67 courses with the subject MATH, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
Basic concepts underlying algebra, functions, exponents, areas, fractions, and percents. Reasoning skills required for these concepts. Word problems. Meets three hours. See also MATH 18000; credit cannot be earned for both MATH 10000 and MATH 18000. Prerequisites: Math placement in group 4, math placement assessment score of 0-45. (F,S,Y) 1 Credit
Introduction to differential calculus, mathematics of finance, and linear programming. Additional topics at the instructor's discretion. Intended for students in the School of Business. Students may not receive credit for both MATH 10400 and MATH 10500, 10600, or 10700. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater, or completion of MATH 10000 or MATH 18000 with a grade of C- or better. (F,S,Y) 4 Credits
Introduction to mathematics useful for making decisions in the business world. Topics include linear functions and optimization; simple interest, compound interest, and annuities; and game theory. Additional topics at the instructor's discretion. Intended for students in the School of Business. Students may not receive credit for both MATH 10410 and MATH 10500. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater. (F,S,Y) 4 Credits
Introduction to probability theory, mathematics of finance and linear programming. Additional topics at the instructor's discretion. Students may not receive credit for both MATH 10500 and MATH 10600. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater, or completion of MATH 10000 or MATH 18000 with a grade of C- or better. (IRR) Attributes: QL3 Credits
Introduction to calculus, with an emphasis placed on problems in the business, economics, social sciences and life sciences. Topics include polynomial, exponential, and logarithmic functions and their derivatives; curve sketching, optimization, and rates of change; the definite integral and area. Further topics may be chosen from applications of differential equations and trigonometric functions. Not open to students who have taken MATH 11100. Completion of this course with a grade of C-or better will move students in group 3 to group 2. Students with group 1 placement who plan to take more than one semester of calculus should instead take MATH 11100. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater, or completion of MATH 10000 with a grade of C- or better. (F,S,Y) Attributes: QL4 Credits
Calculus of functions of one variable. Topics include limits, continuity, derivatives, applications of derivatives (problems of motion, graphing, and optimization), antiderivatives, and an introduction to the definite integral. Functions covered include polynomial, rational, exponential, logarithmic, trigonometric, and piecewise-defined functions. Prerequisites: Math placement in group 1 or higher, math placement assessment score of 76 or greater, or completion of MATH 11000 with a grade of C- or better. (F,S,Y) Attributes: QL4 Credits
Continuation of calculus of functions of one variable. Topics include differential equations, including slope fields, numerical solutions, and separation of variables; evaluation of integrals and antiderivatives; applications of integration; improper integrals; series, with an emphasis placed on power series. Prerequisites: MATH 11100 with a grade of C- or better or MATH 10800 with a grade of B or better. (S,Y) Attributes: ESTS4 Credits
A first course in statistics covering descriptive statistical techniques; introduction to probability; statistical inference including problems of estimation and hypothesis testing; correlation and regression analysis; and multiple regression. Data sets and exercises will be chosen from the fields of business, economics, and management. Technology used in this course may include graphing calculators and statistical software. Not open to students who have completed MATH 14500 or MATH 21600. Prerequisite: Math placement in group 2 or higher, math placement assessment score of 54 or greater, or completion of MATH 10400, MATH 10410, MATH 10800 or MATH 11000 with a grade of C- or better. (F,S,Y) Attributes: ESTS, QL4 Credits
A first course in statistics covering descriptive statistical techniques; introduction to probability; statistical inference including problems of estimation and hypothesis testing; one-way ANOVA; and design of experiments. Most of the data sets and exercises will be chosen from the fields of biology, health, and life sciences, as well as from everyday life. Technology used in this course may include graphing calculators and statistical software. Not open to students who have completed MATH 14400 or MATH 21600. Prerequisite: Math placement group 2 or higher, math placement assessment score of 54 or greater, or completion of MATH 10400, MATH 10410, MATH 10800 or MATH 11000 with a grade of C- or better. (F,S,Y) Attributes: ESTS, QL4 Credits
