Majors in Statistical Science

Statistical Science majors are exposed to a broad range of statistical methods using tools from mathematical and computational sciences. Developing skills and expertise in problem articulation and solving, and abilities to appreciate and accommodate uncertainty in decision-making, are central goals. Graduating students are well prepared and competitive for beginning careers in data science, analytics, business, technology, finance, law, medicine and other fields, as well as for graduate study in statistical science and allied disciplines.

Our program is structured to teach students about the discipline of statistics and provide them with an opportunity to develop a substantial undergraduate research experience. We offer both a Bachelor of Science and a Bachelor of Arts in Statistical Science.

Required Courses:

Prerequisites

The skills developed and techniques explored in these courses are necessary for study of advanced statistical methods in the major:

  • MATH 21 Introductory Calculus I OR MATH 111L Laboratory Calculus I
  • MATH 122 Introductory Calculus II OR MATH 112L Laboratory Calculus II
  • MATH 219 Multivariable Calculus for Engineering and Sciences OR MATH 212 Multivariable Calculus OR MATH 222 Advanced Multivariable Calculus OR MATH 202 Multivariable Calculus for Economics. NOTE: the concentration in mathematical statistics requires 212, 219, or 222
  • MATH 218 Matrices and Vector Spaces (good option for many students) OR MATH 221 Linear Algebra and Application (required for math majors, preferred for statistical science students thinking about graduate study in statistics or mathematical science) OR MATH 216 Linear Algebra and Differential Equations (introductory course; some students may find this less engaging than 218 or 221). NOTE: the concentration in mathematical statistics requires MATH 221, and the concentration in data science requires MATH 218 or MATH 221.
  • COMPSCI 101L Introduction to Computer Science OR COMPSCI 102 Interdisciplinary Computing OR COMPSCI 201 Data Structures and Algorithms OR EGR 103L Computational Methods . Other COMPSCI courses require pre-approval from the DUS. Students with AP credit for COMPSCI 101 may meet the requirement by taking any Duke COMPSCI course. 

Recommended

  • STA 199L Intro to Data Science (We recommend that students wishing to major in Statistical Science start with this course. STA 198L is considered equivalent to STA 199L in the major and is an acceptable alternative.)

Core

  • STA 210L Regression Analysis
  • STA 240L Probability for Statistics (Recommended starting Spring 2020) or STA 230 Probability (MATH 230) or STA 231 (MATH 340) Advanced Introduction to Probability
  • STA 432 Statistics (MATH 343). 
  • STA 360L Bayesian and Modern Statistics (Ideally take this course by the end of your junior year.)
  • STA 440L Case Studies in the Practice of Statistics (Taken any time during senior year.) STA 540L can also be used to meet this requirement.

Electives

Electives are intended to provide breadth in either thinking and methods. All electives must contain statistical content beyond what is covered in STA 210L. STA 199L or STA 198L is allowed to count as a statistics elective, but STA 611 (Introduction to Mathematical Statistics) cannot be used towards this requirement. Up to 1 independent study course can be used towards this requirement (we will continue to consider up to 2 independent study courses for 2020 and May 2021 graduates). Faculty advisors and the Director of Undergraduate Studies will help majors to select elective courses in accordance with their academic goals. See Course Descriptions and Pathways for potential choices.

  • Bachelor of Arts: 3 Statistical Science electives
  • Bachelor of Science: 3 Statistical Science electives plus 1 elective from an applied field, such as engineering, mathematics, natural sciences, or one of the quantitative social sciences. Applied elective must come from the list of approved courses or must be pre-approved by the Director of Undergraduate Studies. See here for more information on this requirement.

Considering Graduate Study in Statistical Science or a Closely-Related Field?

Students considering graduate study in statistical science or a closely-related field are very strongly encouraged to get as much experience in theoretical mathematics as possible, taking MATH 221 as the linear algebra option and taking a course in real analysis (MATH 531 or 431, preferred in that order). If you're nervous about going straight into real analysis, please consider MATH 240 or MATH 245 as an intermediate step between your linear algebra course (216, 218, or 221) and real analysis. The mathematical statistics concentration is a great option for those considering graduate study in statistics.

Concentration in Mathematical Statistics

The concentration in mathematical statistics can be completed by careful course selection as part of the major. The linear algebra prerequisite must be MATH 221, the multivariable calculus prerequisite must be 212, 219, or 222, and the applied elective must be either MATH 431 or MATH 531.

Concentration in Data Science

The concentration in data science can be completed by careful course selection as part of the major. The linear algebra prerequisite must be MATH 218 or MATH 221, of the four electives, at least two must come from the group of STA 198L, 199L, 310, 313L, 322, 323D, 325L, and 393/493 (with a data science focus), 465, 561D, 571, or 671D, at least one of these two must come from the subgroup of STA 313L, 323D, 325L, 465, 561D, 571, or 671D, and one course should come from the group of COMPSCI 216, 316, 330, 370, 371, 516, or 570, with others possible with pre-approval by the DUS.