Designed to provide students with the fundamentals of differential equations. The topics include elementary methods of solution, nth order linear equations, systems of linear equations, Laplace transform methods, numerical solutions, and initial and boundary value problems. Prerequisites: MA 126 and MA 221, both passed with a grade of 'C-" or higher.
Course champion - Dr. David Marshall
Properties of integers, divisibility, prime numbers, congruence, quadratic residues, and Diophantine equations. Prerequisites: MA 120 and MA 221, passed with a grade of "C-" or higher, MA LVL 3, and EN101 and EN 102 or permission of the instructor.
Study of Euclid's axioms, fifth postulate and its substitutes, absolute geometry, projective geometry, constructions, and convexity. Prerequisites: MA 120 and either MA 221 or MA 225, passed with a grade of "C-" or higher, and MA LVL 2.
Combinatorics is the study of countable discrete mathematical structures. Graph theory is the study of mathematical structures involving a collection of objects, known as the vertex set, along with a collection of pairs of vertices, known as the edge set. These two inseparable areas of mathematics are ripe with beautiful theory and endless applications. Students will learn the techniques required to answer questions in these fields, as well as appropriate applications. Prerequisites: MA 120 or MA 130 or CS 202, and MA 221; both passed with a grade of "C-" or higher and MA LVL 2.
Course champion -
A continuation of MA 220, including sample distributions, exploratory data analysis, estimation methods, regression, and correlation, as well as applications to quality control. Prerequisite: one of either MA 116 or MA 118 or MA 126, passed with a grade of "C-" or higher and one of either MA 151 or BE 251 or MA 220, passed with a grade of 'C-" or higher and EN 101 and EN 102.
Gives students a working knowledge of statistical consulting in the world outside of the classroom by working with real clients. Students will interview clients, translate client needs into statistical language, design statistical experiments, generate data collection plans, assist in data collection, analyze data, interpret their analyses, and present their finding to the client. Throughout the process students will interact with their clients regarding ongoing questions that occur. By the end of the course, students will be able to choose and apply appropriate statistical design and analysis methodologies. They will also be able to interpret, evaluate, and present their conclusions in oral and written form. Topics covered will depend upon client needs and may include designing experiments with power and sample size considerations, multiple and logistic regression, survival analysis, t- and chi-square tests, ANOVA/MANOVA/ANCOVA, and principal component analysis. This course may be repeated once for additional credit to either continue work on a long-term project, or to take part in a new statistical consulting project. Prerequisite: Permission of the instructor is required.
Surveys historical milestones in the development of mathematics from ancient times to the nineteenth century, with modern topics as time permits. Prerequisites: MA 314 or MA 317 or MA 318, passed with a grade of "C-" or higher, and EN 101 and EN 102.
Covers topics related to computational statistics, including obtaining large, realistic, real-time datasets, calculation and visualization of basic statistical features, regression, empirical distributions, and time-series features. Also covered will be principal components analysis (PCA), analysis of variance (ANOVA), correlation, prediction, and stochastic volatility estimation (GARCH). Portfolio theory will also be covered. Prerequisites: MA 116 or MA 118 or MA 126, passed with a grade of "C-" or higher, and either MA 151 or MA 220 or BE 251, passed with a grade of "C-" or higher.