# Mathematics

Mathematics plays such pivotal roles in today’s modern civilization that it is nearly impossible to imagine living without the modern conveniences and applications that the field has brought about. People who understand the discipline understand more than an academic subject area; they understand the structures on which entire societies rest.

Mathematics, the abstract science of number, quantity and space, touches all the sciences and offers logic, rather than observation, as a vehicle to move scientists from hypothesizing a result to proving it with accuracy and certainty. At the upper level, studying math has very little to do with calculators. Math students work with their professors to write and prove theorems that are sophisticated and even beautiful explanations of hidden patterns all around us.

Mathematics prepares students exceptionally well for careers or graduate study. Students who have interests in other science programs find that mathematics degrees dovetail nicely to other scientific disciplines. The department offers academic contests, a colloquium series, summer research, independent study projects and study abroad opportunities that round out the degrees, preparing students for some of the fastest growing and highest paying occupations in the United States.

Beginning fall 2020:

Mathematics majors may choose to add a **concentration** in **Data Science and Statistics**. Data Science is an emerging interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from data. The Data Science and Statistics (DSS) Concentration for Mathematics majors at University of Richmond is designed to supplement the major, grounding the student with a solid theoretical foundation in statistics while building the strong analytic skills that are needed to work with large and/or complex data sets. The DSS concentration prepares students for graduate study in the statistical sciences and supports students who aim for careers in any emerging area of data science.

# The Math Major

**Note: **The grade point average of the coursework comprising the major must be no less than 2.00 with no mathematics course grade below C- (1.7). Students are strongly advised to consult with faculty in planning their major curriculum.

#### For either the Bachelor of Arts or Bachelor of Science degree:

MATH 211 Calculus I

MATH 212 Calculus II

MATH 235 Multivariate Calculus

MATH 245 Linear Algebra

MATH 300 Fundamentals of Abstract Mathematics

MATH 306 Abstract Algebra I

MATH 320 Real Analysis I

CMSC 150 Introduction to Computing

Four electives in math at the 300-level

#### And for the Bachelor of Science degree:

Four other units in computer science with at least two at the 300 level, or two units beyond the introductory level in one of the following fields: physics (200 level or above), chemistry (200 level or above), or biology (numbered higher than 205).

Students are expected to fulfill all prerequisites necessary for courses within the major. Prerequisites do not count toward the major unless otherwise noted.

**Notes:**

*Students are strongly advised to complete either MATH 306 or MATH 320 prior to the senior year.*

*Any MATH and CMSC double-major, or MATH major with CMSC minor, having earned at least an A- in MATH 300 may exempt from CMSC 222 but is required to complete an additional CMSC 300-level elective to complete the CMSC major or minor.*

# The Math Minor

**Note:** The grade point average of the coursework comprising the minor must be no less than 2.00 with no mathematics course grade below C- (1.7). Students are strongly advised to consult with faculty in planning their minor curriculum.

Six units, including:

MATH 211 Calculus I

MATH 212 Calculus II

MATH 235 Multivariate Calculus

MATH 245 Linear Algebra

Two units at the 300 level

# The Data Science and Statistics Concentration

The concentration in data science and statistics with a major in mathematics requires six units (where applicable, these may also count for major requirements).

CMSC 221 Data Structures with Lab

MATH 289 Introduction to Data Science

MATH 329 Probability

MATH 330 Mathematical Statistics

MATH 389 Statistical Learning (may replace with CMSC 327 Machine Learning)

One unit, chosen from:

CMSC 325 Database Systems

CMSC 326 Simulation

CMSC 395 Selected Topics (with departmental approval)

ECON 270 Introductory Econometrics

MATH 396 Selected Topics in Mathematics

Note: Students completing a concentration in data science and statistics may not minor in mathematics or computer science.