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Course Criteria
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4.00 Credits
Course content will include the real number system, similarity and proportional reasoning, number theory, measurement, probability and data analysis. Prerequisite: A grade of C- or better in MATH 246. (F, Sp)
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3.00 Credits
Systems of linear equations, matrices, determinants, vector spaces, linear transformations, eigenvalues and diagonalization theorems will be covered in the course. Prerequisite: MATH 156 or 166. (F, Sp)
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3.00 Credits
This course covers topics in multi-variable calculus, including graphing, partial differentiation, directional derivatives, gradients, definite integration over planar regions and regions of space, cylindrical and spherical coordinates, the Jacobian and methods for changing coordinates. Introductory vector analysis, including line and surface integrals are treated as time permits. Prerequisite: A grade of C- or better in MATH 167. (F,Sp; SS upon student request)
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1.00 Credits
A mathematics-related work experience such as tutoring, grading papers or serving as a laboratory assistant. In addition, students will be expected to attend several seminars on job skills and to assist in projects proposed by their on-site supervisor. This course is intended to help prepare students for MATH 379. Prerequisites: Completion of MATH 167; sophomore standing; GPA of 3.0 or higher; permission of MATH Department Internship Supervisor. (F, Sp)
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3.00 Credits
Properties of the real number system, solutions of linear and quadratic equations and inequalities, factoring and graphing are examined. Degree credit will not be given. Required of students whose score on the Wisconsin MATH Placement Test is 20 or 30 and whose ACT math score is below 20. Prerequisite: MATH 010 or Wisconsin MATH Placement test score of as least 20. (F,Sp)
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3.00 Credits
Properties of integers, prime and composite numbers, Euclidean algorithm, Diophantine equations, congruences, number-theoretic functions and continued fractions will be covered. Prerequisite: MATH 236. (F, odd years)
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3.00 Credits
This course covers the basic concepts of descriptive and inferential statistics. The inferential topics include point and interval estimation and hypothesis testing. Under hypothesis testing are the topics of: type I and type II errors, power of a test, t-test, and analysis of variance. Prerequisites: MATH 156, 166 or consent of instructor. (F odd years; Sp odd years)
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3.00 Credits
The fundamental theorems and methods used in studying ordinary differential equations are presented. Applications from physics and engineering are illustrated. Topics include first- and second-order linear, first-order nonlinear equations and series solutions. Prerequisite: MATH 256 or 266. (F, Sp)
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3.00 Credits
This course is an introduction to the numerical algorithms fundamental to analysis, and includes solution to equations by fixed-point iteration, the Newton-Raphson method, error analysis, polynomial interpolation, numerical differentiation and integration, direct methods for solving linear equations, and approximation theory. Co-listed as CSIS 346. Prerequisites: MATH 167 and capability in at least one programming language. (F)
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3.00 Credits
Fundamental concepts of discrete and continuous probability theory will be developed, including density and distribution functions, independence, conditional probability, Baye's theorem, marginal probabilities and densities, bivariate densities, moment-generating functions, and the central limit theorem. Prerequisites: MATH 236 and 266. (F)
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