Quantitative Methods for Decision Makers

Series
Financial Times
Author
Mik Wisniewski  
Publisher
Pearson
Cover
Softcover
Edition
6
Language
English
Total pages
632
Pub.-date
March 2016
ISBN13
9780273770688
ISBN
0273770683
Related Titles


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Description

Were you looking for the book with access to MyMathLab Global? This product is the book alone and does NOT come with access to MyMathLab Global. Buy Quantitative Methods for Decision Makers, 6th edition with MyMathLab Global access card (ISBN 9780273770763) if you need access to MyMathLab Global as well, and save money on this resource. You will also need a course ID from your instructor to access MyMathLab Global.

 

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.

Table of Contents

Contents

 

List of ‘QMDM in Action’ case studies

Preface  

Acknowledgements

 

1   Introduction

 

The Use of Quantitative Techniques by Business

The Role of Quantitative Techniques in Business

Models in Quantitative Decision Making

Use of Computers

Using the Text

Summary

 

2  Tools of the Trade

 

Learning objectives

Some Basic Terminology

Fractions, Proportions, Percentages

Rounding and Significant Figures

Common Notation

Powers and Roots

Logarithms

Summation and Factorials

Equations and Mathematical Models

Graphs

Real and Money Terms

Worked Example

Summary

Exercises

 

3  Presenting Management Information

 

Learning objectives

A Business Example

Bar Charts

Pie Charts

Frequency Distributions

Percentage and Cumulative Frequencies

Histograms

Frequency Polygons

Ogives

Lorenz Curves

Time-Series Graphs

Z Charts

Scatter Diagrams

General Principles of Graphical Presentation

Worked Example

Summary

Exercises

 

4   Management Statistics

 

Learning objectives

A Business Example

Why Are Statistics Needed?

Measures of Average

Measures of Variability

Using the Statistics

Calculating Statistics for Aggregated Data

Index Numbers

Worked Example

Summary

Exercises

 

5   Probability and Probability Distributions

 

Learning objectives

Terminology

The Multiplication Rule

The Addition Rule

A Business Application

Probability Distributions

The Binomial Distribution

The Normal Distribution

Worked Example

Summary

Exercises

 

6  Decision Making Under Uncertainty

 

Learning objectives

The Decision Problem

The Maximax Criterion

The Maximin Criterion

The Minimax Regret Criterion

Decision Making Using Probability Information

Risk

Decision Trees

The Value of Perfect Information

Worked Example

Summary

Exercises

 

7  Market Research and Statistical Inference

 

Learning objectives

Populations and Samples

Sampling Distributions

The Central Limit Theorem

Characteristics of the Sampling Distribution

Confidence Intervals

Other Confidence Intervals

Confidence Intervals for Proportions

Interpreting Confidence Intervals

Hypothesis Tests

Tests on a Sample Mean

Tests on the Difference Between Two Means

Tests on Two Proportions or Percentages

Tests on Small Samples

Inferential Statistics Using a Computer Package

p Values in Hypothesis Tests

x2 Tests

Worked Example

Summary

Exercises
 

8  Quality Control and Quality Management

 

Learning objectives

The Importance of Quality

Techniques in Quality Management

Statistical Process Control

Control Charts

Control Charts for Attribute Variables

Pareto Charts

Ishikawa Diagrams

Six Sigma

Worked Example

Summary

Exercises

 

9  Forecasting I: Moving Averages and Time Series

 

Learning objectives

The Need for Forecasting

Approaches to Forecasting

Trend Projections

Time-Series Models

Worked Example

Summary

Exercises

 

10  Forecasting II: Regression

 

Learning objectives

The Principles of Simple Linear Regression

The Correlation Coefficient

The Line of Best Fit

Using the Regression Equation

Further Statistical Evaluation of the Regression Equation

Non-linear Regression

Multiple Regression

The Forecasting Process

Worked Example

Summary

Exercises
 

11  Linear Programming

 

Learning objectives

The Business Problem

Formulating the Problem

Graphical Solution to the LP Formulation

Sensitivity Analysis

Computer Solutions

Assumptions of the Basic Model

Dealing with More than Two Variables

Extensions to the Basic LP Model

Worked Example

Summary

Exercises

 

12  Stock Control

 

Learning objectives

The Stock-Control Problem

Costs Involved in Stock Control

The Stock-Control Decision

The Economic Order Quantity Model

The Reorder Cycle

Assumptions of the EOQ Model

Incorporating Lead Time

Classification of Stock Items

MRP and JIT

Worked Example

Summary

Exercises

 

13  Project Management

 

Learning objectives

Characteristics of a Project

Project Management

Business Example

Network Diagrams

Developing the Network Diagram

Using the Network Diagram

Precedence Diagrams

Gantt Charts

Uncertainty   

Project Costs and Crashing

Worked Example

Summary

Exercises

 

14  Simulation

 

Learning objectives

The Principles of Simulation

Business Example

Developing the Simulation Model

A Simulation Flowchart

Using the Model

Worked Example

Summary

Exercises

 

15  Financial Decision Making

 

Learning objectives

Interest

Nominal and Effective Interest

Present Value

Investment Appraisal

Replacing Equipment

Worked Example

Summary

Exercises
Conclusion
 
Appendices
A  Binomial Distribution
B  Areas in the Tail of the Normal Distribution
C  Areas in the Tail of the t Distribution
D  Areas in the Tail of the x2 Distribution
E  Areas in the Tail of the F Distribution, 0.05 Level
F Solutions to Progress Check Questions
Index
 

 

Back Cover

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.