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Quantitative methods for decision makers / Mik Wisniewski.

By: Wisniewski, Mik.
Publisher: Harlow : Financial Times Prentice Hall, 2006Edition: 4th ed.Description: xix, 592 p. : ill. ; 27 cm.ISBN: 0273687891 (hbk.) :; 9780273687894.Subject(s): Decision making -- Mathematics | Decision making -- Mathematical models | Decision making -- Mathematics -- Problems, exercises, etc | Management science | Management decision making | Management & management techniques | Business mathematics & systems | Operational research | Business and ManagementDDC classification: 658.4033 WIS Summary: Focusing on the practical uses of the techniques, this text encompasses a mixture of quantitative methods and provides the manager with a detailed overview of how such techniques fit in to the wider management process.
Holdings
Item type Current library Call number Copy number Status Barcode
General lending MTU Kerry North Campus Library First Floor Main 658.4033 WIS (Browse shelf(Opens below)) 1 Available 38888000493597
Total holds: 0

Enhanced descriptions from Syndetics:

Appealing both to students on introductory courses for quantitative methods and MBA and post-experience students, this respected text provides an accessible, practical introduction to an area that students often find difficult.

Concentrating on helping students to understand the relevance of quantitative methods of analysis to managers' decision-making, it focuses on the development of appropriate skills and understanding of how the techniques fit into the wider management process.

Previous ed.: 2002.

Includes bibliographical references and index.

Focusing on the practical uses of the techniques, this text encompasses a mixture of quantitative methods and provides the manager with a detailed overview of how such techniques fit in to the wider management process.

