This is completed downloadable of Finite Mathematics 6th Edition Waner Solutions Manual
Product Details:
Full of relevant, diverse, and current real-world applications, Stefan Waner and Steven Costenoble’s FINITE MATHEMATICS, Sixth Edition helps you relate to mathematics. A large number of the applications are based on real, referenced data from business, economics, the life sciences, and the social sciences. Thorough, clearly delineated spreadsheet and TI Graphing Calculator instruction appears throughout the book. Acclaimed for its readability and supported by the authors’ popular website, this book will help you grasp and understand finite mathematics–whatever your learning style may be.
Table of Content:
0. PRECALCULUS REVIEW. Real Numbers. Exponents and Radicals. Multiplying and Factoring Algebraic Equations. Rational Expressions. Solving Polynomial Equations. Solving Miscellaneous Equations. The Coordinate Plane.
1. FUNCTIONS AND APPLICATIONS. Functions from the Numerical, Algebraic, and Graphical Viewpoints. Functions and Models. Linear Functions and Models. Linear Regression.
2. THE MATHEMATICS OF FINANCE. Simple Interest. Compound Interest. Annuities, Loans, and Bonds.
3. SYSTEMS OF LINEAR EQUATIONS AND MATRICES. Systems of Two Equations in Two Unknowns. Using Matrices to Solve Systems of Equations. Applications of Systems of Linear Equations.
4. MATRIX ALGEBRA AND APPLICATIONS. Matrix Addition and Scalar Multiplication. Matrix Multiplication. Matrix Inversion. Game Theory. Input-Output Models.
5. LINEAR PROGRAMMING. Graphing Linear Inequalities. Solving Linear Programming Problems Graphically. The Simplex Method: Solving Standard Maximization Problems. The Simplex Method: Solving General Linear Programming Problems. The Simplex Method and Duality.
6. SETS AND COUNTING. Sets and Set Operations. Cardinality. The Addition and Multiplication Principles. Permutations and Combinations.
7. PROBABILITY. Sample Spaces and Events. Relative Frequency. Probability and Probability Models. Probability and Counting Techniques. Conditional Probability and Independence. Bayes’ Theorem and Applications. Markov Systems.
8. RANDOM VARIABLES AND STATISTICS. Random Variables and Distributions. Bernoulli Trials and Binomial Random Variables. Measures of Central Tendency. Measures of Dispersion. Normal Distributions.
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