Mathematical Modeling for Business Analytics is written for decision makers at all levels. This book presents the latest tools and techniques available to help in the decision process. The interpretation and explanation of the results are crucial to understanding the strengths and limitations of modeling. This book emphasizes and focuses on the aspects of constructing a useful model formulation, as well as building the skills required for decision analysis. The book also focuses on sensitivity analysis.The author encourages readers to formally think about solving problems by using a thorough process. Many scenarios and illustrative examples are provided to help solve problems. Each chapter is also comprehensively arranged so that readers gain an in-depth understanding of the subject which includes introductions, background information and analysis. Both undergraduate and graduate students taking methods courses in methods and discrete mathematical modeling courses will greatly benefit from using this book.Table of contents :Content: 1. Introduction to Mathematical Modeling for Business Analytics 2. Introduction to Stochastic Decision-Making Models for Business Analytics 3. Mathematical Programming Models: Linear, Integer, and Nonlinear Optimization 4. Introduction to Multi-Attribute Decision-Making in Business Analytics 5. Modeling with Game Theory 6. Regression and Advanced Regression Models 7. Discrete Dynamical System Models 8. Simulation Modeling 9. Mathematics of Finance with Discrete Dynamical System.