Finite Mathematics

In addition to key linear programming and probability topical coverage, this book emphasizes cross-disciplinary applications in an effort to relate mathematics to everyday life and various careers within business, finance, management, operations research, computer science, and the life and social sciences. The book begins with "Linear Equations and Mathematical Concepts" to solve linear systems of equations and includes a discussion of elementary and classical algebra concepts such as finding solutions to simple equations and how to graph these equations or systems. "Mathematics of Finance" addresses simple and compound interest, annuities, and amortization and includes an introduction to arithmetic and geometric sequences. "Matrix Algebra" includes a basic introduction to matrices for solving systems of equations in linear programming and Markov chains. "Linear Programming - Geometric Solutions" provides insights into the finite nature of linear programs as well as their optimal solutions, solution space, and limitations while "Linear Programming - Simplex Method" addresses the use of the simplex method to maximize profit or to minimize costs. "Linear Programming Application Models"discusses linear programming's wide usage as a mathematical optimization tool in industry and government for allocating resources, which is a prime managerial and decision making skill. "Set and Probability Relationships" includes an introduction to probability theory with coverage on working with sets, Venn diagrams, and tree diagrams. "Random Variables and Probability Distributions" addresses two key concepts in probability theory and how they can be used to gain insights to basic probability distributions and the underlying chance phenomena and assumptions. "Markov Chains" is presented both algebraically and with matrices to model transition diagrams and parallel decision diagrams. "Mathematical Statistics"discusses the role of probability in building statistical forms from sample data and includes coverage of population and sample statistics, descriptive statistics, uniform distribution, normal distribution, and surveys. The book concludes with "Enrichment in Finite Mathematics," which is divided into five sections with a focus on the related applications of game theory, finance and economics, life and social sciences, Monte Carlo method, and dynamic programming.