An introduction to the principles and tools of data science focusing on exploratory data analysis. Topics include data collection, types of variables, mathematical representations of data, data cleaning and wrangling, data visualization and numerical summaries, the research cycle and methods, and data ethics. This course includes an introduction to the R programming language. MATH 14800 and COMP 14800 are crosslisted; students cannot earn credit for both. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater. (F,Y) 4 Credits
Cultural approach to selected topics in mathematics. See instructor for current list of topics. Students may not receive credit for both MATH 15200 and MATH 25200. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater, or completion of MATH 10000 or MATH 18000 with a grade of C- or better. (IRR) 3 Credits
Students reflect on and find their own answer to the questions: “What is Mathematics and where does it come from?” Investigates the nature of the institution of mathematics by experiencing, reading about, and discussing several aspects of mathematical thinking and learning. Uses ideas from philosophy, psychology, history, sociology, and biology to explore and gain insight into math as it has developed historically, as it is taught in schools, and as it is used in society. Prerequisites: Math placement in group3 or higher, math placement assessment score of 46 or greater, or completion of MATH 10000 with a grade of C- or better. (IRR) Attributes: SO3 Credits
Basic concepts involved in statistical reasoning, including identifying basic elements of sampling and experiments, interpreting simple graphical displays and basic numerical summaries of univariate data, interpreting the results of hypothesis tests and interval estimates for univariate data, the concept of type I error, and the idea of correlation. Emphasis is placed on understanding the use of statistics rather than on how to do statistical analysis. Not open to students who have taken MATH 14400, MATH 14500, MATH 21600 or PSYC 20700. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater, or completion of MATH 10000 or MATH 18000 with a grade of C- or better. (F,S,Y) Attributes: ESTS, QL3 Credits
An introduction to R, a free, open-access scientific computing platform that is especially good at statistics, including simulation, large data sets, and graphing. Focuses on the use of R by covering a variety of applied problems. Prerequisite: Math placement in group 2 or higher, math placement assessment score of 54 or greater. (IRR) 1 Credit
Explores connections between mathematics and the liberal arts. Covers three to six topics chosen for their mathematical and societal component, with comparable emphasis given to each component. Only a high school math background is assumed, but students must have scored in group 2 or 1 on the math placement exam. Actual course content varies with instructor, but examples of topics are exponential growth and world population; symmetry and group theory in art and architecture; fair allocation and equity; binomial models and the death penalty; quantitative communication and the media. Prerequisites: Math placement in group 2 or higher, math placement assessment score of 54 or greater, or completion of MATH 11000 with a grade of C- or better. (IRR) Attributes: SO3 Credits
Introduces different quantitative methods that are used by different stakeholders (teachers, administrators, and policy makers) to make decisions related to education. Topics include the achievement gap in education and data-driven instruction. (IRR) Attributes: ESE, QL3 Credits
Addresses mathematical topics that have close connections to politics: apportionment, voting and weighted voting, fair division, and districting. (IRR) Attributes: QL, SO3 Credits
Examines the sustainable production and consumption of natural resources from a quantitative perspective. The course introduces quantitative tools to create, analyze, and critique mathematical models relating to sustainability and explores methods for communicating these results effectively. Topics vary based on student interest but may include climate change, epidemiology, population growth, energy, and agriculture. Prerequisites: Math placement in group 3 or higher or math placement assessment score of 46 or greater. (S,Y) Attributes: QL, SC3 Credits
