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Brief contents Preface xiii Guided tour 000 Note to the reader xv Acknowledgements 000 Introduction: Why quantitative methods? 1 Part 1 NUMBERS HOW WE HANDLE THEM 5 1 Tools of the trade: basic numeracy skills 7 2 Spreadsheets and other computer-based resources 34 Part 2 NUMBERS A MEANS OF COMMUNICATION 37 3 Obtaining the figures: data and data collection 39 4 Presenting the figures: tables and diagrams 58 5 Summarising the figures: measures of location and spread 94 6 Measuring changes: index numbers 121 Part 3 NUMBERS A BASIS FOR DEDUCTION 139 7 A firm foundation: elementary probability 141 8 Patterns of probability: some distributions 164 9 Estimating from samples: inference 197 10 Checking a theory: hypothesis testing 219 11 Making it better: statistics and quality improvement 253 12 Looking for connections: correlation 285 13 Spotting the relationship: line fitting 305 14 Multiple regression 323 Part 4 NUMBERS A TOOL OF PLANNING 341 15 Planning an inventory policy: stock control and simulation 343 16 Forecasting: time-series, semi-log graphs and exponential smoothing 365 17 Allowing for interest: financial mathematics 395 18 Planning production levels: linear programming 416 19 Planning a project: network analysis 437 20 Quantitative methods in the student research project 455 Appendices 469 1 Suggestions for further reading 471 2 Random sampling numbers 472 3 Cumulative binomial probabilities 473 4 Cumulative Poisson probabilities 475 5 Areas under the standard normal curve 477 6 Percentage points of the c2 distribution 478 7 The correlation coefficient 481 8 The t-distribution 482 9 Solutions to selected exercises 483 Index 501 Contents Preface xiii Guided tour 000 Note to the reader xv Acknowledgements 000 Introduction: Why quantitative methods? 1 Part 1 NUMBERS HOW WE HANDLE THEM 1 Tools of the trade: basic numeracy skills 7 Almost everybody s problem 9 Numbers and how we combine them 9 Operation with fractions 11 Decimals: a special kind of fraction 13 Significant figures and rounding 14 Percentages 15 Letters for numbers 16 Powers and roots 17 The use of brackets 18 Solving equations 19 Equations from problems 21 Some unfamiliar symbols 22 Simultaneous equations 22 Straight line graphs 25 Other types of graph 28 Graphing inequalities 28 Sketching graphs 29 Making use of graphs 30 A business application 30 A word about calculators 32 Further reading 33 2 Spreadsheets and other computer-based resources 34 Introduction 34 MicrosoftÂ Excel and the companion website 34 Other statistical and mathematical software 35 Writing out mathematics to word-process or not? 36 Part 2 NUMBERS A MEANS OF COMMUNICATION 3 Obtaining the figures: data and data collection 39 Quantitative methods in practice 40 A multiplicity of measurements 41 Whence information? 44 Collect-it-yourself 45 Where to find second-hand statistics 52 Points for further thought 54 A word of warning 55 Exercises 55 Further reading 57 4 Presenting the figures: tables and diagrams 58 Quantitative methods in practice 59 The management trainee s problem 60 Eye-balling data 61 The narrative approach 62 The do s and don ts of effective tabulation 62 More complicated tables 65 Easily digested diagrams 67 Tabulating quantitative data 73 Diagrams from frequency tables 78 Some simple graphs 83 Tables and diagrams with Excel 86 How not to do it 89 Back to the Tesco charts 90 Exercises 91 Further reading 93 5 Summarising the figures: measures of location and spread 94 Quantitative methods in practice 95 The trade union leader s problem 95 What needs to be measured 96 Measuring location 98 Measuring spread 108 Summary measures with Excel 116 Which should we choose? 116 So what is typical? 118 Exercises 118 Further reading 120 6 Measuring changes: index numbers 121 Quantitative methods in practice 122 The investor s problem 123 What is an index number? 123 Diversifying the diet 125 Weighting the index 126 Calculating the indices 127 Deciding which to use 128 The Retail Price Index 129 What is the use of the RPI? 131 Advising the investor 132 Some technical considerations 133 Other kinds of index 134 Exercises 135 Further reading 138 Part 3 NUMBERS A BASIS FOR DEDUCTION 7 A firm foundation: elementary probability 141 Quantitative methods in practice 142 The product development manager s problem 143 Reckoning the chances 143 Putting probabilities together 147 Tackling problems 150 Giving probabilities a cash value 154 Decision tables 155 Decision trees 157 Drawbacks of the method 160 Exercises 161 Further reading 163 8 Patterns of probability: some distributions 164 Quantitative methods in practice 165 The quality manager s problem 165 The idea of a probability distribution 167 The binomial distribution 169 The Poisson distribution 175 The normal distribution 178 Some further points 189 Probabilities from the computer 192 Thinking again about computer failures 193 Exercises 194 9 Estimating from samples: inference 197 Quantitative methods in practice 198 The dissatisfied customer s problem 199 The sampling distribution of percentages 201 Applications of STEP 204 The sampling distribution of means 211 The problem revisited 214 So how reliable are opinion polls? 