Quantitative Methods for Business Decisions

621 Pages·2013·31.654 MB·English

by  Roger Slater, Jon Curwin

seventh edition
Ouantitative MethOds
For Business Decisions
JON CURWIN
ROGER SLATER
DAVID EADSON
Australia • Brazil • Japan • Korea • Mexico • Singapore • Spain • United Kingdom • United States
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Quantitative Methods For Business © 2013, Cengage Learning EMEA
Decisions, 7th edition
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Jon Curwin, Roger Slater and David Eadson
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1 2 3 4 5 6 7 8 9 10 – 15 14 13
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CONTENTS
Preface ix
List of Mini Cases xi
About the authours xii
About the digital resources xiii
Walk through tour xiv
1 Mathematical Background 1
1A Basic Mathematics 2
Objectives 2
1A.1 Basic arithmetic 3
1A.2 Basic algebra 9
1A.3 Logarithms 14
1A.4 Arithmetic and geometric progressions 15
1A.5 Functions 19
1A.6 Conclusions to Part A 32
1B Financial Mathematics 33
Objectives 33
1B.1 Interest: simple and compound 33
1B.2 Depreciation 36
1B.3 Present value 38
1B.4 The internal rate of return 43
1B.5 Incremental payments 45
1B.6 Annual percentage rate (APR) 50
1B.7 Conclusions to Part B 52
1.8 Questions for Parts A and B 53
iii
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iv CONTENTS
PART ONE UNDERSTANDING
QUANTITATIVE INFORMATION 59
2 The Quantitative Approach 65
Objectives 65
2.1 Problem solving 66
2.2 Methodology 70
2.3 Models 73
2.4 Measurement 79
2.5 Scoring models 81
2.6 Conclusions 85
2.7 Questions 86
3 Managing Data 90
Objectives 90
3.1 Issues of data collection 92
3.2 Published sources 94
3.3 Internet sources 96
3.4 A census or a sample? 98
3.5 Market research 100
3.6 Conclusions 101
3.7 Questions 102
4 Survey Methods 105
Objectives 105
4.1 Probability sampling 108
4.2 Non-probability sampling 113
4.3 Survey design 117
4.4 Questionnaire design 123
4.5 Non-response 128
4.6 Conclusions 130
4.7 Questions 131
PART TWO DESCRIBING DATA 135
5 Presentation of Data 139
Objectives 139
5.1 Raw data 140
5.2 Tabulation of data 140
5.3 Presentation of categorical data 147
5.4 Presentation of continuous data 154
5.5 Graphical representation 161
5.6 Conclusions 168
5.7 Questions 169
6 Measures of Location 174
Objectives 174
6.1 Raw data 177
6.2 Tabulated (ungrouped) discrete data 181
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CONTENTS v
6.3 Tabulated (grouped) continuous data 184
6.4 Other measures of location 191
6.5 Relationships between averages 193
6.6 Conclusions 194
6.7 Questions 195
7 Measures of Dispersion 199
Objectives 199
7.1 The measures 199
7.2 Raw data 200
7.3 Tabulated data 204
7.4 Grouped data 206
7.5 Relative measures of dispersion 213
7.6 Variability in sample data 216
7.7 Conclusions 218
7.8 Questions 218
8 Index Numbers 223
Objectives 223
8.1 The interpretation of an index number 223
8.2 The construction of index numbers 229
8.3 The weighting of index numbers 235
8.4 The Consumer Prices Index and
the Retail Prices Index 236
8.5 Conclusions 242
8.6 Questions 243
PART THREE MEASURING
UNCERTAINTy 249
9 Probability 253
Objectives 253
9.1 Basic concepts 254
9.2 Definitions 256
9.3 Basic relationships in probability 261
9.4 Probability trees 266
9.5 Expected values 269
9.6 Decision trees 271
9.7 Bayes’ theorem 274
9.8 Conclusions 276
9.9 Questions 277
10 Discrete Probability Distributions 282
Objectives 282
10.1 Probability distributions 283
10.2 Discrete probability distributions 284
10.3 Poisson approximation to the binomial 301
10.4 Conclusions 302
10.5 Questions 303
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vi CONTENTS
11 The Normal Distribution 307
Objectives 307
11.1 Characteristics of the Normal distribution 307
11.2 The standard Normal distribution 308
11.3 Combinations of variables 314
11.4 Normal approximations 317
11.5 Other continuous probability distributions 320
11.6 Conclusions 320
11.7 Questions 321
PART FOUR USING STATISTICAL
INFERENCE 325
12 Samples, Estimation and Confidence Intervals 330
Objectives 330
12.1 Statistical inference 331
12.2 Sampling Distributions 332
12.3 Estimation – inference about a population 339
12.4 Confidence interval for the population mean 340
12.5 Confidence interval for a population percentage 347
12.6 The difference between means of independent samples 350
12.7 The finite population correction factor 353
12.8 The t-distribution 355
12.9 Conclusions 361
12.10 Questions 363
13 Significance Testing 367
Objectives 367
13.1 Significance testing using confidence intervals 368
13.2 Hypothesis testing for single large samples 370
13.3 One-sided significance tests 377
13.4 Types of error 383
13.5 Hypothesis testing with two large samples 385
13.6 Hypothesis testing with small samples 388
13.7 Reservations about test conclusions 395
13.8 Conclusions 396
13.9 Questions 397
14 Non-Parametric Tests 401
Objectives 401
14.1 Chi-squared tests 402
