Statistics and Data Science

Faculty
Admission to the Major:
The Major

The university-wide Department of Statistics and Data Science offers undergraduate and graduate degrees in Statistical Science (B.A.), Applied Statistics (MPS), and Statistics (M.S./Ph.D.). The Statistical Science undergraduate major, open to students in Arts and Sciences, provides an interdisciplinary academic program in the study of empirical quantitative reasoning in its scientific and social context. The Statistical Science major has been designed to ensure that students have a firm grounding in both the major area as well as substantial depth in a particular applied area.

Website: stat.cornell.edu

Faculty

M. Wells, chair; J. Booth, director of graduate studies; T. DiCiccio, director of undergraduate studies; S. Basu, F. Bunea, A. El Alaoui, J. Entner, J. Guinness, G. Hooker, M.E. Karns, K. Kato, N. Kiefer, D. Matteson, F. Molinari, Y. Ning, M. Nussbaum, K. Packard, D. Ruppert, M. Smith, Y. S. Wang, M. Wegkamp, M. T. Wells, X. D. Yang, X. Yang

The Major:

Note: In addition to the major requirements outlined below, all students must meet the college graduation requirements .

Admission to the Major:

Prerequisites to apply for the major include a minimum 2.50 cumulative GPA and grades of C- or higher in the following courses to ensure foundational mathematical, computational and statistical ability:

MATH 1110 - Calculus I
MATH 1120 - Calculus II or
MATH 1910 - Calculus for Engineers
STSCI 2200 - Biological Statistics I (crosslisted) or
BTRY 6010 - Statistical Methods I (crosslisted) or
Equivalent courses listed on the Statistics and Data Science website.

Requirements for major:

To complete the major, students must take a minimum of 60 credits.

Statistical Theory (7 courses):

Statistical Methods (2 courses):

Two (2) additional courses from among:

External Electives (3 courses):

Three thematically-linked courses covering related topics to statistics. The courses should either have a quantitative component that involves probabilistic reasoning or covers mathematical or computational tools that are used within statistics.

CS 1110 - Introduction to Computing Using Python or CS 1112 - Introduction to Computing Using MATLAB may be used as one of these courses in conjunction with two others in any discipline. This is strongly recommended for anyone without prior programming experience.

Courses from the Statistical Methods list may be used to satisfy this requirement, but no course can be used for both requirements. Unless otherwise noted all courses should be taken at the 3000 level or above. Example sequences are provided on the Statistical Science and Biometry and Statistics websites.