Three hours lecture/two hours lab per week. An introduction to astronomy, earth science, chemistry, and physics. Students will learn about current events that relate to these topics and how to think critically about scientific information as an informed citizen. NS

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.

Multivariate calculus: three-dimensional coordinate system, vectors functions, partial differentiation, multiple integration, integration in vector fields, and applications. Prerequisite: C or higher in 221. QL

Four hours lecture per week. First order equations, second order linear equations, linear systems of equations, numerical methods, nonlinear systems and phase place analysis, matrices and linear systems, matrix operations, determinants, linear transformations, vector spaces, eigenvalues and eigenvectors. Prerequisite: grade of C or higher in 221. QL

Random variables, probability theory, application, and simulation. The binomial, Poisson, geometric, normal, gamma, and chi-square distributions are studied. Additional topics covered as determined by the instructor. Prerequisite: grade of C or higher in 220; grade of C or higher in 130 or 230. QL

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.

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

Principles, goals, and methods of teaching elementary school and middle school mathematics. Topics include set theory, number systems, whole numbers, number theory and integers and the associated binary operations. Emphasis on problem solving. Offered every semester. Prerequisite: grade of C or higher in 155 or a Math ACT score of 22 or higher. QL

Mathematical logic and proofs are introduced and used to discuss sets, functions, mathematical induction, and countability. Counting methods are covered which include permutations, combinations, and applications to probability. Introductory graph theory topics may include isomorphisms, Euler and Hamiltonian circuits, directed graphs, spanning trees. Computer programming is used to carry out various algorithms throughout the course. Prerequisite: acceptable placement score or grade of C or higher in MATH 112.