Finite Mathematics for the Managerial, Life, and Social Sciences

Soo T. Tan has published numerous papers in Optimal Control Theory and Numerical Analysis. He received his S.B. degree from Massachusetts Institute of Technology, his M.S. degree from the University of Wisconsin-Madison, and his Ph.D. from the University of California at Los Angeles. One of the most important lessons I learned from my early experience teaching these courses is that many of the students come into these courses with some degree of apprehension. This awareness led to the intuitive approach I have adopted in all of my texts.""

PREFACE.
1. STRAIGHT LINES AND LINEAR FUNCTIONS.
The Cartesian Coordinate System. Straight Lines. Linear Functions and Mathematical. Intersection of Straight Lines. The Method of Least Squares.
2. SYSTEMS OF LINEAR EQUATIONS AND MATRICE.
Systems of Linear Equations: An Introduction. Systems of Linear Equations: Unique Solutions. Systems of Linear Equations: Underdetermined and Overdetermined Systems. Matrices. Multiplication of Matrices. The Inverse of a Square Matrix. Leontief Input–Output Model.
3. LINEAR PROGRAMMING: A GEOMETRIC APPROACH.
Graphing Systems of Linear Inequalities in Two Variables. Linear Programming Problems. Graphical Solution of Linear Programming Problems. Sensitivity Analysis.
4. LINEAR PROGRAMMING: AN ALGEBRAIC APPROACH.
The Simplex Method: Standard Maximization Problems. The Simplex Method: Standard Minimization Problems. The Simplex Method: Nonstandard Problems.
5. MATHEMATICS OF FINANCE.
Compound Interest. Annuities. Amortization and Sinking Funds. Arithmetic and Geometric Progressions.
6. SETS AND COUNTING.
Sets and Set Operations. The Number of Elements in a Finite Set. The Multiplication Principle. Permutations and Combinations.
7. PROBABILITY.
Experiments, Sample Spaces, and Events. Definition of Probability. Rules of Probability. Use of Counting Techniques in Probability. Conditional Probability and Independent Events. Bayes’ Theorem.
8. PROBABILITY DISTRIBUTIONS AND STATISTICS.
Distributions of Random Variables. Expected Value. Variance and Standard Deviation. The Binomial Distribution. The Normal Distribution. Applications of the Normal Distribution.
9. MARKOV CHAINS AND THE THEORY OF GAMES.
Markov Chains. Regular Markov Chains. Absorbing Markov Chains. Game Theory and Strictly Determined Games. Games with Mixed Strategies.
APPENDIX A.
Introduction to Logic.
A.1 Propositions and Connectives.
A.2 Truth Tables.
A.3 The Conditional and Biconditional Connectives.
A.4 Laws of Logic.
A.5 Arguments.
A.6 Applications of Logic to Switching Networks
APPENDIX B.
The System of Real Numbers.
APPENDIX C.
Review of Logarithms.
APPENDIX D.
Tables.
Table 1. Binomial Probabilities.
Table 2. The Standard Normal Distribution.