Explores the ways mathematics can inform artistic endeavors and artwork can inspire mathematical thinking. Students explore the interrelation of mathematics and art through activities such as perspective drawing, explorations of symmetry, and paper folding. Students also analyze the work of various artists to experience multiple approaches to perspective and pattern, comparing the practices of various cultures and eras. Fee for course materials. (IRR) Attributes: CA3 Credits
Students explore mathematical phenomena experimentally, detect patterns, and provide mathematical explanations for these patterns. Students gain insight into mathematical thinking and the process of conjecture by designing and implementing mathematical algorithms with a Computer Algebra System. Discrete dynamical systems including Markov chains will be investigated. Other topics vary but may include the distribution of prime numbers, modular arithmetic, the Collatz Conjecture. Prerequisites: Math placement in group 1 or higher, math placement assessment score of 76 or greater, or completion of MATH 11000 with a grade of C- or better. (F,O) 3 Credits
Introduction to the objects and tools of applied linear algebra. Emphasis placed on computation, both by hand and with computer algorithms, and applications to data. Topics include vectors, norm, angle, linear independence, orthogonality and projections, clustering and the k-means algorithm, left and right inverses of matrices, QR factorization, least-squares, model fitting, the singular value decomposition, and dimension reduction of data. Prerequisites: Math placement group 3 or higher, math placement assessment score of 46 or greater. (F,Y) Attributes: QL4 Credits
MATH 11100 and MATH 14400 8 (Quantitative Literacy (QL) and (LA)))
Topics to be determined by instructor and department. May be repeated for credit for selected topics on different subjects. Prerequisites: Appropriate to topics. (IRR) 1-4 Credits
Introduction to advanced mathematics through faculty presentations and problem-solving activities. Prerequisites: MATH 11200 or MATH 18500 (either may be taken concurrently). Pass/Fail only. (S,Y) 1 Credit
Individual study of selected subjects extending the student's mathematical knowledge. Prerequisites: Permission of instructor. (IRR) 1-3 Credits
Introduction to vectors and the geometry of vector spaces. Calculus of functions of several variables: partial derivatives, gradients, optimization, double integrals. Prerequisites: MATH 11200 with a grade of C- or better. (F,Y) 4 Credits
Multiple integrals and change of variables. Line and surface integrals. Classical theorems of vector calculus. Prerequisites: MATH 21100 with a grade of C- or better. (IRR,S) 3 Credits
Topics will include modeling with differential equations, existence and uniqueness of solutions, separation of variables; first order linear equations; second order equations with constant coefficients; homogeneous equations, phase plane analysis, eigenvalues; and systems of differential equations. Additional topics may include: series solutions of differential equations, non-linearity and equilibrium analysis, and transforms among others. Prerequisites: MATH 11200 with a grade of C- or better. (E,S) 3 Credits
An introduction to statistical analysis for students with a calculus background, developing an understanding of descriptive and inferential statistics through the use of a variety of traditional and simulation methods. Topics will include hypothesis testing and parameter estimation. Additional topics to be selected from experimental design and data collection, exploratory data analysis, non-parametric methods, monte carlo and resampling methods, analysis of variance, correlation and regression. Statistical literacy and data analysis concepts will be emphasized. Prerequisites: MATH 10800 with a grade of B or better, or MATH 11100 with a grade of C- or better. (IRR) Attributes: QL3 Credits
This is a math content course for future elementary school teachers. Students develop a deep understanding of mathematical content, strengthen their mathematical reasoning and problem-solving skills, and learn how to help elementary students make mathematical sense of their world. (S,Y) Attributes: ESE, QL3 Credits
Provides an introduction to spatial data management, analysis, modelling and visualization, and their applications, with a focus on problem solving with a geographic information system. The context for applications in this course will mainly be environmental. The industry-standard ArcGIS software will be used. Prerequisites: MATH 14400, MATH 14500, MATH 21600, MATH 24600, or PSYC 20700. (IRR,S) Attributes: DSCI, ENRE, ESTS3 Credits
