Advanced Problem Solving with Maple

Dr. William P. Fox is an emeritus professor in the Department of Defense Analysis at the Naval Postgraduate School. Currently, he is an adjunct professor, Department of Mathematics, the College of William and Mary. He received his Ph.D. at Clemson University and has many publications and scholarly activities including twenty books and over one hundred and fifty journal articles. William C. Bauldry, Prof. Emeritus and Adjunct Research Prof. at Appalachian State University, received his PhD in Approximation Theory from Ohio State. He has published many papers on pedagogy and technology, often using Maple, and has been the PI of several NSF-funded projects incorporating technology and modeling into math courses. He currently serves as Associate Director of COMAP’s Math Contest in Modeling (MCM).

• Introduction to Problem Solving and MapleProblem SolvingIntroduction to MapleThe Structure of MapleGeneral Introduction to MapleMaple TrainingMaple Applications CenterIntroduction, Basic Concepts, and Techniques in Problem Solving with First Order, Ordinary Differential EquationsIntroduction Applied First Order Differential Equations and Solution MethodsSlope Fields and Qualitative AssessmentsAnalytical Solution of 1st Order ODEsFirst Order ODEs and MapleNumerical Methods for 1st Order ODEsIntroduction, Basic Concepts, and Techniques in Problem Solving with Systems of Ordinary Differential EquationsSystems of Differential EquationsApplied Systems of Differential EquationsPhase Portraits and Qualitative AssessmentSolving Homogeneous and Non-Homogeneous Systems of ODEsNumerical Solutions to Systems of Ordinary Differential EquationsProblem Solving with Linear, Integer, and Mixed Integer ProgrammingFormulating Linear Programming ProblemsUnderstanding Two-Variable Linear Programming: A Graphical SimplexSolving the Linear Program: The Simplex Method and MapleLinear Programming with Internal Maple CommandsSensitivity Analysis with MapleInteger and Mixed Integer Problems with MapleModel Fitting and Linear RegressionIntroductionThe Different Curve Fitting CriterionPlotting the Residuals for a Least-Squares FitCase StudiesStatistical and Probabilistic Problem Solving with MapleIntroductionBasic Statistics: Univariate DataIntroduction to Classical ProbabilityReliability in Engineering and BusinessCase Study: Airlines Overbooking ModelThe Normal DistributionConfidence Intervals and Hypothesis TestingProblem Solving with SimulationIntroductionMonte Carlo SimulationProbability and Monte Carlo Simulation Using Deterministic BehaviorProbability and Monte Carlo Simulation: Using Probabilistic BehaviorCase Studies: Applied Simulation ModelsIndex

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