216 Exercises 217 Further reading 218 10 Checking a theory: hypothesis testing 219 Quantitative methods in practice 220 The training manager s problem 220 Testing hypotheses about percentages 221 Further points about hypothesis testing 225 Testing hypotheses about means of large samples 228 An alternative way of carrying out hypothesis tests 229 Testing hypotheses about the means of small samples 230 Testing the difference between two sample means 233 Testing hypotheses about more than one proportion 235 Using the c2 distribution 239 More about c2 241 Single-row tables 243 A cautionary note 244 A mixed batch of examples 245 Hypothesis testing with Excel 248 Conclusion 250 Exercises 250 11 Making it better: statistics and quality improvement 253 Quantitative methods in practice 254 The pizza manufacturer s problem 254 The importance of quality 255 Total quality management 256 How can statistics help? 257 Tracking down the problem 257 The effect of variability on processes 266 Can our machines meet the tolerances? 267 Controlling the mean of a capable process 270 Controlling the range 275 Controlling other aspects of a process 276 Sampling inspection 278 How did it work for Ford? 282 Exercises 282 Further reading 284 12 Looking for connections: correlation 285 Quantitative methods in practice 286 The sales manager s problem 287 What kind of relationship? 288 Using the scattergraph 289 Measuring the strength of a relationship: the correlation coefficient 292 Interpreting the correlation coefficient 296 The sales data revisited 298 What we have and have not proved 298 The rank correlation 300 Exercises 302 13 Spotting the relationship: line fitting 305 Quantitative methods in practice 306 More problems for the sales manager! 306 What is a well-fitting line ? 307 Calculating the regression line 310 Using straight lines to forecast over time 317 Regression with Excel 318 Exercises 320 14 Multiple regression 323 Quantitative methods in practice 324 The advertising manager s problem 324 Carrying out the multiple regression 325 Interpreting the results 326 Qualitative variables in a regression equation 328 Using multiple regression to fit curves 331 Some points to watch for when using regression 332 Back to the Treasury Economic Model 335 Exercises 336 Further reading 339 Part 4 NUMBERS A TOOL OF PLANNING 15 Planning an inventory policy: stock control and simulation 343 Quantitative methods in practice 344 The small business s problem 344 The information needed 345 Simplifying the problem 346 Solving the simplified problem 348 Eliminating some assumptions 351 Making and using 352 Allowing stock-outs 354 The effect of errors in estimates 356 Alternative approaches 358 Simulating an inventory process 358 Exercises 362 Further reading 364 16 Forecasting: time-series, semi-log graphs and exponential smoothing 365 Quantitative methods in practice 366 The airline manager s problem 367 Forecasting: when can we do it? 367 Forecasting a steady percentage growth 368 More uses for semi-log graphs 371 Forecasting from a short-term pattern 374 Extracting the trend 376 Analysing the seasonal variations 379 Calculating random variations 380 Getting a forecast 381 Other patterns of variation 381 Forecasting the pie sales figures 383 Forecasting in an unpredictable situation 386 Features of exponential smoothing 388 Software for forecasting 390 Exercises 391 Further reading 394 17 Allowing for interest: financial mathematics 395 Quantitative methods in practice 396 The management accountant s problem 396 The fundamentals of compound interest 397 Applications of the compound interest formula 399 The idea of present value 402 Applications of discounting 405 Calculating mortgage and hire purchase repayments 407 Some further points 409 Comparing investments 409 Computational note 412 Worked examples 413 Exercises 414 Further reading 415 18 Planning production levels: linear programming 416 Quantitative methods in practice 417 The production manager s problem 417 Setting up the model 418 Graphing the model 420 Finding the best solution 422 Varying the constraints 425 Changes in the profits 428 A different type of problem 429 Problems where the solutions must be integers 431 Solving linear programming problems with Excel Solver 431 Reservations and conclusions 433 Exercises 434 Further reading 436 19 Planning a project: network analysis 437 Quantitative methods in practice 438 The office supervisor s problem 438 Drawing up a precedence table 439 Constructing the network 440 Numbering the network 444 An alternative way of drawing the network 445 The shortest time for the job 446 Finding the floats 447 Making the best of it 449 Limitations of the method 451 The technique in practice 451 Exercises 452 Further reading 454 20 Quantitative methods in the student research project 455 The business student s problem 456 What shall I write about? 456 A general methodology for quantitative investigations 458 Examples 466 Further reading 468 Appendices 469 1 Suggestions for further reading 471 2 Random sampling numbers 472 3 Cumulative binomial probabilities 473 4 Cumulative Poisson probabilities 475 5 Areas under the standard normal curve 477 6 Percentage points of the c2 distribution 478 7 The correlation coefficient 481 8 The t-distribution 482 9 Solutions to selected exercises 483 Index 501

Library of Congress Subject Headings for this publication:

Management -- Statistical methods.

Decision making -- Mathematical models.

Statistical decision.