ISBN | Product | Product | Price CHF | Available | |
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Quantitative Analysis for Decision Makers, 7th Edition (formerly known as Quantitative Methods for Decision Makers) |
9781292276618 Quantitative Analysis for Decision Makers, 7th Edition (formerly known as Quantitative Methods for Decision Makers) |
74.20 |
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There's no doubt that a manager's job is getting tougher. Do it better, do it faster, do it cheaper are the pressures every manager faces. And at the heart of every manager's job is decision-making: deciding what to do and how to do it. This well-respected text looks at how quantitative analysis techniques can be used effectively to support such decision making.
As a manager, developing a good understanding of the quantitative 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.
Appealing both to students on introductory-level courses and to MBA and postgraduate students, this internationally successful text provides an accessible introduction to a subject area that students often find difficult. Quantitative Analysis for Decision Makers (formerly known as Quantitative Methods for Decision Makers) helps students to understand the relevance of quantitative methods of analysis to management decision-making by relating techniques directly to real-life business decisions in public and private sector organisations and focuses on developing appropriate skills and understanding of how the techniques fit into the wider management process.
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
There's no doubt that a manager's job is getting tougher. Do it better, do it faster, do it cheaper are the pressures every manager faces. And at the heart of every manager's job is decision-making: deciding what to do and how to do it. This well-respected text looks at how quantitative analysis techniques can be used effectively to support such decision making.
As a manager, developing a good understanding of the quantitative 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.
Appealing both to students on introductory-level courses and to MBA and postgraduate students, this internationally successful text provides an accessible introduction to a subject area that students often find difficult. Quantitative Analysis for Decision Makers (formerly known as Quantitative Methods for Decision Makers) helps students to understand the relevance of quantitative methods of analysis to management decision-making by relating techniques directly to real-life business decisions in public and private sector organisations and focuses on developing appropriate skills and understanding of how the techniques fit into the wider management process.
Key features:
Mik Wisniewski has almost five decades of experience in quantitative analysis. He has taught at a number of leading universities, worked in both industry and government and has extensive consultancy experience in the UK and across Europe, Africa, the Middle East and Asia.
Dr. Farhad Shafti is a senior academic with expertise in Management Science. He has extensive experience teaching in highly ranked universities, covering undergraduate, postgraduate and MBA studies in the UK and overseas.