Table of contents provided by Syndetics

  • Preface (p. xiv)
  • Guided Tour (p. xvi)
  • Acknowledgements (p. xviii)
  • 1 Introduction (p. 1)
  • The Use of Quantitative Techniques by Business (p. 2)
  • The Role of Quantitative Techniques in Business (p. 6)
  • Models in Quantitative Decision Making (p. 9)
  • Use of Computers (p. 9)
  • Using the Text (p. 10)
  • Summary (p. 11)
  • Further reading (p. 11)
  • Useful online resources (p. 12)
  • Application: British Telecom (p. 12)
  • 2 Tools of the Trade (p. 16)
  • Learning objectives (p. 16)
  • Some Basic Terminology (p. 17)
  • Fractions, Proportions, Percentages (p. 18)
  • Rounding and Significant Figures (p. 19)
  • Common Notation (p. 21)
  • Powers and Roots (p. 23)
  • Logarithms (p. 24)
  • Summation and Factorials (p. 26)
  • Equations and Mathematical Models (p. 27)
  • Graphs (p. 29)
  • Real and Money Terms (p. 35)
  • Summary (p. 36)
  • Further reading (p. 37)
  • Exercises (p. 38)
  • 3 Presenting Management Information (p. 40)
  • Learning objectives (p. 40)
  • A Business Example (p. 41)
  • Bar Charts (p. 44)
  • Pie Charts (p. 52)
  • Frequency Distributions (p. 54)
  • Percentage and Cumulative Frequencies (p. 56)
  • Histograms (p. 58)
  • Frequency Polygons (p. 61)
  • Ogives (p. 62)
  • Lorenz Curves (p. 64)
  • Time-series Graphs (p. 66)
  • Z Charts (p. 68)
  • Scatter Diagrams (p. 74)
  • General Principles of Graphical Presentation (p. 77)
  • Worked Example (p. 78)
  • Summary (p. 82)
  • Further reading (p. 83)
  • Useful online resources (p. 83)
  • Application: Cowie Health Centre, Scotland (p. 84)
  • Exercises (p. 87)
  • 4 Management Statistics (p. 93)
  • Learning objectives (p. 93)
  • A Business Example (p. 94)
  • Why are Statistics Needed? (p. 95)
  • Measures of Averages (p. 96)
  • Measures of Variability (p. 100)
  • Using the Statistics (p. 111)
  • Calculating Statistics for Aggregated Data (p. 113)
  • Index Numbers (p. 117)
  • Worked Example (p. 125)
  • Summary (p. 126)
  • Further reading (p. 127)
  • Useful online resources (p. 127)
  • Application: Halifax plc: house price index (p. 127)
  • Exercises (p. 134)
  • 5 Probability and Probability Distributions (p. 138)
  • Learning objectives (p. 138)
  • Terminology (p. 141)
  • The Multiplication Rule (p. 144)
  • The Addition Rule (p. 145)
  • A Business Application (p. 146)
  • Probability Distributions (p. 149)
  • The Binomial Distribution (p. 152)
  • The Normal Distribution (p. 159)
  • Worked Example (p. 168)
  • Summary (p. 173)
  • Further reading (p. 173)
  • Useful online resources (p. 173)
  • Application: ICI Pharmaceuticals (p. 174)
  • Exercises (p. 177)
  • 6 Decision Making Under Uncertainty (p. 180)
  • Learning objectives (p. 180)
  • The Decision Problem (p. 181)
  • The Maximax Criterion (p. 184)
  • The Maximin Criterion (p. 184)
  • The Minimax Regret Criterion (p. 184)
  • Decision Making Using Probability Information (p. 186)
  • Risk (p. 187)
  • Decision Trees (p. 189)
  • The Value of Perfect Information (p. 192)
  • Worked Example (p. 194)
  • Summary (p. 196)
  • Further reading (p. 196)
  • Useful online resources (p. 197)
  • Application: Gulf Oil (p. 197)
  • Exercises (p. 200)
  • 7 Market Research and Statistical Inference (p. 203)
  • Learning objectives (p. 203)
  • Populations and Samples (p. 205)
  • Sampling Distributions (p. 210)
  • The Central Limit Theorem (p. 211)
  • Characteristics of the Sampling Distribution (p. 212)
  • Confidence Intervals (p. 213)
  • Other Confidence Intervals (p. 215)
  • Confidence Intervals for Proportions (p. 217)
  • Interpreting Confidence Intervals (p. 219)
  • Hypothesis Tests (p. 219)
  • Tests on a Sample Mean (p. 227)
  • Tests on the Difference Between Two Means (p. 228)
  • Tests on Two Proportions or Percentages (p. 230)
  • Tests on Small Samples (p. 232)
  • Inferential Statistics Using a Computer Package (p. 235)
  • p Values in Hypothesis Tests (p. 236)
  • x[superscript 2] Tests (p. 237)
  • Worked Example (p. 244)
  • Summary (p. 250)
  • Further reading (p. 250)
  • Useful online resources (p. 251)
  • Application: Queen's College, Taunton (p. 251)
  • Exercises (p. 255)
  • 8 Quality Control and Quality Management (p. 262)
  • Learning objectives (p. 262)
  • The Importance of Quality (p. 263)
  • Techniques in Quality Management (p. 264)
  • Statistical Process Control (p. 265)
