Data analysis using simulation, machine learning algorithms: logistic regression, Naive Bayes, decision trees, k-means, k-nearest neighbors, and dimension reduction (principal component analysis). Students will learn how to test and validate models as well as format and display data. A data analysis project will be completed. Prerequisite: grade of C or higher in 230.

Study of elementary number theory, groups, rings, and fields. Specific examples and additional topics selected by instructor. Prerequisite: grade of C or higher in 112. QL

An introduction to mathematical modeling, computer simulation, and procedural programming. Various deterministic, stochastic, and simulation models are covered, with applications to engineering, physics, biology, chemistry, business, and other areas. Requirements include modeling projects with written reports and class presentations. Prerequisite: acceptable placement score or grade of C or higher in 220, 325. (Equivalent to ENGR 365). QL, WCII

An introduction to the analysis of the real number system. Topics include continuity, differential calculus, integral calculus, sequences and series. Prerequisite: grade of C or higher in 221. QL

Topics in Euclidean and other geometries; foundations of geometry; place of Euclidean geometry among other geometries. Offered every other year. Prerequisite: grade of C or higher in 260. QL

Non-classroom experiences in the field of mathe- matics. Placements are off-campus, and may be full- or part-time, and with or without pay. Credit for experiences must be sought prior to occurance, and learning contracts must be submitted before the end of the first week of the semester. See the experiential learning: internship section of this catalog for more details. Restricted to students with freshman or sophomore standing. Graded CR/NC.

Independent reading and/or research under the guidance of a mathematics faculty member. Refer to the academic policy section for independent study policy. Independent study contract is required. May be repeated for credit.

Limits, continuity, derivatives, applications, and an introduction to the integral. Differentiation of polynomial, rational, trigonometric, logarithmic and exponential functions. Prerequisite: acceptable placement score, or at least three years of high school algebra and trigonometry with at least a B average, or a grade of C or higher in 113. QL

Integration techniques including substitution, by parts, and approximate integration. Applications of integration including area, volume, arc length, surface area, center of mass, and probability. The course also covers differential equations, direction fields, growth models, sequences, and infinite series. Prerequisite: C or higher in 220. QL

Descriptive statistics, probability, random variables, estimation of parameters, and tests of hypotheses. Inference using bootstrap and randomization distributions as well as the normal, T, chi-square and F distributions. Includes regression, analysis of variance, and multiple regression. Computers are heavily used for data analysis. Prerequisite: acceptable placement score or grade of C or higher in MATH 112. QL