14.2 Mann-Whitney U test 416
14.3 Wilcoxon test 419
14.4 Runs test 423
14.5 Conclusions 424
14.6 Questions 426
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CONTENTS vii
PART FIVE RELATING VARIABLES
AND PREDICTING OUTCOMES 431
15 Correlation and Simple Regression Analysis 434
Objectives 434
15.1 Correlation 435
15.2 Measuring linear association 440
15.3 Regression analysis 447
15.4 Simple linear regression 448
15.5 Predictions from the regression line 451
15.6 Regression analysis using ExCEL 456
15.7 Interpretation 457
15.8 Non-linear relationships 458
15.9 Conclusions 462
15.10 Questions 463
16 Multiple Regression Analysis 470
Objectives 470
16.1 The multiple regression model 471
16.2 The effects of adding variables 472
16.3 Investigating the assumptions 475
16.4 Analysis of a multiple regression model 484
16.5 Using multiple regression models 489
16.6 Conclusions 490
16.7 Questions 491
17 Time Series 495
Objectives 495
17.1 Time series models 496
17.2 The trend 499
17.3 The seasonal factors 508
17.4 The cyclical factors 513
17.5 The residual or random factor 514
17.6 Predictions 516
17.7 Developing models for short-term forecasts 519
17.8 Conclusions 525
17.9 Questions 526
ONLINE CONTENTS 531
The following Parts 6-8 can be found by visiting our
premium online platform. See the ‘About the digital
resources’ page for more details.
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viii CONTENTS
PART SIX MODELLING
18 Linear programming
19 Networks
20 Modelling stock control and queues
21 Simulation
22 Game theory
23 Factor analysis
PART SEVEN MATHEMATICAL TOPICS
24 Matrices
25 Use of Calculus
PART EIGHT STUDENT GUIDES
Guide to creative problem solving
Guide to ExCEL
Guide to SPSS
Guide to project management software
Guide to writing and reporting statistics
Appendices 532
A Cumulative binomial probabilities 533
B Cumulative Poisson probabilities 534
C Areas in the right-hand tail of the Normal distribution 535
D Student’s t critical points 537
E c2 critical values 538
F Present value factors 540
G Mann-Whitney test statistic 542
H Wilcoxon test statistic 545
I Runs test 546
J Durbin-Watson statistic 548
K Random number table 550
Answers section 552
Glossary 587
Statistics formula sheet 595
Index 600
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PREFACE
WE WOUld lIkE TO WElCOmE you to a very different seventh edition of Quantitative
Methods for Business Decisions. David Eadson has joined Jon Curwin and Roger Slater
in the author team, and together they have sought to offer a more compact book with
all the qualities of the previous six editions and strengthened the links to online support
materials. This new edition, like the previous editions, is intended for students from a variety of
backgrounds who find that their courses require a good understanding of mathematics and statistics
in a business context. Few assumptions are made about what a student can remember from pre­
vious studies and the focus is on developing the important skills of being effective with numbers.
Each chapter offers an introduction and explanation of some aspect of the quantitative approach to
problem solving. Together these chapters are designed to build a confidence with business problem
analysis but are sufficiently self­contained to be used as a source of reference or for revision purposes.
A review of basic mathematics is now included as the first chapter and allows for an easier revision
of key mathematical topics and for easier cross­referencing if only as a reminder of a mathematical
technique that is required. The book itself is still divided into five parts: Understanding quantitative
information; Describing data; Measuring uncertainty; Using statistical inference; and Relating
variables and predicting outcomes, with a further three parts offered online, adressing Modelling,
Mathematical topics and student guides, respectively. The online support has been considerably
strengthened to include chapters on Game theory and Factor analysis, and student guides on creative
problem solving, ExCEl, SPSS, Project management software, and writing and reporting statistics.
The rationale for the book remains broadly the same, but the following improvements have been
made:
l A review and revision of basic mathematics takes place at the beginning of the book.
l All chapters have been revised to reflect subject and course developments with additional
chapters and student guides being offered online.
l The questions at the end of each chapter have been revised. In addition to the multiple
choice and numeric based exercise questions, a set of discussion questions have been added.
These have been designed to encourage you to explore the application of concepts raised in
each chapter.
l A complete set of fully annotated answers for all end of chapter questions are offered online,
and some can still be found at the end of the book.
ix
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