Applied Mathematics Minor

Required Courses for the Applied Mathematics Minor

The Applied Mathematics Minor provides students in other disciplines with a solid practical background in major branches of modern mathematics.

A student must successfully complete, at Fontbonne, a minimum of 50 percent of the credit hours required for the minor.

Courses required for the minor:

  • MTH 120

    Discrete Mathematics

    3 credits

    Topics include: truth tables, propositional logic, sets, binary and equivalence relations, functions, matrices, binary, octal and hexadecimal number systems, combinatorics, proof by induction and recursion, and algorithms. Prerequisites: Competency in arithmetic and algebra.

  • MTH 150

    Calculus with Analytic Geometry I

    4 credits

    Differential and integral calculus of the algebraic and transcendental functions associated with analytic geometry. Prerequisite: Three years of high school mathematics including trigonometry with grades of B or better, or MTH 110 (with a grade of C- or better), or (MTH 105 and MTH 108) with grades of C- or better, or the consent of the instructor.

  • MTH 151

    Calculus with Analytic Geometry II

    4 credits

    A continuation of MTH 150, continuation of differential and integral calculus; infinite series. Prerequisite: MTH 150 with grades of C- or better.

Plus two of the following six courses:

  • MTH 300

    Modeling and Numerical Approximation

    3 credits

    Principles of model construction with selected case studies from various fields. Also, techniques of numerical approximation. Prerequisites: MTH 150; CIS 160.

  • MTH 315

    Advanced Statistics

    3 credits

    Covers widely used statistical tools such as linear and nonlinear regression, analysis of variance, expected mean squares and pooling. Students will use a statistical package to analyze data sets. Prerequisites: (MTH 115 or MTH 125) and MTH 150 or consent of instructor.

  • MTH 316

    Non-Parametric Statistics

    3 credits

    An introduction to nonparametric statistical procedures. Topics include order statistics, rank order statistics and scores, tests of goodness of fit, linear rank tests for location and scale problems, applications. Prerequisite: MTH 115.

  • MTH 320

    Elements of Geometry

    3 credits

    Transformational approach to isometries and similarities; studies of Euclidean and non-Euclidean geometries. Prerequisite: MTH 150 or consent of instructor.

  • MTH 325

    Theory and Applications of Probability

    3 credits

    Introduces the mathematical treatment of random phenomena occurring in the natural, physical, and social sciences. Topics include combinatorial analysis, binomial distribution, Poisson and normal approximation, random variables and probability distributions, generating functions, Markov chains applications. Prerequisitess: MTH 115 or MTH 125 and MTH 150

  • MTH 430

    Algebraic Structures

    3 credits

    Covers algebraic structures including Boolean algebra, groups, rings, integral domains and fields and their applications which may include: cryptography, coding theory, color patterns, and switching circuits. Prerequisites: MTH 120; MTH 150.

Plus one of the following two courses:

  • MTH 115

    Introduction to Statistics

    3 credits

    Topics covered: descriptive statistics, probability, binomial, chi-squared and normal probability distributions, tests of hypotheses, linear correlation and regression, and analysis of variance. Prerequisites: Grades of C- or better in MTH 095 or competency in arithmetic and algebra.

  • MTH 125


    3 credits

    Introduces the application of statistical concepts to biological problems over a broad range of fields including biological sciences, medicine and public health. The evaluation of experimental design in biological studies will be addressed. Topics covered include: scientific method, data representation, descriptive statistics, inferential statistics and data analysis, normal probability distributions, estimation and hypotheses testing, chisquared
    distributions and the analysis of variance. An appropriate statistical program (currently R) will be used as a tool in the course. Prerequisite: MTH 105 or MTH 110 (or equivalent knowledge) and BIO 112 or an introductory biology course (can be concurrent).

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