The Major

Learning objectives

At the end of this curriculum a student will:

1. Understand the mathematical foundations of classical and modern statistical and data science methods, as well as gain experience with
their software implementations
2. Apply statistical techniques to solve real world problems, including problem formulation, data collection, modeling and analysis, and
results interpretation and communication
3. Work in a group/team setting using concepts and methods from statistics and data science and communicate results with stakeholders

Requirements

All courses used to satisfy these requirements must be completed with a passing grade (D or higher), but not with a “P.” A cumulative quality point average of at least 2.000 is required in all Mathematics and Statistics courses taken. Completion of a MATH or STATISTC course carrying the Integrative Experience designation is required. Currently these are: Math 455, Math 456, Math 475, Stat 525, Stat 494CI.

Lower division requirements

1. Differential and integral calculus: MATH 131 and 132, with a grade of C or better in Math 132
2. Multivariable calculus and linear algebra: MATH 233 and 235
3. Fundamental concepts of statistics: STAT 310
4. Computer programming: CICS 110 OR INFO 190S OR COMPSCI 121 or equivalent
5. Writing in mathematics: MATH 370

Upper division requirements

1. Probability and statistics: STAT 315 (was Stat 515) and STAT 516 or 490S
2. Regression analysis: STAT 525 
3. Statistical computing: STAT 535
4. Four electives: at least two of the four electives are required to be drawn from STAT 390+, excluding STAT 501 and STAT 517, and at most two of the four electives can be MATH 390+ courses, MATH 300, MATH 331 or approved courses from outside of the department