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This archived information is dated to the 2011-12 academic year only and may no longer be current.

For currently applicable policies and information, see the current Stanford Bulletin.

Minor in Mathematical and Computational Science

Up one level:

Mathematical and Computational Science

The minor in Mathematical and Computational Science is intended to provide an experience of the four constituent areas: Computer Science, Mathematics, Management Science and Engineering, and Statistics. Five basic courses are required:

CS 106X. Programming Methodology and Abstractions (Accelerated)

or CS 106A,B. Programming Methodology

MATH 51. Linear Algebra and Differential Calculus of Several Variables

or MATH 104. Applied Matrix Theory

MS&E 211. Linear and Nonlinear Optimization

or MS&E 221. Stochastic Modeling

STATS 116. Theory of Probability, and either

STATS 191. Introduction to Applied Statistics

or STATS 200. Introduction to Statistical Inference

In addition to the above, the minor requires three courses from the following, two of which must be in different departments:

CME 108. Introduction to Scientific Computing

CS 103. Mathematical Foundations of Computing

CS 107. Programming Paradigms

CS 154. Introduction to Automata and Complexity Theory

CS 161. Design and Analysis of Algorithms

EE 261. The Fourier Transform and its Applications

ECON 102C. Advanced Topics in Econometrics

ECON 160. Game Theory and Economic Applications (prerequisite ECON 51)

ECON 181. Optimization and Economic Analysis

MS&E 211. Linear and Nonlinear Optimization

MS&E 212. Mathematical Programming and Combinatorial Optimization

MS&E 221. Stochastic Modeling

MS&E 251. Stochastic Decision Models

MATH 104. Applied Matrix Theory

MATH 106. Functions of a Complex Variable

MATH 108. Introduction to Combinatorics and its Applications

MATH 109. Applied Group Theory

MATH 110. Applied Number Theory and Field Theory

MATH 115. Functions of a Real Variable

MATH 131. Partial Differential Equations I

MATH 132. Partial Differential Equations II

MATH 171. Fundamental Concepts of Analysis

PHIL 151. First-Order Logic

STATS 191. Introduction to Applied Statistics

STATS 200. Introduction to Statistical Inference

STATS 202. Data Analysis

STATS 203. Introduction to Regression Models and Analysis of Variance

STATS 217. Introduction to Stochastic Processes

Other upper-division courses appropriate to the program major may be substituted with consent of the program director. Undergraduate majors in the constituent programs may not count courses in their own departments.

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