent;
    2. Inference: ORIE 6700 or equivalent;
    3. Linear or Generalized Linear Models: BTRY/ORIE/STSCI 7170 STSCI 7180 or equivalent.
    4. Electives: At least one other course with a high level of content relevant to applied or theoretical statistics or probability, the final decision being up to the faculty member representing the field of statistics.

Students must complete the following:

  1. Field representation: A Field of Statistics member must agree to serve as a minor member on the Special Committee of a doctoral student at least 6 months prior to either the A or B exams.
  2. Coursework: The student must take, or demonstrate proficiency in, a minimum of five courses in Statistics (letter grades only), achieving above a B average. Specifically, the following graduate-level coursework is required:
    • Probability: STSCI 5080 or equivalent;
    • Inference: BTRY/STSCI 5090, Math 4720 or equivalent;
    • Regression Modeling: STSCI 5030 or a related course with detailed coverage of linear and multiple linear regression at the matrix algebra level.
    • Electives: At least two other courses with a high level of content relevant to applied statistics, the final decision being up to the faculty member representing the field of statistics.
  1. Field representation: a Field of Statistics member must agree to serve as a minor member on the Special Committee of a doctoral student at least 6 months prior to either the A or B exams.
  2. Coursework: The student must have the knowledge of the topics covered in an introductory statistics course (such as BTRY 6010).  The student must also take, or demonstrate proficiency in, a minimum of five courses in Statistics (letter grades only), achieving above a B average. Specifically, the following coursework is required:
    • Regression Modeling: STSCI 5030 or a related course with detailed coverage of linear and multiple linear regression at the matrix algebra level;
    • Machine Learning: STSCI 5740 or a related course with coverage of Data Mining and Machine Learning;
    • Big Data Computing: Two courses from STSCI 5060, STSCI 5065, or equivalent;
    • Electives: At least one other course with a high level of content relevant to data science, the final decision being up to the faculty member representing the field of statistics.