Foundational theory and applications of linear algebra, with a focus on different ways to view and use matrices. Topics include a matrix as representing a system of equations, as representing a collection of vectors, and as a transformation of vectors; linear independence, span, basis, dimension, rank, coordinate systems, eigenvalues and eigenvectors. Applications include image compression, Markov chains, and the PageRank algorithm. Prerequisites: MATH 10800 with a grade of B or better or MATH 11100, MATH 18500, or MATH 18700 with a grade of C- or better. (S,Y) Attributes: DSCI, NS3 Credits
An introduction to R, a free scientific computing platform, as applied to basic statistics. Students learn how to manage data, create appropriate graphs, perform basic statistical tests (t-tests, chi-square, ANOVA, regression, etc), and compute confidence intervals. Additional topics include tests of assumptions (e.g., normality) and post hoc tests. Prerequisites: MATH 14400, MATH 14500, MATH 21600, MATH 24600, or PSYC 20700. (IRR) 1 Credit
An introduction to effective visual representation of data. Topics include design principles for visual communication, relationships in graphs, theories of visual perception, and critiques of graphs. Students will create visualizations of data using packages in the R programming language. Prerequisites: MATH 14400, MATH 14500, MATH 14800, MATH 18700, MATH 24800, or PSYC 20700. (S,Y) 1 Credit
Covers statistical methods not typically covered in introductory statistics courses. Topics include multivariate analysis and nonparametric techniques, bootstrapping and jackknife methods, and two-way ANOVA. Emphasis will be placed on working with data sets from a broad variety of disciplines with an exploratory data analysis approach. The statistical software environment R will be used in analyzing data. Prerequisite: MATH 14400, MATH 14500, MATH 21600, MATH 24800 or PSYC 20700 with a grade of C- or better. (S,Y) Attributes: DSCI, QL3 Credits
An applied introduction to modern statistical methods with an emphasis on data science and multivariable thinking. Topics include exploratory data analysis, multivariable data visualization and summarization, randomization and bootstrap methods for statistical inference, confidence intervals and hypothesis testing using both simulation- and model-based approaches, and building and interpreting linear and multiple regression models for prediction and explanation. The course uses R statistical software. Prerequisites: One liberal arts course; Math placement in group 2 or higher, math placement assessment score of 54 or greater, or completion of MATH 10410, MATH 10800, MATH 14800, or MATH 18700, with a grade of B or better. (F,Y) 4 Credits
Techniques used in the solution of diverse mathematical problems are developed and discussed. Problems will often be drawn from national competitions, such as the Putnam exam and the COMAP Modeling Competition, or from problem sections of mathematics journals. The course will be offered for either 0.5 or one credit ; it may be repeated for credit up to a total of four credits. Prerequisites: MATH 11100 with a grade of C- or better. Pass/fail only. (IRR) 0.5-1 Credits
Explores intersections of mathematics with culture, historical traditions, and sociocultural roots. Studies mathematical ideas arising from world cultures, recognizes contributions of non-Western societies to the history of mathematics, and explores mathematical thinking outside of traditional Western approaches. Investigates interdisciplinary connections with fields such as history, linguistics, fine arts, and architecture. Emphasizes fostering self-assurance and enthusiasm for mathematics through an examination of cultural heritage. (F,Y) Attributes: DV, ESE, SO3 Credits
Focus is on the underpinnings of and strategies for mathematical arguments that constitute mathematical proof. These underpinnings include logical connectives, (universal and existential) quantification, and rules of deductive inference. Strategies include direct proof, indirect proof, "proof" by counterexample, proof by cases, and proof by induction. Students learn to employ these strategies and concepts to create basic mathematical proofs. Content topics include, but are not limited to, fundamentals concepts of sets and functions as well as multiple topics from discrete mathematics that include elementary counting principles. Prerequisites: MATH 23100 or MATH 18500 with a grade of C- or better. MATH 18500 may be taken concurrently. (IRR) 3 Credits
Topics to be determined by instructor and department. This course may be repeated for credit when topics vary. Prerequisites: Permission of instructor. (IRR) 1-4 Credits
Individual study of selected subjects extending the student's mathematical knowledge. Prerequisites: Permission of instructor. (IRR) 1-3 Credits