  • Control Charts (p. 267)
  • Control Charts for Attribute Variables (p. 275)
  • Pareto Charts (p. 276)
  • Ishikawa Diagrams (p. 277)
  • Worked Example (p. 279)
  • Summary (p. 281)
  • Further reading (p. 282)
  • Useful online resources (p. 283)
  • Application: Hewlett-Packard (p. 283)
  • Exercises (p. 285)
  • 9 Forecasting I: Moving Averages and Time Series (p. 287)
  • Learning objectives (p. 287)
  • The Need for Forecasting (p. 288)
  • Approaches to Forecasting (p. 293)
  • Trend Projections (p. 296)
  • Time-series Models (p. 310)
  • Worked Example (p. 324)
  • Summary (p. 326)
  • Further reading (p. 327)
  • Useful online resources (p. 327)
  • Application: Retail supermarket, UK (p. 328)
  • Exercises (p. 330)
  • 10 Forecasting II: Regression (p. 335)
  • Learning objectives (p. 335)
  • The Principles of Simple Linear Regression (p. 336)
  • The Correlation Coefficient (p. 340)
  • The Line of Best Fit (p. 344)
  • Using the Regression Equation (p. 347)
  • Further Statistical Evaluation of the Regression Equation (p. 348)
  • Non-linear Regression (p. 361)
  • Multiple Regression (p. 363)
  • The Forecasting Process (p. 376)
  • Worked Example (p. 381)
  • Summary (p. 386)
  • Further reading (p. 386)
  • Useful online resources (p. 386)
  • Application: RAC (p. 387)
  • Exercises (p. 392)
  • 11 Linear Programming (p. 399)
  • Learning objectives (p. 399)
  • The Business Problem (p. 400)
  • Formulating the Problem (p. 401)
  • Graphical Solution to the LP Formulation (p. 403)
  • Sensitivity Analysis (p. 410)
  • Computer Solutions (p. 413)
  • Assumptions of the Basic Model (p. 415)
  • Dealing with More than Two Variables (p. 415)
  • Extensions to the Basic LP Model (p. 419)
  • Worked Example (p. 419)
  • Summary (p. 425)
  • Further reading (p. 425)
  • Useful online resources (p. 426)
  • Application: Blue Bell Inc. (p. 427)
  • Exercises (p. 429)
  • 12 Stock Control (p. 431)
  • Learning objectives (p. 431)
  • The Stock-control Problem (p. 432)
  • Costs Involved in Stock Control (p. 433)
  • The Stock-control Decision (p. 435)
  • The Economic Order Quantity Model (p. 438)
  • The Reorder Cycle (p. 439)
  • Assumptions of the EOQ Model (p. 440)
  • Incorporating Lead Time (p. 440)
  • Classification of Stock Items (p. 441)
  • MRP and JIT (p. 445)
  • Worked Example (p. 452)
  • Summary (p. 454)
  • Further reading (p. 454)
  • Useful online resources (p. 454)
  • Application: Unipart (p. 455)
  • Exercises (p. 457)
  • 13 Project Management (p. 459)
  • Learning objectives (p. 459)
  • Characteristics of a Project (p. 460)
  • Project Management (p. 460)
  • Business Example (p. 461)
  • Network Diagrams (p. 466)
  • Developing the Network Diagram (p. 470)
  • Using the Network Diagram (p. 474)
  • Precedence Diagrams (p. 475)
  • Gantt Charts (p. 477)
  • Uncertainty (p. 479)
  • Project Costs and Crashing (p. 482)
  • Worked Example (p. 484)
  • Summary (p. 486)
  • Further reading (p. 487)
  • Useful online resources (p. 487)
  • Application: Central Regional Council, Scotland (p. 488)
  • Exercises (p. 490)
  • 14 Simulation (p. 496)
  • Learning objectives (p. 496)
  • The Principles of Simulation (p. 497)
  • Business Example (p. 499)
  • Developing the Simulation Model (p. 500)
  • A Simulation Flowchart (p. 501)
  • Using the Model (p. 504)
  • Worked Example (p. 512)
  • Summary (p. 516)
  • Further reading (p. 517)
  • Useful online resources (p. 518)
  • Application: University Hospital of Wales (p. 518)
  • Exercises (p. 524)
  • 15 Financial Decision Making (p. 529)
  • Learning objectives (p. 529)
  • Interest (p. 530)
  • Nominal and Effective Interest (p. 532)
  • Present Value (p. 533)
  • Investment Appraisal (p. 535)
  • Replacing Equipment (p. 540)
  • Worked Example (p. 545)
  • Summary (p. 546)
  • Further Reading (p. 550)
  • Application: Tomco Oil Inc. (p. 550)
  • Exercises (p. 553)
  • Conclusion (p. 556)
  • Appendices
  • A Binomial Distribution (p. 557)
  • B Areas in the Tail of the Normal Distribution (p. 562)
  • C Areas in the Tail of the t Distribution (p. 563)
  • D Areas in the Tail of the x[superscript 2] Distribution (p. 564)
  • E Areas in the Tail of the F Fistribution, 0.05 Level (p. 565)
  • F Solutions to Chapter Activities (p. 567)
  • Index (p. 585)

Author notes provided by Syndetics

Mik Wisniewski is Senior Research Fellow at Strathclyde Business School in Scotland