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This set includes
Finite Mathematics: Models and Applications emphasizes cross-disciplinary applications that relate mathematics to everyday life. The book provides a unique combination of practical mathematical applications to illustrate the wide use of mathematics in fields ranging from business, economics, finance, management, operations research, and the life and social sciences.
The book features coverage including: Algebra Skills; Mathematics of Finance; Matrix Algebra; Geometric Solutions; Simplex Methods; Application Models; Set and Probability Relationships; Random Variables and…mehr
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This set includes
Finite Mathematics: Models and Applications emphasizes cross-disciplinary applications that relate mathematics to everyday life. The book provides a unique combination of practical mathematical applications to illustrate the wide use of mathematics in fields ranging from business, economics, finance, management, operations research, and the life and social sciences.
The book features coverage including: Algebra Skills; Mathematics of Finance; Matrix Algebra; Geometric Solutions; Simplex Methods; Application Models; Set and Probability Relationships; Random Variables and Probability Distributions; Markov Chains; Mathematical Statistics; Enrichment in Finite Mathematics
Finite Mathematics: Models and Applications emphasizes cross-disciplinary applications that relate mathematics to everyday life. The book provides a unique combination of practical mathematical applications to illustrate the wide use of mathematics in fields ranging from business, economics, finance, management, operations research, and the life and social sciences.
The book features coverage including: Algebra Skills; Mathematics of Finance; Matrix Algebra; Geometric Solutions; Simplex Methods; Application Models; Set and Probability Relationships; Random Variables and Probability Distributions; Markov Chains; Mathematical Statistics; Enrichment in Finite Mathematics
Produktdetails
- Produktdetails
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 712
- Erscheinungstermin: 2. November 2015
- Englisch
- Abmessung: 259mm x 185mm x 38mm
- Gewicht: 1361g
- ISBN-13: 9781119015536
- ISBN-10: 1119015537
- Artikelnr.: 41562029
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 712
- Erscheinungstermin: 2. November 2015
- Englisch
- Abmessung: 259mm x 185mm x 38mm
- Gewicht: 1361g
- ISBN-13: 9781119015536
- ISBN-10: 1119015537
- Artikelnr.: 41562029
Carla C. Morris, PhD, ?is Assistant Professor of Mathematics in the Associate in Arts Program at the University of Delaware. A member of The Institute for Operations Research and the Management Sciences and the Mathematical Association of America, Dr. Morris teaches courses ranging from college algebra to calculus and statistics. Robert M. Stark, PhD, ?is Professor Emeritus in the Departments of Mathematical Sciences and Civil and Environmental Engineering at the University of Delaware. Dr. Stark's teaching and research interests include applied probability, mathematical optimization, operations research, and mathematics education.
Preface ix About the Authors xi 1 Linear Equations and Mathematical
Concepts 1 1.1 Solving Linear Equations 2 1.2 Equations of Lines and Their
Graphs 7 1.3 Solving Systems of Linear Equations 15 1.4 The Numbers pi and
e 21 1.5 Exponential and Logarithmic Functions 24 1.6 Variation 32 1.7 Unit
Conversions and Dimensional Analysis 38 2 Mathematics of Finance 47 2.1
Simple and Compound Interest 47 2.2 Ordinary Annuity 55 2.3 Amortization 59
2.4 Arithmetic and Geometric Sequences 63 3 Matrix Algebra 71 3.1 Matrices
72 3.2 Matrix Notation, Arithmetic, and Augmented Matrices 78 3.3
Gauss-Jordan Elimination 89 3.4 Matrix Inversion and Input-Output Analysis
100 4 Linear Programming - Geometric Solutions 116 Introduction 116 4.1
Graphing Linear Inequalities 117 4.2 Graphing Systems of Linear
