Enhanced descriptions from Syndetics:

Substantially revised and updated, this third edition of Quantitative Methods for Decision Makers'retains its easy-to-read and accessible style. The author provides a detailed understanding of the role and purpose of quantitative methods in effective management and in managerial decision-making.The text focuses on the practical application of techniques by public and private sector managers and shows how such techniques can be incorporated into the wider decision-making process in every organisation. A complete range of quantitative skills is developed using real data sets. New features: * New and updated cases and Financial Times extracts* More international examples* Increased coverage of use and interpretation of software generally * Inclusion of solutions to some text questions to allow students to test their understanding* Restructuring of longer sections into more accessible pieces* Improved Instructor's Manual, including solutions to text questions.Key features: * Includes real-life case studies which help to bring to life the techniques introduced in the text. * Focuses on public and private sector organisations illustrating how techniques can contribute to management decis

Table of contents provided by Syndetics

• 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
• Further Reading
• Application: British Telecom
• 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
• Summary
• Further Reading
• Exercises
• 3 Management Information and Diagrams
• Learning objectives
• 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
• Further Reading
• Application: Cowie Health Centre, Scotland
• Exercises
• 4 Management Statistics
• Learning objectives
• A business example
• Why are statistics needed?
• Measures of averages
• Measures of variability
• Using the statistics
• Calculating statistics for aggregated data
• Index numbers
• Working example
• Summary
• Further Reading
• Application: Halifax Building Society - House Price Index
• 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
• Further Reading
• Application: ICI Pharmaceuticals
• 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
• Further Reading
• Application: Gulf Oil
• Exercises
• 7 Market Research and Statistical Inference
• Learning objectives
• Population 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 test
• Tests on a sample mean
• Tests on the difference between two means
• Tests on two proportions of percentages
• Tests on small samples
• Inferential statistics using a computer package
• P values in hypothesis tests [chi]2 tests
• Worked example
• Summary
• Further Reading
• Application: Queen's College, Taunton
• 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
• Worked example
• Summary
• Further Reading
• Application: Hewlett Packard
• Exercises
• 9 Forecasting I: Moving Averages and Time Series
• Learning objectives
• The need for forecasting
• Alternative approaches for forecasting
• Trend projections
• Time-series models
• Worked example
• Summary
• Further Reading
• Application: Retail supermarket, UK
• 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
• Further Reading
• Application: RAC
• 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
• Further Reading
• Application: Blue Bell, Inc
• 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
• Further Reading
• Application: Unipart
• 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
• Further Reading
• Application: Central Regional Council, Scotland
• Exercises
• 14 Simulation
• Learning objectives
• The principles of simulation
• Business example
• Developing the simulation model
• A simulation flowchart
• Using the model
• Worked example
• Summary
• Further Reading
• Application: University Hospital of Wales
• Exercises
• 15 Financial Decision Making
• Learning objectives
• Interest
• Nominal and effective interest
• Present value
• Investment appraisal
• Replacing equipment
• Worked example
• Summary
• Further Reading
• Application: Tomco Oil Inc
• Exercises