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Widely known for incorporating interesting, relevant, and realistic applications, this text offers many real applications citing current data sources. There are a wide variety of opportunities for use of technology, allowing for increased visualization and a better understanding of difficult concepts.
R. Algebra Reference.
Polynomials.
Factoring.
Rational Expressions.
Equations.
Inequalities.
Exponents.
Radicals.
1. Linear Functions.
Slopes and Equations of Lines.
Linear Functions and Applications.
The Least Squares Line.
2. Systems of Linear Equations and Matrices.
Solution of Linear Systems by the Echelon Method.
Solution of Linear Systems by the Gauss-Jordan Method.
Addition and Subtraction of Matrices.
Multiplication of Matrices.
Matrix Inverses.
Input-Output Models.
3. Linear Programming: The Graphical Method.
Graphing Linear Inequalities.
Solving Linear Programming Problems Graphically.
Applications of Linear Programming.
4. Linear Programming: The Simplex Method.
Slack Variables and the Pivot.
Maximization Problems.
Minimization Problems; Duality.
Nonstandard Problems.
5. Mathematics of Finance.
Simple and Compound Interest.
Future Value of an Annuity.
Present Value of an Annuity; Amortization.
6. Logic.
Statements.
Truth Tables and Equivalent Statements.
The Conditional and Circuits.
More on the Conditional.
Analyzing Arguments and Proofs.
Analyzing Arguments with Quantifiers.
7. Sets and Probability.
Sets.
Applications of Venn Diagrams.
Introduction to Probability.
Basic Concepts of Probability.
Conditional Probability; Independent Events.
Bayes' Theorem.
8. Counting Principles; Further Probability Topics.
The Multiplication Principle; Permutations.
Combinations.
Probability Applications of Counting Principles.
Binomial Probability.
Probability Distributions; Expected Value.
9. Statistics.
Frequency Distributions; Measures of Central Tendency.
Measures of Variation.
The Normal Distribution.
Normal Approximation to the Binomial Distribution.
10. Markov Chains.
Basic Properties of Markov Chains.
Regular Markov Chains.
Absorbing Markov Chains.
11. Game Theory.
Strictly Determined Games.
Mixed Strategies.
Game Theory and Linear Programming
Margaret Lial, Raymond Greenwell and Nathan Ritchey
ISBN13: 978-0321228260Widely known for incorporating interesting, relevant, and realistic applications, this text offers many real applications citing current data sources. There are a wide variety of opportunities for use of technology, allowing for increased visualization and a better understanding of difficult concepts.
Table of Contents
R. Algebra Reference.
Polynomials.
Factoring.
Rational Expressions.
Equations.
Inequalities.
Exponents.
Radicals.
1. Linear Functions.
Slopes and Equations of Lines.
Linear Functions and Applications.
The Least Squares Line.
2. Systems of Linear Equations and Matrices.
Solution of Linear Systems by the Echelon Method.
Solution of Linear Systems by the Gauss-Jordan Method.
Addition and Subtraction of Matrices.
Multiplication of Matrices.
Matrix Inverses.
Input-Output Models.
3. Linear Programming: The Graphical Method.
Graphing Linear Inequalities.
Solving Linear Programming Problems Graphically.
Applications of Linear Programming.
4. Linear Programming: The Simplex Method.
Slack Variables and the Pivot.
Maximization Problems.
Minimization Problems; Duality.
Nonstandard Problems.
5. Mathematics of Finance.
Simple and Compound Interest.
Future Value of an Annuity.
Present Value of an Annuity; Amortization.
6. Logic.
Statements.
Truth Tables and Equivalent Statements.
The Conditional and Circuits.
More on the Conditional.
Analyzing Arguments and Proofs.
Analyzing Arguments with Quantifiers.
7. Sets and Probability.
Sets.
Applications of Venn Diagrams.
Introduction to Probability.
Basic Concepts of Probability.
Conditional Probability; Independent Events.
Bayes' Theorem.
8. Counting Principles; Further Probability Topics.
The Multiplication Principle; Permutations.
Combinations.
Probability Applications of Counting Principles.
Binomial Probability.
Probability Distributions; Expected Value.
9. Statistics.
Frequency Distributions; Measures of Central Tendency.
Measures of Variation.
The Normal Distribution.
Normal Approximation to the Binomial Distribution.
10. Markov Chains.
Basic Properties of Markov Chains.
Regular Markov Chains.
Absorbing Markov Chains.
11. Game Theory.
Strictly Determined Games.
Mixed Strategies.
Game Theory and Linear Programming