In this interactive two-credit course, students connect their STEM interests to social problem-solving and community-based vocational leadership. Students will participate in project-based math modeling, validating alumni panels, employer excursions, guided discussions, and small-group faculty mentoring. Through this collaborative learning, students will foster a sense of community, launch their college careers confidently, and exhibit the mindset of change agents.
Previously: MATH 100
For students with one or two years of high school algebra. This course is at the level of college algebra, but is not focused on algebra. It stresses application of mathematics in careers of non-scientists and in the everyday lives of educated citizens, covering basic mathematics, logic, and problem solving in the context of real-world applications.
Every Fall, Interim, and Spring
Previously: MATH 140
The focus of this course is the foundational ideas of grades K-8 mathematics. The purpose is to engage prospective teachers in (re)discovering the real number system in order to develop a deep understanding of number meanings, representation, operations, algorithms, and properties. Through intuition and imagination, rather than rigidly following prescribed methods, students will explore models for arithmetic, consideration of children’s thinking about numbers, and investigations with technology.
Every Fall
Previously: MATH 130
This course investigates foundational ideas of grades K-8 mathematics. The focus is on thinking about mathematical concepts that are currently prominent in elementary schools from the perspective of teaching. Mathematical tasks include a deep analysis of concepts, consideration of children’s thinking, and investigations with technology. Topics include two and three dimensional geometry, transformations,area, volume, surface area, measurements, statistics, and probability.
Every Spring
Previously: MATH 131
Algebra review, functions and graphs, logarithmic and exponential functions, analytic geometry, trigonometric functions, trigonometric identities and equations, mathematical induction, complex numbers. Students completing this course are prepared to enter calculus.
Every Fall and Spring
Previously: MATH 150
Limits and continuity for functions of one real variable. Derivatives and integrals of algebraic, trigonometric, exponential, and logarithmic functions. Applications of the derivative. Introduction to related numerical methods.
Every Fall and Spring
Previously: MATH 151
Techniques of integration, numerical integration, and applications of integrals. Infinite series including Taylor series. Introduction to differential equations. Calculus in polar coordinates.
Every Fall and Spring, occasional Summers
Previously: MATH 152
Students acquire fundamental knowledge and practical experience to utilize the potential of R. Students engage in understanding data types and variables, vectors, matrices, lists, and functions. Students enhance their data manipulation skills and learn basic statistical functions and packages. Students master important topics such as logical statements, if/else statements, loops, and apply.
Every Interim
Previously: MATH 125
The topics of this course are: Introduction to R, Data Basics and Data Collection Principles, Numerical and Graphical Description of a Single Variable, Scatterplots, Least Squares Regression, Contingency Tables, Basic Probability Theory, Bayes’ Rule, Discrete Random Variable, Binomial Random Variable, Continuous Random Variable, Normal Random Variable, Sampling Distributions, Confidence Intervals, Hypothesis Testing, Connection between Testing and Estimation, Comparing two Means, Estimating and Testing a Single Proportion, Comparing two Proportions.
Every Fall
Previously: MATH 280
Bridges the gap between computational, algorithmic mathematics courses and more abstract, theoretical courses. Emphasizes the structure of modern mathematics: axioms, postulates, definitions, examples conjectures, counterexamples, theorems, and proofs. Builds skill in reading and writing proofs. Includes careful treatment of sets, functions, relations, cardinality, and construction of the integers, and the rational, real, and complex number systems.
Every Fall
Previously: MATH 200
Vector spaces, linear independence, basis and dimension, linear mappings, matrices, linear equations, determinants, Eigen values, and quadratic forms.
Every Spring
Previously: MATH 220
The calculus of vector-valued functions, functions of several variables, and vector fields. Includes vector operations, equations of curves and surfaces in space, partial derivatives, multiple integrals, line integrals, surface integrals, and applications.
Every Spring
Previously: MATH 153
Methods of solving first and second order differential equations, applications, systems of equations, series solutions, existence theorems, numerical methods, and partial differential equations.
Every Fall
Previously: MATH 310
The specific topics of the course include Introduction to Regression Analysis, Straight-Line Regression Analysis, The correlation coefficient and Straight-Line Regression Analysis, The Analysis of Variance table, Multiple Regression Analysis, Statistical Inference in Multiple Regression, Correlations, Confounding and Interaction in Regression, Regression Diagnostics.
Previously: MATH 305
The history of mathematics from ancient to modern times. The mathematicians, their times, their problems, and their tools. Major emphasis on the development of geometry, algebra, and calculus.
Occasional Interims
Previously: MATH 330
Topics to be selected from counting techniques, mathematical logic, set theory, data structures, graph theory, trees, directed graphs, algebraic structures, Boolean algebra, lattices, and optimization of discrete processes.
Every Spring
Previously: MATH 320
A review of Euclidean geometry, an examination of deficiencies in Euclidean geometry, and an introduction to non-Euclidean geometrics. Axiomatic structure and methods of proof are emphasized.
Occasional Interims
Previously: MATH 335
This course explores the mathematical foundations of algorithms used in the field of Data Science, typically taken after a course in mathematical statistics. It includes the study of classification and regression techniques, robust regression, decision trees, support vector machines, neural networks, cross-validation techniques, forecasting models, and Topological data analysis. The course includes a data-driven project that requires the student to propose a question and gather, clean, and analyze data to present a response to a real-world problem.
Occasionally
Previously: MATH 327
The specific topics of the course include combinatorics, basic probability, discrete and cont. random variables, probability distributions (emphasis on Normal distribution), multivariate dist., expected values, conditional probability, independence, Moment generating functions, central limit theorem.
Every Fall
Previously: MATH 315
Point Estimation, interval estimation, hypothesis testing, one factor analysis of variance (ANOVA) and two-way, Chi-Square Goodness of Fit Tests, Contingency Tables.
Occasionally
Previously: MATH 316
This course reviews and correlates the courses in the mathematics major. Each student is responsible for preparing the review of one area. Students also read papers from contemporary mathematics journals and present them to the class. The course uses the ETS mathematics major exam.
Every Spring
Previously: MATH 490
An introduction to topological structures from point-set, differential, algebraic, and combinatorial points of view. Topics include continuity, connectedness, compactness, separation, dimension, homeomorphism, homology, homotopy, and classification of surfaces.
Every other Spring, odd years
Previously: MATH 345
A survey of the classical algebraic structures taking an axiomatic approach. Deals with the theory of groups and rings and associated structures, including subgroups, factor groups, direct sums of groups or rings, quotient rings, polynomical rings, ideals, and fields.
Every other Fall, even years
Previously: MATH 340
This course develops the logical foundations underlying the calculus of real-valued functions of a single real variable. Topics include limits, continuity, uniform continuity, derivatives and integrals, sequences and series of numbers and functions, convergence, and uniform convergence.
Occasionally
Previously: MATH 350
A study of the concepts of calculus for functions with domain and range in the complex numbers. The concepts are limits, continuity, derivatives, integrals, sequences, and series. Topics include Cauchy-Riemann equations, analytic functions, contour integrals, Cauchy integral formulas, Taylor and Laurent series, and special functions.
Occasionally
Previously: MATH 355
Students will learn about supervised and unsupervised learning (K-Means Clustering). They will be able to assess model accuracy. Students will be able to perform classification, in particular they will learn about Generative Models for Classification and Generalized Linear Models GLMs. Students will be able to perform Cross-Validation: Training and Test Set. Students will be able to make variable selection by applying Ridge or LASSO Regression.
Previously: MATH 325