Why Statistics?
Statistical thinking and quantitative reasoning have become pervasive in culture, economy, law, government,
and science, dramatically changing the way we view the world. With the increased development of computing
power and the growing availability in digital form of vast quantities of data, there has been widespread
statistical activity across all areas of industry and academic research. In this new millennium statistics
has emerged as a truly interdisciplinary activity that draws together researchers and educators from the
information sciences, physical sciences, life sciences, social sciences, and the humanities.
Statistics teaches a mode of reasoning that can be applied flexibly and with nuance across fields of study.
Statistics is reasoning about data, and data itself provides multiple and multidisciplinary contexts for problem-solving.
Read a recent New York Times article on the promise of the field of statistics
here.
Prerequisites
Prerequisites to apply for the major include a minimum 2.50 cumulative GPA over at least two (2) semesters
at Cornell University; and grades of C or higher in at least three (3) of the following courses to ensure
foundational mathematical, computational, and/or statistical ability:
Calculus I (MATH 1110)
Calculus II (MATH 1120)
Introduction to Computing (CS 1110 or CS 1112)
Statistical Methods I (STSCI 2200 / BTRY 3110)
Statistical Methods II (STSCI 3200 / BTRY 6020)
STSCI courses are offered through the College of Arts and Sciences. STSCI course numbers TBD.
Download the application to affiliate with the major in Statistical Science
here. This major is open only to students in the College of Arts & Sciences.
Statistical Science Major Requirements (B.A.)
Major Core (14 courses)
Statistical Theory (8 courses)
CS 1112 or 1110 Introduction to Computing Using JAVA or MATLAB
MATH 2210-2220 or 2230-2240 or 2930-2940 or 2130 & 2310: second-year calculus and linear algebra
PHL 2010: puzzles and paradoxes; or PHL 2310: deductive logic; or PHL 2610: knowledge and reality
STSCI 2200: statistical methodology I (cross-listed as BTRY/NTRES 3010)
STSCI 3200 statistical methodology II (cross-listed as BTRY 3020/NTRES 4130)
STSCI 4080 (cross-listed as BTRY 4080) or MATH 4710: theory of probability
STSCI 4090 (cross-listed as BTRY 4090) or MATH 4720: theory of statistics
Statistical Applications (3 courses)
Three (3) additional courses from among:
STSCI 3100: statistical sampling (cross-listed with BTRY/ILRST 3100)
ORIE 3510: stochastic processes
STSCI 4100: multivariate analysis (cross-listed with BTRY/ILRST 4100)
STSCI 4110: categorical data (cross-listed with BTRY/ILRST 4110)
STSCI 4120: applied experimental design (cross-listed with BTRY 6040)
ORIE 4740: statistical data mining (prerequisites: ORIE 3600, Math 2940)
CS 4780: machine learning (prerequisites: CS 2110, CS 2120, CS 2800, CS 3110)
BTRY 6520 computational statistics**
NTRES 6700 spatial statistics**
** comparable courses are being developed at the 400-level
External Specialization (3 courses)
Three 300+ related courses that are outside of Statistical Science and total at least nine credits. (3 credit min per course).
At least one course to include paper, project or research with substantive, non-trivial application of statistical methods to
subject-related data.
FAQs
More about the External Specialization
Each student pursuing the B.A. in Statistical Science must complete an "external specialization" as part of the
requirements of the major. Students may apply any subject across the social sciences, natural science, humanities, engineering, etc. Biometry
and/or BTRY courses may not be used to satisfy the external specialization.
Although these three courses at the 300-level or above (minimum of 3 credits per course) are designed to facilitate
the addition of a second major ("double major"), the external specialization
must include non-trivial application of statistical methods to subject-related data.
A proposal is required for the external specialization, and it should include a description of the applied statistics
component. For example, a student would like to use three courses in mathematics (courses not already required for the major in Statistical
Science) to satisfy her external specialization. One of these courses must contribute toward a statistical analysis of some dataset, or to
an investigation of a statistical problem either theoretically (mathematically) or via computer simulation. The course need not include
this work in the syllabus, but the student should use one of the course assignments
(project, paper, etc.) to apply statistical methods.
Each student must submit this brief proposal in writing. Submit this proposal as an attachment to bj11@cornell.edu. The proposal
document must include your name and NetID, your major faculty advisor, and the date.
AP Statistics
AP Statistics does not satisfy a major requirement toward a BA in Statistical Science. It is not eligible for
transfer toward the major requirements or major electives for this degree. You may be eligible to apply AP Statistics toward a free elective or
college-level requirement.
Transfer Credit
Read your college’s transfer credit policy before taking the course or applying for transfer credit. Some
colleges have restrictions, for example, on the application of transfer credits to satisfy certain requirements. It is always a good idea to
get departmental approvals before you take transfer credit courses elsewhere.
Transfer Students
Transfer students apply to the College of Arts and Sciences and request admission to the Department of Statistical Science.
Transfers are admitted directly into a College and Major when they are accepted to Cornell University. To learn about the application
process, visit the
Cornell University Transfer Student website.
Contact Information
Undergraduate Coordinator
Beatrix Johnson
bj11@cornell.edu
(607) 255-1646
Comstock Hall Room 1198
Director of Undergraduate Studies
Martin Wells
mtw1@cornell.edu
(607) 255-1646
Comstock Hall Room 1190
