Quantitative Methods for Business 13th Edition by David R. Anderson (eBook PDF)

Quantitative Methods for Business 13th Edition by David R. Anderson (eBook PDF) – Digital Ebook – Instant Delivery Download

Product details:

• ISBN-10 ‏ : ‎ 1285866312
• ISBN-13 ‏ : ‎ 978-1285866314
• Author: James J. Cochran, David R. Anderson, Dennis J. Sweeney

You don’t have to be a mathematician to maximize the power of quantitative methods. Written for the current?or future?business professional, QUANTITATIVE METHODS FOR BUSINESS, 13E makes it easy for you to understand how you can most effectively use quantitative methods to make smart, successful decisions. The book’s hallmark problem-scenario approach guides you step by step through the application of mathematical concepts and techniques. Memorable real-life examples demonstrate how and when to use the methods found in the book, while instant online access provides you with Excel worksheets, LINGO, and the Excel add-in Analytic Solver Platform. The chapter on simulation includes a more elaborate treatment of uncertainty by using Microsoft Excel to develop spreadsheet simulation models. The new edition also includes a more holistic approach to variability in project management. Completely up to date, QUANTITATIVE METHODS FOR BUSINESS, 13E reflects the latest trends, issues, and practices from the field.

Table of contents:

Chapter 1: Introduction

Chapter 2: Introduction to Probability

Chapter 3: Probability Distributions

Chapter 4: Decision Analysis

Chapter 5: Utility and Game Theory

Chapter 6: Time Series Analysis and Forecasting

Chapter 7: Introduction to Linear Programming

Chapter 8: Linear Programming: Sensitivity Analysis and Interpretation of Solution

Chapter 9: Linear Programming Applications in Marketing, Finance, and Operations Management

Chapter 10: Distribution and Network Models

Chapter 11: Integer Linear Programming

Chapter 12: Advanced Optimization Applications

Chapter 13: Project Scheduling: PERT/CPM

Chapter 14: Inventory Models

Chapter 15: Waiting Line Models

Chapter 16: Simulation

Chapter 17: Markov Processes

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