Quantitative Methods for Decision Makers, 6th Edition

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Appealing both to students on introductory courses for quantitative methods and MBA students, this well-respected text provides an accessible introduction to an area that students often find difficult. As a manager, developing a good understanding of the business analysis techniques at your disposal is crucial. Knowing how and when to use them and what their results really mean can be the difference between making a good or bad decision and, ultimately, between business success and failure.

Quantitative Methods for Decision Makers helps students to understand the relevance of quantitative methods of analysis to manager’s decision-making by relating techniques directly to real-life business decisions in public and private sector organisations and focusing on developing appropriate skills and understanding of how the techniques fit into the wider management process.

Key features:

• Student Activities with a solutions Appendix
• Fully worked examples and exercises supported by Excel data sets
• “QMDM in Action” case studies illustrating how real-life organisations benefit from the use of quantitative techniques
• Chapter on financial decision-making

“Wisniewski makes numerical and statistical concepts understandable and brings them to life using excellent scenarios and case studies. This book was a valuable resource during my MBA studies and I am encouraging all my non-statistical colleagues and anyone who works with statistics or performance measurement data to read this book!” Brian J Pickett, Assistant Director, Local Government Data Unit, Wales

Mik Wisniewski is Senior Research Fellow at Strathclyde Business School in Scotland. He also works as a freelance management consultant with clients including PriceWaterhouseCoopers, ScottishPower and Shell, and a variety of public sector organisations in the UK and internationally.

Table of Contents

Chapter 1 Introduction
Chapter 2 Tools of the Trade
Chapter 3 Presenting Management Information
Chapter 4 Management Statistics
Chapter 5 Probability and Probability Distributions
Chapter 6 Decision Making Under Uncertainty
Chapter 7 Market Research and Statistical Inference
Chapter 8 Quality Control and Quality Management
Chapter 9 Forecasting I: Moving Averages and Time Series
Chapter 10 Forecasting II: Regression
Chapter 11 Linear Programming
Chapter 12 Stock Control
Chapter 13 Project Management
Chapter 14 Simulation
Chapter 15 Financial Decision Making