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• MATH 318: Exploratory Data Analysis with R

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  Exploratory data analysis is an approach to analyzing data sets with statistical graphics, interactive data visualization and numerical techniques. It makes complex data more accessible and understandable. Students will learn how to display, communicate and analyze data using R, one of the top programming languages for data science. Prerequisite:    MATH110 OR MATH311 AND CPSC101 OR CPSC100 OR CPSC130
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• MATH 320: Linear Algebra

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course deals with the arithmetic of matrices, linear transformation of the plane, algebra of determinants with applications to the systems of linear equations, vector spaces, characteristic values and their application. Prerequisite:    MATH220
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• MATH 341: Differential Equations

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course examines solutions of first order Differential Equations, Linear Equations of Higher Order, Numerical Techniques of Solution, Power Series Methods, LaPlace Transform, and Applications. Prerequisite:    MATH240
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• MATH 351: Modern Geometry

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  Problem solving in Geometry will be the main focus of this course. Three types of problems are studied. The first will be straightedge and compass constructions from Euclidean Geometry. The next will develop the Newton-Poincare model of Lobachevskian Geometry. The third will be isometries of the Euclidean plane. Prerequisite:    MATH220
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• MATH 360: Introduction to Combinatorics

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course introduces the basic techniques and modes of reasoning of combinatorial problem-solving. Topics covered include elementary counting principles, permutations and combinations, the inclusion/exclusion principle, recurrence relations, basic properties of graphs and digraphs, trees, graph coloring, and Eulerian and Hamiltonian circuits. Prerequisite:    MATH220
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• MATH 402: Applied Statistical Methods

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  Students in this course will be provided with practical applications of several commonly used statistical procedures, including correlation analysis, single and multiple regression analyses, one-and two-way analysis of variance and experimental design and parametric stastics for undergraduate and graduate health and science majors. Prerequisite:    MATH110 OR MATH311 AND CPSC100 OR CPSC101
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• MATH 405: Experimental Design and Sampling for Surveys

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course gives an introduction to survey sampling and experimental design. The topic of survey sampling covers the typical sampling methods, the calculation of estimators of population parameters and sample size calculations. The topic of experimental design covers the typical methods of design of experiments, ANOVA (analysis of variance) for these design methods, multiple comparisons and contrast analyses. The emphasis will be on applications of the methods of survey sampling and experimental design. The computer package SAS will be required for data analysis. Prerequisite:    MATH311 OR MATH110 AND CPSC130 OR CPSC101 OR CPSC100
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• MATH 411: Statistics II

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  The mathematical properties of the sampling distributions of statistics will be investigated to develop criteria for precise estimation, powerful hypothesis testing, and assessing the robustness of model assumptions. Emphasis will be placed on the classical methods associated with the normal distribution and to the analysis of real data with linear models. Standard software packages will be used. Prerequisite:    MATH141 AND MATH311
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• MATH 416: Linear Statistical Modeling with SAS

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course is intended for advanced undergraduate students, graduate students, and working professionals who engage in applied research. Statistical linear modeling methods are used in conjunction with SAS computer software to analyze data from experiments and observational studies. Topics include regression analysis, analysis of variance, multiple comparisons and multiple tests, mixed models, analysis of covariance, logistic regression, and generalized linear models. Prerequisite:    MATH110 OR MATH311 AND CPSC100 OR CPSC101
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• MATH 420: Number Theory

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course deals with the study of the divisibility properties of integers, the theory of congruences, continued fractions, linear diophantine equation in one variable and more than one variable, algebraic number fields, and rings of algebraic integers.
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