Inequalities 121 4.3 Geometric Solutions to Linear Programs 125 5 Linear
Programming - Simplex Method 136 5.1 The Standard Maximization Problem
(SMP) 137 5.2 Tableaus and Pivot Operations 142 5.3 Optimal Solutions and
the Simplex Method 149 5.4 Dual Programs 161 5.5 Non-SMP Linear Programs
167 6 Linear Programming - Application Models 182 7 Set and Probability
Relationships 203 7.1 Sets 204 7.2 Venn Diagrams 210 7.3 Tree Diagrams 216
7.4 Combinatorics 221 7.5 Mathematical Probability 231 7.6 Bayes' Rule and
Decision Trees 245 8 Random Variables and Probability Distributions 259 8.1
Random Variables 259 8.2 Bernoulli Trials and the Binomial Distribution 265
8.3 The Hypergeometric Distribution 273 8.4 The Poisson Distribution 279 9
Markov Chains 285 9.1 Transition Matrices and Diagrams 286 9.2 Transitions
291 9.3 Regular Markov Chains 295 9.4 Absorbing Markov Chains 304 10
Mathematical Statistics 314 10.1 Graphical Descriptions of Data 315 10.2
Measures of Central Tendency and Dispersion 323 10.3 The Uniform
Distribution 331 10.4 The Normal Distribution 334 10.5 Normal Distribution
Applications 348 10.6 Developing and Conducting a Survey 363 11 Enrichment
in Finite Mathematics 371 11.1 Game Theory 372 11.2 Applications in Finance
and Economics 385 11.3 Applications in Social and Life Sciences 394 11.4
Monte Carlo Method 403 11.5 Dynamic Programming 422 Answers to Odd Numbered
Exercises 439 Using Technology 502 Glossary 506 Index 513
Concepts 1 1.1 Solving Linear Equations 2 1.2 Equations of Lines and Their
Graphs 7 1.3 Solving Systems of Linear Equations 15 1.4 The Numbers pi and
e 21 1.5 Exponential and Logarithmic Functions 24 1.6 Variation 32 1.7 Unit
Conversions and Dimensional Analysis 38 2 Mathematics of Finance 47 2.1
Simple and Compound Interest 47 2.2 Ordinary Annuity 55 2.3 Amortization 59
2.4 Arithmetic and Geometric Sequences 63 3 Matrix Algebra 71 3.1 Matrices
72 3.2 Matrix Notation, Arithmetic, and Augmented Matrices 78 3.3
Gauss-Jordan Elimination 89 3.4 Matrix Inversion and Input-Output Analysis
100 4 Linear Programming - Geometric Solutions 116 Introduction 116 4.1
Graphing Linear Inequalities 117 4.2 Graphing Systems of Linear
Inequalities 121 4.3 Geometric Solutions to Linear Programs 125 5 Linear
Programming - Simplex Method 136 5.1 The Standard Maximization Problem
(SMP) 137 5.2 Tableaus and Pivot Operations 142 5.3 Optimal Solutions and
the Simplex Method 149 5.4 Dual Programs 161 5.5 Non-SMP Linear Programs
167 6 Linear Programming - Application Models 182 7 Set and Probability
Relationships 203 7.1 Sets 204 7.2 Venn Diagrams 210 7.3 Tree Diagrams 216
7.4 Combinatorics 221 7.5 Mathematical Probability 231 7.6 Bayes' Rule and
Decision Trees 245 8 Random Variables and Probability Distributions 259 8.1
Random Variables 259 8.2 Bernoulli Trials and the Binomial Distribution 265
8.3 The Hypergeometric Distribution 273 8.4 The Poisson Distribution 279 9
Markov Chains 285 9.1 Transition Matrices and Diagrams 286 9.2 Transitions
291 9.3 Regular Markov Chains 295 9.4 Absorbing Markov Chains 304 10
Mathematical Statistics 314 10.1 Graphical Descriptions of Data 315 10.2
Measures of Central Tendency and Dispersion 323 10.3 The Uniform
Distribution 331 10.4 The Normal Distribution 334 10.5 Normal Distribution
Applications 348 10.6 Developing and Conducting a Survey 363 11 Enrichment
in Finite Mathematics 371 11.1 Game Theory 372 11.2 Applications in Finance
and Economics 385 11.3 Applications in Social and Life Sciences 394 11.4
Monte Carlo Method 403 11.5 Dynamic Programming 422 Answers to Odd Numbered
Exercises 439 Using Technology 502 Glossary 506 Index 513
Preface ix About the Authors xi 1 Linear Equations and Mathematical
Concepts 1 1.1 Solving Linear Equations 2 1.2 Equations of Lines and Their
Graphs 7 1.3 Solving Systems of Linear Equations 15 1.4 The Numbers pi and
e 21 1.5 Exponential and Logarithmic Functions 24 1.6 Variation 32 1.7 Unit
Conversions and Dimensional Analysis 38 2 Mathematics of Finance 47 2.1
Simple and Compound Interest 47 2.2 Ordinary Annuity 55 2.3 Amortization 59