Introduction to algebraic structures. Study includes concepts from group theory, ring theory, or field theory. Topics may include Abelian groups, cyclic groups, permutation groups, factor groups, ideals, quotient rings, integral domains, isomorphisms, and homomorphisms. Additional topics may be included. Prerequisites: One three or four credit level 2 MATH course with a grade of C- or better. (F,O) 4 Credits
Topology of the real line. Continuity, differentiability, and integrability of functions of a real variable. Prerequisites: One three to four credit level 2 MATH course with a grade of C- or better. (E,S) 4 Credits
Students explore the theory of functions defined in the complex plane, highlighting the interplay between geometric visualization and analysis. Topics may include the geometry of analytic mappings, power series, Cauchy's Theorem, and the Residue Theorem. Connections to other areas of mathematics and to other scientific fields will be explored through applications. Prerequisites: MATH 21100 or MATH 23100. (IRR) 3 Credits
Explores principles of probability and their use in analyzing random phenomena across mathematics and applied contexts. Topics include axioms of probability, conditional probability, Bayes' rule, independence, random variables, expectation, and likelihood functions. Additional topics may include random processes with applications to data science. Prerequisites: MATH 21100 with a grade of C- or better. (S,Y) Attributes: DSCI3 Credits
Topics in graph theory include basic properties of graphs, Eulerian trails, Hamilton chains, trees, and may include the chromatic polynomial, planar graphs, and the independence number. Topics in combinatorics include the pigeonhole principle, permutations and combinations, the binomial theorem, and may include generating functions, Catalan numbers, and Stirling numbers. Prerequisites: COMP 22000 or one 3-4 credit MATH course at the 200-level. (E,F) 3 Credits
Theory, application, and programming of computational algorithms in mathematics and data science. Topics include approximation and error analysis, numerical root-finding algorithms, numerical differentiation and optimization, and iterative methods for solving linear systems, along with applications. Additional topics may include numerical integration, numerical computation of eigenvalues, and numerical solutions of differential equations. Prerequisites: MATH 11200 and MATH 23100. (O,S) Attributes: DSCI3 Credits
Modern data science brings together programming, statistics, and mathematical skills to understand the world. The course focuses on data visualization and modeling, while also covering topics related to data management and programming in the R environment. Students use theory together with programming and statistical methods to develop the capacity to create new and unique models, visualizations, and/or solutions in data-based multidisciplinary investigations into problems from a variety of fields. Prerequisites: MATH 14800; MATH 18700; MATH 24800. (F,Y) 3 Credits
Introduces students to the creation of interactive and animated graphics for the visualization of data. Prerequisites: MATH 34800, or COMP 17100 and MATH 24600. (IRR) 1 Credit
Rigorous development of Euclidean and hyperbolic geometry from both a metric and synthetic point of view. Some topics in transformational geometry are also covered. Prerequisites: One three to four credit level 2 MATH course with a grade of C- or better. (F,O) 4 Credits
Individual study of selected subjects extending the student's mathematical knowledge. Does not fulfill a required mathematics elective. This course may be repeated for credit for different studies. Prerequisites: Any MATH course at the 300-level (may be taken concurrently). (IRR) 1-3 Credits
Students will work with faculty on focused mathematical investigations. Research problems will be presented by faculty teaching MATH 39810 Research Experience in Mathematics. Students will attend a variety of talks related to mathematics. Weekly problem solving related to research topics. Prerequisites: One level-2 MATH course. Pass/fail only. (F,O) 1 Credit
Students actively participate in mathematical investigation and exposition, working collaboratively on research questions. Review of relevant literature and research methods will be incorporated. Students are required to present their findings both in writing (consistent with the standards of the discipline) and in public presentations. Topics vary by instructor. Permission of instructor is required. Prerequisites: MATH 39700. (O,S) 3 Credits
Capstone course in which students synthesize and apply the skills, methods, and knowledge acquired throughout their studies to a substantial data project. Emphasizes independent project design, execution, and professional presentation of results. MATH 44800 and COMP 44800 are crosslisted courses; credit can only be earned for one. Prerequisites: MATH 34800. (S,Y) 3 Credits
