Finite Mathematics / Edition 9by Margaret Lial, Raymond N. Greenwell, Nathan P. Ritchey
Pub. Date: 10/16/2007
Finite Mathematics, Tenth Edition, by Lial, Greenwell, and Ritchey, is our most applied text to date, making the math relevant and accessible for students of business, life science, and social sciences. Current applications, many using real data, are incorporated in numerous forms throughout the book, preparing students for success in their professional careers. With this edition, students will find new ways to get involved with the material, such as “Your Turn” exercises and “Apply It” vignettes that encourage active participation.
- Publication date:
- Edition description:
- New Edition
- Product dimensions:
- 8.17(w) x 10.58(h) x 1.14(d)
Table of ContentsR. Algebra Reference.
R.3 Rational Expressions.
1. Linear Functions.
1.2 Linear Functions and Applications.
1.3 The Least Squares Line.
2. Systems of Linear Equations and Matrices.
2.2 Solution of Linear Systems by the Gauss-Jordan Method.
2.3 Addition and Subtraction of Matrices.
2.4 Multiplication of Matrices.
2.5 Matrix Inverses.
2.6 Input-Output Models.
3. Linear Programming: The Graphical Method.
3.2 Solving Linear Programming Problems Graphically.
3.3 Applications of Linear Programming.
4. Linear Programming: The Simplex Method.
4.2 Maximization Problems.
4.3 Minimization Problems; Duality.
4.4 Nonstandard Problems.
5. Mathematics of Finance.
5.2 Future Value of an Annuity.
5.3 Present Value of an Annuity; Amortization.
6.2 Truth Tables and Equivalent Statements.
6.3 The Conditional and Circuits.
6.4 More on the Conditional.
6.5 AnalyzingArguments with Euler Diagrams.
6.6 Analyzing Arguments with Truth Tables.
7. Sets and Probability.
7.2 Applications of Venn Diagrams.
7.3 Introduction to Probability.
7.4 Basic Concepts of Probability.
7.5 Conditional Probability; Independent Events.
7.6 Bayes' Theorem.
8. Counting Principles; Further Probability Topics.
8.3 Probability Applications of Counting Principles.
8.4 Binomial Probability.
8.5 Probability Distributions; Expected Value.
9.2 Measures of Variation.
9.3 The Normal Distribution.
9.4 Normal Approximation to the Binomial Distribution.
10. Markov Chains.
10.2 Regular Markov Chains.
10.3 Absorbing Markov Chains.
11. Game Theory.
11.2 Mixed Strategies.
11.3 Game Theory and Linear Programming.
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