2.4 Arithmetic and Geometric Sequences 63 3 Matrix Algebra 71 3.1 Matrices
72 3.2 Matrix Notation, Arithmetic, and Augmented Matrices 78 3.3
Gauss-Jordan Elimination 89 3.4 Matrix Inversion and Input-Output Analysis
100 4 Linear Programming - Geometric Solutions 116 Introduction 116 4.1
Graphing Linear Inequalities 117 4.2 Graphing Systems of Linear
Inequalities 121 4.3 Geometric Solutions to Linear Programs 125 5 Linear
Programming - Simplex Method 136 5.1 The Standard Maximization Problem
(SMP) 137 5.2 Tableaus and Pivot Operations 142 5.3 Optimal Solutions and
the Simplex Method 149 5.4 Dual Programs 161 5.5 Non-SMP Linear Programs
167 6 Linear Programming - Application Models 182 7 Set and Probability
Relationships 203 7.1 Sets 204 7.2 Venn Diagrams 210 7.3 Tree Diagrams 216
7.4 Combinatorics 221 7.5 Mathematical Probability 231 7.6 Bayes' Rule and
Decision Trees 245 8 Random Variables and Probability Distributions 259 8.1
Random Variables 259 8.2 Bernoulli Trials and the Binomial Distribution 265
8.3 The Hypergeometric Distribution 273 8.4 The Poisson Distribution 279 9
Markov Chains 285 9.1 Transition Matrices and Diagrams 286 9.2 Transitions
291 9.3 Regular Markov Chains 295 9.4 Absorbing Markov Chains 304 10
Mathematical Statistics 314 10.1 Graphical Descriptions of Data 315 10.2
Measures of Central Tendency and Dispersion 323 10.3 The Uniform
Distribution 331 10.4 The Normal Distribution 334 10.5 Normal Distribution
Applications 348 10.6 Developing and Conducting a Survey 363 11 Enrichment
in Finite Mathematics 371 11.1 Game Theory 372 11.2 Applications in Finance
and Economics 385 11.3 Applications in Social and Life Sciences 394 11.4
Monte Carlo Method 403 11.5 Dynamic Programming 422 Answers to Odd Numbered
Exercises 439 Using Technology 502 Glossary 506 Index 513
Concepts 1 1.1 Solving Linear Equations 2 1.2 Equations of Lines and Their
Graphs 7 1.3 Solving Systems of Linear Equations 15 1.4 The Numbers pi and
e 21 1.5 Exponential and Logarithmic Functions 24 1.6 Variation 32 1.7 Unit
Conversions and Dimensional Analysis 38 2 Mathematics of Finance 47 2.1
Simple and Compound Interest 47 2.2 Ordinary Annuity 55 2.3 Amortization 59
2.4 Arithmetic and Geometric Sequences 63 3 Matrix Algebra 71 3.1 Matrices
72 3.2 Matrix Notation, Arithmetic, and Augmented Matrices 78 3.3
Gauss-Jordan Elimination 89 3.4 Matrix Inversion and Input-Output Analysis
100 4 Linear Programming - Geometric Solutions 116 Introduction 116 4.1
Graphing Linear Inequalities 117 4.2 Graphing Systems of Linear
Inequalities 121 4.3 Geometric Solutions to Linear Programs 125 5 Linear
Programming - Simplex Method 136 5.1 The Standard Maximization Problem
(SMP) 137 5.2 Tableaus and Pivot Operations 142 5.3 Optimal Solutions and
the Simplex Method 149 5.4 Dual Programs 161 5.5 Non-SMP Linear Programs
167 6 Linear Programming - Application Models 182 7 Set and Probability
Relationships 203 7.1 Sets 204 7.2 Venn Diagrams 210 7.3 Tree Diagrams 216
7.4 Combinatorics 221 7.5 Mathematical Probability 231 7.6 Bayes' Rule and
Decision Trees 245 8 Random Variables and Probability Distributions 259 8.1
Random Variables 259 8.2 Bernoulli Trials and the Binomial Distribution 265
8.3 The Hypergeometric Distribution 273 8.4 The Poisson Distribution 279 9
Markov Chains 285 9.1 Transition Matrices and Diagrams 286 9.2 Transitions
291 9.3 Regular Markov Chains 295 9.4 Absorbing Markov Chains 304 10
Mathematical Statistics 314 10.1 Graphical Descriptions of Data 315 10.2
Measures of Central Tendency and Dispersion 323 10.3 The Uniform
Distribution 331 10.4 The Normal Distribution 334 10.5 Normal Distribution
Applications 348 10.6 Developing and Conducting a Survey 363 11 Enrichment
in Finite Mathematics 371 11.1 Game Theory 372 11.2 Applications in Finance
and Economics 385 11.3 Applications in Social and Life Sciences 394 11.4
Monte Carlo Method 403 11.5 Dynamic Programming 422 Answers to Odd Numbered
Exercises 439 Using Technology 502 Glossary 506 Index 513