Study of connections and relationships among various disciplines within mathematics. Specific content varies. Topics may include, but are not limited to, the following: historical development of mathematics and various philosophies of mathematics, cultural similarities and differences in viewpoints and developments in mathematics, cross-discipline approaches that combine subdisciplines such as probability techniques in number theory and random graph theory, field theory and geometric constructions, and algebraic topology. This course may be repeated for credit when topics vary. Prerequisites: One 300-level course in mathematics with a grade of C- or better. (F,Y) 3 Credits
Topics to be selected by instructor and students. Fulfills a required mathematics elective. This course may be repeated for credit when topics vary. Prerequisites: Permission of instructor. (IRR) 3 Credits
Individual study of selected subjects extending the student's mathematical knowledge. Fulfills a required mathematics elective. This course may be repeated for credit. Prerequisites: Permission of instructor. (IRR) 1-3 Credits
Preparation of honors thesis in partial fulfillment of requirement for graduation with honors in mathematics. Prerequisites: Honors standing in mathematics. (IRR) 1-2 Credits
Preparation of honors thesis in partial fulfillment of requirement for graduation with honors in mathematics. Prerequisites: Honors standing in mathematics. (IRR) 1-2 Credits
Students develop a capstone project proposal that will be completed in MATH 49900. Students reflect on how their prior math courses have prepared them for their project. Prerequisites: Junior standing; six credits in mathematics at level 3 or 4 with a grade of C- or better. (S,Y) Attributes: CP, WI1 Credit
Students reflect upon the field of mathematics via an integrative project developed in concert with a faculty mentor. Students analyze mathematical ideas related to their projects and integrate this knowledge with ideas learned in the mathematics curriculum. Students complete a comprehensive thesis (begun in MATH 49800) and give a public presentation. Prerequisites: MATH 49800 with a grade of C- or better. (F,Y) Attributes: CP, WI2 Credits
The seminar will address a selection of topics in mathematics education, devoting several weeks to each topic. Topics will be chosen to examine theoretical aspects of the teaching and learning of mathematics at the secondary (7-12) level and will be connected to related discussions of pedagogical design and implementation. Class discussions, presentations and projects will be central to the course. (F,Y)
Advanced study of mathematics in an applied setting. Topics may include but are not limited to the following: stochastic processes, actuarial mathematics, partial differential equations and applied dynamical systems, numerical analysis, and applied statistics. Prerequisite: Graduate student in good standing or permission of instructor. can be repeated for credit. (F, E)
This course will explore the historical development of mathematical ideas that appear in the high school mathematics curriculum. Students will select a topic and research its history, then present their work and lead the class in explorations that use the historical development to better understand the concept.
This course will explore the connections between algebra topics from the high school (7-12) mathematics curriculum and the content of the algebra courses that math majors have learned in college. In particular, ideas from advanced algebra will be used to develop a deeper understanding of fundamental algebraic ideas. Class discussions, individual research, presentations and projects will be central to the course.
Advanced study of connections and relationships among various disciplines within mathematics. Specific content varies. Topics may include but are not limited to the following: historical development of mathematics and various philosophies of mathematics, cultural similarities and differences in viewpoints and developments in mathematics, cross-discipline approaches that combine subdisciplines such as probability techniques in number theory and random graph theory, field theory and geometric constructions, and algebraic topology. instructor. can be repeated for credit. (S, E)
Reading on selected advanced subjects, with frequent, informal discussions with the instructor. Fulfills a required mathematics elective. This course may be repeated for credit. Prerequisites: permission of instructor. (IRR)
Source: Ithaca College's catalog, linked per course · table learning_unit · CourseShelf publish 61
