Quantitative Methods for Decision Makers
6th Edition
Published on 23. March 2016
Book
Paperback/Softback
600 pages
978-0-273-77068-8 (ISBN)
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.
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.
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.
More details
Other editions
New editions
Mik Wisniewski
Quantitative Analysis for Decision Makers
(formerly known as Quantitative Methods for Decision Makers)
Book
11/2019
Pearson Education Limited
€101.82
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Content
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
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