QUANTITATIVE METHODS. for Decision Makers. Mik Wisniewski. Fifth Edition. FT Prentice Hall

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1 Fifth Edition QUANTITATIVE METHODS for Decision Makers Mik Wisniewski Senior Research Fellow, Department of Management Science, University of Strathclyde Business School FT Prentice Hall FINANCIAL TIMES An imprint of Pearson Education Harlow, England London New York Boston San Francisco Toronto Sydney Singapore Hong Kong Tokyo Seoul Taipei New Delhi Cape Town Madrid Mexico City Amsterdam Munich Paris Milan

2 Contents List of 'QMDM in Action' case studies Preface Guided Tour Acknowledgements XIV xv xvii xix 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 Tools of the Trade c 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

3 viii CONTENTS 3 Presenting Management Information A Business Example 47 Bar Charts 50 Pie Charts 58 Frequency Distributions 60 Percentage and Cumulative Frequencies 62 Histograms 64 Frequency Polygons 67 Ogives 68 Lorenz Curves 70 Time-Series Graphs 72 Z Charts 74 Scatter Diagrams 81 General Principles of Graphical Presentation Management Statistics A Business Example 99 Why are Statistics Needed? 100 Measures of Average 101 Measures of Variability 105 Using the Statistics. c 118 Calculating Statistics for Aggregated Data 120 Index Numbers Probability and Probability Distributions Terminology 148 The Multiplication Rule 152 The Addition Rule 153 A Business Application 157

4 CONTENTS ix Probability Distributions, 163 The Binomial Distribution 166 The Normal Distribution Decision Making Under Uncertainty The Decision Problem 195 The Maximax Criterion 198 The Maximin Criterion 198 The Minimax Regret Criterion 198 Decision Making Using Probability Information 200 Risk. 201 Decision Trees 201 The Value of Perfect Information Market Research and Statistical Inference Populations and Samples 219 Sampling Distributions 222 The Central Limit Theorerfi 224 Characteristics of the Sampling Distribution 225 Confidence Intervals 226 Other Confidence Intervals 229 Confidence Intervals for Proportions 230 Interpreting Confidence Intervals 232 Hypothesis Tests 232 Tests on a Sample Mean 240 Tests on the Difference Between Two Means 241 Tests on Two Proportions or Percentages 243 Tests on Small Samples 245 Inferential Statistics Using a Computer Package 247 p Values in Hypothesis Tests 248 X 2 Tests

5 CONTENTS Quality Control and Quality Management The Importance of Quality Techniques in Quality Management Statistical Process Control Control Charts Control Charts for Attribute Variables Pareto Charts Ishikawa Diagrams Forecasting I: Moving Averages and Time Series The Need for Forecasting Approaches to Forecasting Trend Projections Time-Series Models Forecasting II: Regression 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

6 CONTENTS Linear Programming 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 Stock Control 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 Tinie Classification of Stock Items MRP and JIT Project Management Characteristics of a Project Project Management Business Example

7 XII CONTENTS Network Diagrams Developing the Network Diagram Using the Network Diagram Precedence Diagrams Gantt Charts Uncertainty Project Costs and Crashing Simulation The Principles of Simulation Business Example Developing the Simulation Model A Simulation Flowchart Using the Model Financial Decision Making 538 Interest Nominal and Effective Interest Present Value Investment Appraisal Replacing Equipment ' c

8 CONTENTS xiii Conclusion 565 Appendices A Binomial Distribution 566 B Areas in the Tail of the Normal Distribution 571 C Areas in the Tail of the t Distribution 572 D Areas in the Tail of the % 2 Distribution. 573 E Areas in the Tail of the F Fistribution, 0.05 Level 574 F Solutions to Chapter Activities 576 Further Reading 593 Index 599

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