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• MATH 486: Field Experience & Internship

  1.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course consists of in-depth involvement in an environment that focuses on the use of mathematics to model and solve industrial, administrative, business or governmental problems. The student will work under direct professional supervision. Prerequisite:    MATH220 AND MATH240 AND MATH311 AND MATH320
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• MATH 487: Internship in Statistics

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course consists of in-depth involvement in an environment that focuses on the use of statistics to model and solve problems. The student will work under direct professional supervision. Prerequisite:    MATH311 AND MATH402 AND MATH405 AND MATH411 AND MATH416
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• MATH 499: Student Teaching Internship

  1.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course is designed to provide the student with an opportunity to work with a faculty member in the students primary Arts and Sciences discipline during the student teaching experience. The course will enhance the students ability to understand and maximize the relationship between disciplinary subject matter and pedagogy.
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• MATH 500: ST:

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course is designed to provide the student with an opportunity to work with a faculty member in the students primary Arts and Sciences discipline during the student teaching experience. The course will enhance the students ability to understand and maximize the relationship between disciplinary subject matter and pedagogy.
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• MATH 502: Applied Statistical Methods

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  Students in this course will be provided with practical application of serveral 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.
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• MATH 516: Linear Statistical Modeling Methods with SAS

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course is intended for 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: Satisfactory completion of a college course in statistics. (Offered fall term of odd years)
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• MATH 520: Number Theory

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course includes a consideration of the fundamental laws of integers, the linear Diophantine equation, the Euclidean algorithm, prime numbers, divisibility, congruencies, the Theorems of Fermat and Wilson, primitive roots, and indices. (Not regularly offered)
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• MATH 530: Trends in Secondary Education

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course will examine current and proposed secondary mathematics curricula and models of teaching and learning mathematics. Major foci will be mathematical problem solving and integrating technology into the mathematics curriculum. (Not regularly offered)
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• MATH 531: Teaching Mathematics Using Technology

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  Designed for in-service secondary mathematics teachers, this course will cover the use of graphing calculators, computer algebra and geometry systems, how to incorporate them into the classroom and how the availability of technology will change the mathematics that will be taught. (Not regularly offered)
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• MATH 545: Mathematics in Modern Technology

  3.00 Credits

  East Stroudsburg University of Pennsylvania

  
  This course is designed to introduce the student to some of the contemporary mathematical practices that have been developed to address problems relating to such technologies as digital image compression, edge detection and signal de-noising. Using appropriate software the students will learn how to model a variety of filters and advanced mathematical transformations and to apply them to real-life problems. Prerequisite: MATH 141 and 320.
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