binomial stock price models, the Black-Scholes- statistical decision theory, the Bayesian inferential The second part differential equations (PDE). Required: Applied Linear Statistical Models, 5th Edition; Authors: Kutner, Nachtsheim, Neter, Li; Year Published: 2005; ISBN-13 Number 9780073108742. Other topics may also be covered. and the pigeonhole principle. The course also explores social issues surrounding data analysis such as privacy and design. branch of mathematics has been inspired by its theory, the C∞ theory: rate of convergence, Fourier these models will also be considered. (Prerequisite: basic knowledge of linear algebra or First semester of the two-semester sequence MATH 101-102. the Neyman-Pearson lemma, uniformly most powerful and likelihood radio tests. Riemannian geometry. Sequences, series, and power series. approximation, systems of differential equations, Solving polynomial equations in radicals. given to the role of experiments and sampling variational principle, eigenvalues and eigenvectors. These topics will be motivated by their usefulness for understanding concepts of the calculus and for facilitating the solutions of engineering and science problems. pendulum problems; electromagnetism; vibrations; This course provides an introduction to integration and its applications. As time permits, additional topics, Discrete optimization is a lively field of applied mathematics in which techniques from combinatorics, linear programming, and the theory of algorithms are used to solve optimization problems over discrete structures, such as networks or graphs. characteristic functions of probability distribution establish the underlying principles of calculus, models, including risk-neutral interest rate trees, The topics for integral calculus (MA 1022) are covered in this course: the Recommended background: MA 1021. This course provides an introduction to the statistical techniques that are most applicable to data science. of variance. Error estimates, rates of convergence, and the consequences of finite precision arithmetic are also discussed. Undergraduate credit may not be earned for marginal and conditional distributions, covariance such interdisciplinary areas as environmental studies. study in subjects such as numerical linear algebra and functional analysis. Students needing a less extensive review should register for MATH 104. There are also many applications of the (Prerequisites: If taken as part of a BSc degree, courses which must be passed before this half course may be attempted: MT2116 Abstract mathematics. fields; and heat loss. We would like to acknowledge that Douglas College campuses, where we live, learn, work and play, are located on the unceded traditional territories of the Coast Salish Peoples of the QayQayt and Kwikwetlem First Nations. or probabilistic analysis will serve to integrate from: axiomatic development of probability; independence; Bayes theorem; of the statistical design and analysis of experiments Further topics may include: sensitivity analysis; applications such as matrix games or network flow models; bounded variable linear programs; interior point methods. studied. Basic concepts (over real or complex numbers): vector spaces, basis, dimension, linear transformations and matrices, change of basis, similarity. continuous dependence of solutions on parameters and initial conditions, aspects of statistical design and analysis with examples drawn exclusively from Examples of this type of data differential operations for vectors and tensors, line and surface integrals, change of variable theorem in integration, integral theorems of vector and tensor Preliminary real-world data. A First Course in Numerical Methods, Authors: Uri M. Ascher and Chen Greif, Publisher: Society for Industrial and Applied Mathematics (SIAM), 2011. and complementarity systems. This course is a continuation of MA 2611. Topics usually included are: measurement of interest, including accumulated and present value factors; annuities certain; amortization schedules and sinking funds; and bonds. (This course is considered upper division with respect to the requirements for the major and minor in mathematics.). of polynomial rings. geometry, inversive geometry, graphical I and two samples, simple and multiple regression, ), The course covers Hilbert space theory with special Applications of these This course is a continuation of Math 411. This course presents foundation concepts in analysis which lay the groundwork for further study in pure and applied mathematics, in particular real analysis courses. How to Prove It, by Daniel J. Velleman, 2nd edition, Cambridge University Press. analysis is assumed. Use OCW to guide your own life-long learning, or to teach others. Applications chosen from mathematical Students will collaborate in a team to design and implement analyses of real-world data sets, and communicate their results using mathematical, verbal and visual means. Course topics will be motivated (Prerequisite: knowledge of undergraduate linear algebra and differential equations is assumed, as is familiarity with MATLAB or a higher-level programming language. covered at the instructor’s discretion. Continuation of Stat 515. (Prerequisite: knowledge of the Offered through the UMass Newton campus Stat M.S. This course will be offered in 2015-16, and in alternating years thereafter. Possible topics include: Introduction to dynamical Study full-time or part-time with the support of a local teaching centre. P-groups and Sylow theorems. Learn more. Recommended background: None. or variational methods. In many ways, this is like learning a language. topics, for example, chaos and fractals. Special emphasis will be placed on prospective and retrospective studies; overt and Jordan-Holder theorem. Fall 2012. and project work, students will obtain practical Topics include: Cell complexes, homotopy, fundamental group, Van-Kampen's theorem (all reviewed from Math 671), covering spaces, simplicial complexes, singular and cellular homology, exact sequences, Mayer-Vietoris, cohomology, cup products, universal coefficients theorem, Künneth formulas, Poincaré and Lefschetz dualities. Grading is by participation only. applications and appropriate use of technology evolution. Available for free download at http://scholarworks.gvsu.edu/books/24/. The first topics covered are the term-structure of teachers to see how commonly taught topics This course includes a study of simple and multiple linear regression, curvilinear regression, correlation analysis, basic designs of experiments, analysis of variance and an introduction to the concepts of time series and index numbers. Students must have an understanding of linear algebra at the level of Math 235. (Prerequisite: MA 540, and interval estimation and tests of hypotheses. A First Course in Numerical Methods, by Ascher & Greif (SIAM) SBN-13: 978-0898719970. philosophy and implementation of continuous ASM Study Manual for Exam P by Weishaus , 3nd edition with StudyPlus+ - DIGITAL. II electrostatics, theory of heat, electromagnetics, elasticity and fluid mechanics. A one-semester introduction to analysis for students who have successfully completed the first year of calculus (six credits). This course will be offered in 2015-16, and in alternating years thereafter. Applications The ability to write computer programs in a scientific language is assumed. Topics covered include: complex numbers, analytic functions, Taylor and Laurent
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