Applied Finite Mathematics

by Rupinder Sekhon and Roberta Bloom

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This text covers topics including linear equations, matrices, linear programming, the mathematics of finance, sets and counting, probability, Markov chains, and game theory. Finite Math covers a variety of topics united by their focus on mathematical techniques used in business applications. The growing field of “business analytics” encompasses many types of applications; the text gives insight to some methods used in industry, although we will explore them on a smaller scale.

Description from LibreTexts.

Publisher
De Anza College
Subjects
Mathematics, Applied Mathematics
Licence
CC BY 4.0, as LibreTexts states it
Who can read
Tweens profiles and older, judged from its title and subjects

Contents

LibreTexts writes equations in TeX, and here they show as TeX; the PDF has them typeset.

  1. Front Matter
  2. TitlePage
  3. InfoPage
  4. Table of Contents
  5. Licensing
  6. 1: Linear Equations
  7. 1.1: Graphing a Linear Equation
  8. 1.1.1: Graphing a Linear Equation (Exercises)
  9. 1.2: Slope of a Line
  10. 1.2.1: Slope of a Line (Exercises)
  11. 1.3: Determining the Equation of a Line
  12. 1.3.1: Determining the Equation of a Line (Exercises)
  13. 1.4: Applications
  14. 1.4.1: Applications (Exercises)
  15. 1.5: More Applications
  16. 1.5.1: More Applications (Exercises)
  17. 1.6: Chapter Review
  18. 2: Matrices
  19. 2.1: Introduction to Matrices
  20. 2.1.1: Introduction to Matrices (Exercises)
  21. 2.2: Systems of Linear Equations and the Gauss-Jordan Method
  22. 2.2.1: Systems of Linear Equations and the Gauss-Jordan Method (Exercises)
  23. 2.3: Systems of Linear Equations – Special Cases
  24. 2.3.1: Systems of Linear Equations – Special Cases (Exercises)
  25. 2.4: Inverse Matrices
  26. 2.4.1: Inverse Matrices (Exercises)
  27. 2.5: Application of Matrices in Cryptography
  28. 2.5.1: Application of Matrices in Cryptography (Exercises)
  29. 2.6: Applications – Leontief Models
  30. 2.6.1: Applications – Leontief Models (Exercises)
  31. 2.7: Chapter Review
  32. 3: Linear Programming - A Geometric Approach
  33. 3.1: Maximization Applications
  34. 3.1.1: Maximization Applications (Exercises)
  35. 3.2: Minimization Applications
  36. 3.2.1: Minimization Applications (Exercises)
  37. 3.3: Chapter Review
  38. 4: Linear Programming - The Simplex Method
  39. 4.1: Introduction to Linear Programming Applications in Business, Finance, Medicine, and Social Science
  40. 4.2: Maximization By The Simplex Method
  41. 4.2.1: Maximization By The Simplex Method (Exercises)
  42. 4.3: Minimization By The Simplex Method
  43. 4.3.1: Minimization By The Simplex Method (Exercises)
  44. 4.4: Chapter Review
  45. 5: Exponential and Logarithmic Functions
  46. 5.1: Prelude to Exponential and Logarithmic Functions
  47. 5.2: Exponential Growth and Decay Models
  48. 5.2.1: Exponential Growth and Decay Models (Exercises)
  49. 5.3: Graphs and Properties of Exponential Growth and Decay Functions
  50. 5.3.1: Graphs and Properties of Exponential Growth and Decay Functions (Exercises)
  51. 5.4: Logarithms and Logarithmic Functions
  52. 5.4.1: Logarithms and Logarithmic Functions (Exercises)
  53. 5.5: Graphs and Properties of Logarithmic Functions
  54. 5.5.1: Graphs and Properties of Logarithmic Functions (Exercises)
