Math 5: Pre-calculus
Preparation for calculus. Analyzing data by means of
functions (linear, quadradic, polynomial, logarithmic,
exponential and trigonometric) and graphs with an emphasis
on mathematical modeling of real-world applications.
Math 15: Introduction to Scientific Data Analysis
Fundamental analytical and computational skills to find,
assemble and evaluate information, and to teach the basics
of data analysis and modeling using spreadsheets,
statistical tool, scripting languages, and high-level
mathematical languages. This course is not for students
from School of Engineering.
Co-requisite: Math 5.
Math 18: Statistics for Scientific Data Analysis
Analytical and computational methods for statistical
analysis of data. Descriptive statistics, graphical
representations of data, correlation, regression, causation,
experiment design, introductory probability, random
variables, sampling distributions, inference and
significance.
Pre-requisite: Math 5 and Math 15.
Math 21: Calculus of a Single Variable I
An introduction to differential and integral calculus of
functions of one variable. Elementary functions such as the
exponential and the natural logarithm, rates of change and
the derivative with applications to natural sciences,
engineering and social sciences.
Pre-requisites: Passing score on calculus readiness
placement test, or score of 3 or higher on AP Calculus AB
exam or grade of C- or higher in Math 5.
Math 22: Calculus of a Single Variable II
A continuation of MATH 21. Analytical and numerical
techniques for integration with applications, sequences and
series, first-order differential equations.
Pre-requisites: Score of 4 or higher on AP Calculus AB
exam OR Score of 3 or higher on AP Calculus BC exam OR grade
of C- or better in MATH 21 or ICP 1
Math 23: Vector Calculus
Calculus of several variables. Parametric equations and
polar coordinates, algebra and geometry of vectors and
matrices, partial derivatives, multiple integrals and
introduction to theorems of Green, Gauss and Stokes.
Pre-requisite: Math 22
Math 24: Linear Algebra and Differential Equations
Introduces ordinary differential equations, systems of
linear equations, matrices, determinants, vector spaces,
linear transformations and linear systems of differential
equations.
Pre-requisite: Math 22
Math 30: Calculus II for Biological Sciences
A version of Math 22 for students majoring in the life
sciences. Analytical and numerical techniques of
integration, modeling differential equations for biology.
Pre-requisite: Math 21 or ICP 1
Math 32: Probability and Statistics
Concepts of probability and statistics. Conditional
probability, independence, random variables, distribution
functions, descriptive statistics, transformations, sampling
errors, confidence intervals, least squares and maximum
likelihood. Exploratory data analysis and interactive
computing.
Pre-requisite: Math 21 or ICP 1