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Course Criteria
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3.00 Credits
This course is an introduction to the basic laws of probability needed to performstatistical analysis. Included are probability distributions, the Central Limit Theorem, confidence intervals, hypothesis testing, and Analysis of Variance. (prereq:MA-137 orMA-225)
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3.00 Credits
This subject introduces the laws of probability with applications to statistical analysis of data, includingmedical data. Topics include estimation of population parameters, tests of hypotheses, and tests for goodness of fit. Note: This course is open only to students in the School of Nursing. (prereq:MA-125 or equivalent)
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3.00 Credits
This subject provides a brief study of vector algebra and vector calculus, including velocity and acceleration, space curves, gradient, divergence and curl using the del operator, line, surface and volume integrals, conservative fields, curvilinear coordinates, Green's theorem, the divergence theorem, and Stokes' theorem. (prereq:MA-232 orMA-226)
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4.00 Credits
Almost allmanagerial decisions involve some amount of uncertainty. This course is designed to acquaint the student with some of the statisticalmethods that can be used to helpmake these decisions. Topics covered are probability, probabilitymodels, estimation, tests of hypotheses, analysis of variance, and regression. Note: This course is open only to students in the Rader School of Business. (prereq:MA-127 or equivalent)
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3.00 Credits
This course is an introduction tomatrixmethods and linear programming, includingmatrix algebra,matrix inversion, simultaneous linear equations, linear programming including the simplexmethod, duality, and the transportation problem. (prereq:MA-231)
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4.00 Credits
This and the following course cover post-calculus topics of interest to and importance for engineers. The emphasis in this course is on differential equations. Covered are: first and second order differential equations, the Laplace transform, series solutions, numerical approximations to solutions. (prereq:MA-226 or equivalent)
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4.00 Credits
A continuation ofMA-3501. This course emphasizes linear algebra. Covered are: vectors and vector spaces;matrices, determinants and systems of linear equations; eigenvalues and diagonalization. (prereq:MA-3501)
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4.00 Credits
This course provides an introduction to biostatistics and design of experiments for biomedical engineering students. As a result of this course, the students are expected to understand and prepare statistical analyses to data fromphysiological systems in the laboratory and clinical environment. Students learn basic probability theory that includes discrete and continuous probability distributions. They learn how to apply that theory to hypothesis testing and understand the difference between a z-test and t-test, and one- and two-sample inference hypothesis testing. Additionally, concepts associated withmeasurement validity and reliability, hypothesis formulation and testing, and the experimental and statistical control of error. Particular emphasis is given to the appropriate selection and use of parametric statistical tests including t-tests, analysis of variance, repeated-measures designs, and simple andmultiple regression. Statistical software tools are used throughout the course. (prereq:MA-137)
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3.00 Credits
This course discusses the basics of probability theory, randomvariables, stochastic processes, and statistics at a level that will allow the successful student to pursue research and access the literature in electrical engineering. Applications and randomprocesses associated with practical systems will be studied. (prereq:MA-232)
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3.00 Credits
This course gives the studentmore powerfulmethods of solving differential equations. Topics includematrixmethods for solution of systems of linear differential equations, series solution of linear differential equations with variable coefficients, andmore Laplace transformtools. (prereq:MA-235,MA-232)
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