  55. 5.6: Application Problems with Exponential and Logarithmic Functions
  56. 5.6.1: Applications of Exponential and Logarithmic Functions (Exercises)
  57. 5.7: Chapter Review
  58. 6: Mathematics of Finance
  59. 6.1: Simple Interest and Discount
  60. 6.1.1: Simple Interest and Discount (Exercises)
  61. 6.2: Compound Interest
  62. 6.2.1: Compound Interest (Exercises)
  63. 6.3: Annuities and Sinking Funds
  64. 6.3.1: Annuities and Sinking Funds (Exercises)
  65. 6.4: Present Value of an Annuity and Installment Payment
  66. 6.4.1: Present Value of an Annuity and Installment Payment (Exercises)
  67. 6.5: Miscellaneous Application Problems
  68. 6.5.1: Miscellaneous Application Problems (Exercises)
  69. 6.6: Classification of Finance Problems
  70. 6.6.1: Classification of Finance Problems (Exercises)
  71. 6.7: Chapter Review
  72. 7: Sets and Counting
  73. 7.1: Sets and Counting
  74. 7.1.1: Sets and Counting (Exercises)
  75. 7.2: Tree Diagrams and the Multiplication Axiom
  76. 7.2.1: Tree Diagrams and the Multiplication Axiom (Exercises)
  77. 7.3: Permutations
  78. 7.3.1: Permutations (Exercises)
  79. 7.4: Circular Permutations and Permutations with Similar Elements
  80. 7.4.1: Circular Permutations and Permutations with Similar Elements (Exercises)
  81. 7.5: Combinations
  82. 7.5.1: Combinations (Exercises)
  83. 7.6: Combinations- Involving Several Sets
  84. 7.6.1: Combinations- Involving Several Sets (Exercises)
  85. 7.7: Binomial Theorem
  86. 7.7.1: Binomial Theorem (Exercises)
  87. 7.8: Chapter Review
  88. 8: Probability
  89. 8.1: Sample Spaces and Probability
  90. 8.1.1: Sample Spaces and Probability (Exercises)
  91. 8.2: Mutually Exclusive Events and the Addition Rule
  92. 8.2.1: Mutually Exclusive Events and the Addition Rule (Exercises)
  93. 8.3: Probability Using Tree Diagrams and Combinations
  94. 8.3.1: Probability Using Tree Diagrams and Combinations (Exercises)
  95. 8.4: Conditional Probability
  96. 8.4.1: Conditional Probability (Exercises)
  97. 8.5: Independent Events
  98. 8.5.1: Independent Events (Exercises)
  99. 8.6: Chapter Review
  100. 9: More Probability
  101. 9.1: Binomial Probability
  102. 9.1.1: Binomial Probability (Exercises)
  103. 9.2: Bayes' Formula
  104. 9.2.1: Bayes' Formula (Exercises)
  105. 9.3: Expected Value
  106. 9.3.1: Expected Value (Exercises)
  107. 9.4: Probability Using Tree Diagrams
  108. 9.4.1: Probability Using Tree Diagrams (Exercises)
  109. 9.5: Chapter Review
  110. 10: Markov Chains
  111. 10.1: Introduction to Markov Chains
  112. 10.1.1: Introduction to Markov Chains (Exercises)
  113. 10.2: Applications of Markov Chains
  114. 10.2.1: Applications of Markov Chains (Exercises)
  115. 10.3: Regular Markov Chains
  116. 10.3.1: Regular Markov Chains (Exercises)
  117. 10.4: Absorbing Markov Chains
  118. 10.4.1: Absorbing Markov Chains (Exercises)
  119. 10.5: CHAPTER REVIEW
  120. 11: Game Theory
  121. 11.1: Strictly Determined Games
  122. 11.1.1: Strictly Determined Games (Exercises)
  123. 11.2: Non-Strictly Determined Games
  124. 11.2.1: Non-Strictly Determined Games (Exercises)
  125. 11.3: Reduction by Dominance
  126. 11.3.1: Reduction by Dominance (Exercises)
  127. 11.4: Chapter Review
  128. Back Matter
  129. Calculator Instructions - TI-83+ and TI-84+
  130. Practice Exam
  131. Index
  132. Index
  133. Glossary
  134. Detailed Licensing