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Finite Mathematics was written for the one-semester finite math course for students majoring in a variety of fieldsbusiness, economics, social science, and biological and physical science. Widely known for incorporating interesting, relevant, and realistic applications, this new edition now offers many more real applications citing current data sources. The new edition now offers more opportunities for use of technology, allowing for increased visualization and a better understanding of difficult concepts. A dedicated Web site rounds out the teaching and learning package, offering extended applications from the book, skill mastery quizzes, and graphing calculator programs tied to the text.
1.1 Slopes and Equations of Lines. 1.2 Linear Functions and Applications. 1.3 The Least Squares Line.
2. Systems of Linear Equations and Matrices.
2.1 Solution of Linear Systems by the Echelon Method. 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.
3.1 Graphing Linear Inequalities. 3.2 Solving Linear Programming Problems Graphically. 3.3 Applications of Linear Programming.
4. Linear Programming: The Simplex Method.
4.1 Slack Variables and the Pivot. 4.2 Maximization Problems. 4.3 Minimization Problems; Duality. 4.4 Nonstandard Problems.
5. Mathematics of Finance.
5.1 Simple and Compound Interest. 5.2 Future Value of an Annuity. 5.3 Present Value of an Annuity; Amortization.
6.1 Statements and Quantifiers. 6.2 Truth Tables and Equivalent Statements. 6.3 The Conditional and Circuits. 6.4 More on the Conditional. 6.5 Analyzing Arguments with Euler Diagrams. 6.6 Analyzing Arguments with Truth Tables.
7. Sets and Probability.
7.1 Sets. 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.
8.1 The Multiplication Principle; Permutations. 8.2 Combinations. 8.3 Probability Applications of Counting Principles. 8.4 Binomial Probability. 8.5 Probability Distributions; Expected Value.
9.1 Frequency Distributions; Measures of Central Tendency. 9.2 Measures of Variation. 9.3 The Normal Distribution. 9.4 Normal Approximation to the Binomial Distribution.