200

An introduction to descriptive and inferential statistics, with applications in various disciplines using statistical computer software. May not be used to satisfy general distribution requirements of the Baccalaureate Experience.

This course is designed to provide students with the fundamental components of differential and integral calculus, with a particular emphasis on those aspects of calculus that have applications to business. The course covers exponential and logarithmic functions, limits, differentiation and differentiation techniques, applications of the derivative (e.g., marginal cost, marginal revenue, rate of growth), anti-derivatives, the integral as an area, functions of several variables, and partial derivatives.

Covers limits, continuity, differentiation, applications of derivatives, integration, and integration by substitution.

Covers integration techniques and applications, parametric and polar curves, sequences and infinite series.

Covers vectors in two and three dimensional space, partial derivatives, multiple integration and vector calculus.

This course is designed for majors in computer science. It covers basic aspects of discrete mathematics that are fundamental to digital computing. Topics include sets and relations, numbers and sequences, mathematical logic, elementary combinatorics, graph theory, and related algorithms.

Covers linear equations, matrices and determinants. Vector spaces and linear transformations. Inner products and eigenvalues. Emphasizes computational aspects of linear algebra and applications.

This course provides the basic understanding of descriptive and inferential statistics, with applications in various disciplines. It gives the insight into how a statistician gathers, summarizes, and draws conclusions from real life data. This course covers the basics of statistical testing, regression analysis, experimental design, analysis of variance, and use of statistical software (especially R) to analyze data.

This course teaches programming fundamentals such as program design and modularity, with an emphasis on mathematical applications. Mathematical fields from which problems will be drawn include number theory, linear algebra, statistics, differential equations, multivariable calculus and modeling.

Covers proof techniques, basic set theory, relations and partitions, functions and cardinality.