Quantitative methods for decision making using Excel:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Oxford
Oxford Univ. Press
2013
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXI, 629 S. Ill., graph. Darst. |
| ISBN: | 9780199694068 |
Staff View
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV041985629 | ||
| 003 | DE-604 | ||
| 005 | 20150107 | ||
| 007 | t | ||
| 008 | 140721s2013 ad|| |||| 00||| eng d | ||
| 020 | |a 9780199694068 |c (pbk.) |9 978-0-19-969406-8 | ||
| 035 | |a (OCoLC)827198114 | ||
| 035 | |a (DE-599)HBZHT017692758 | ||
| 040 | |a DE-604 |b ger | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-11 | ||
| 082 | 0 | |a 658.40300721 | |
| 084 | |a SK 830 |0 (DE-625)143259: |2 rvk | ||
| 100 | 1 | |a Davis, Glyn |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Quantitative methods for decision making using Excel |c Glyn Davis ; Branko Pecar |
| 264 | 1 | |a Oxford |b Oxford Univ. Press |c 2013 | |
| 300 | |a XXI, 629 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 0 | 7 | |a Entscheidungsfindung |0 (DE-588)4113446-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a EXCEL |0 (DE-588)4138932-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Quantitative Methode |0 (DE-588)4232139-6 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Entscheidungsfindung |0 (DE-588)4113446-1 |D s |
| 689 | 0 | 1 | |a Quantitative Methode |0 (DE-588)4232139-6 |D s |
| 689 | 0 | 2 | |a EXCEL |0 (DE-588)4138932-3 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Pecar, Branko |e Verfasser |4 aut | |
| 856 | 4 | 2 | |m HBZ Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027427982&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-027427982 | ||
Record in the Search Index
| _version_ | 1804152388351688704 |
|---|---|
| adam_text | Titel: Quantitative methods for decision making using Excel
Autor: Davis, Glyn
Jahr: 2012
Detailed Contents
How to use this Book xviii
How to use the Online Resource Centre xx
Contributors xxii
Part I Refresher Course in Business Mathematics
and Statistics 1
i Refresher course in key numerical skills 3
Overview 3
Learning objectives 4
1.1 Basic algebra 4
1.1.1 Squares 4
1.1.2 Square roots 4
1.1.3 Indices 4
1.1.4 To solve simple equations 4
1.1.5 Standard form (or scientific notation) 5
1.1.6 Logarithms and exponential functions 5
1.1.7 Linear and non-linear equations 6
1.1.8 Excel mathematical functions 6
1.2 Drawing graphs 6
1.2.1 The coordinates of a point 6
1.2.2 Plotting straight line graphs 7
1.2.3 Linear equation parameters m and c 8
1.2.4 Plotting non-linear relationships when y is a polynomial of x 9
1.3 Describe change with calculus 9
1.3.1 Introducing the concept of differentiation 9
1.3.2 Finding the minimum and maximum value of a function 12
1.3.3 Relationship between differentiation and integration 13
Summary 14
Further reading 14
Formula summary 15
2 Descriptive statistics and basic survey processing 16
Overview 16
Learning outcomes 16
2.1 Datatypes 17
2.1.1 Discrete data 17
2.1.2 Category or nominal data 17
2.1.3 Ordinal data 17
2.1.4 Continuous or numeric data 17
2.2 Creating tables and graphs 18
2.2.1 Tables and frequency distributions using Excel 18
2.2.2 Creating bar and pie charts using Excel 21
2.2.3 Creating a histogram using Excel 25
2.2.4 Creating a scatter plot and time series charts using Excel 30
Student exercises 34
2.3 Providing measures of average, dispersion, and shape for raw data 36
2.3.1 Measures of average using Excel 38
2.3.2 Measures of dispersion using Excel 41
2.3.3 Measures of shape using Excel 44
Student exercises 46
2.4 Basic survey processing 47
2.4.1 A need for questionnaires 47
2.4.2 Types of questions 48
2.4.3 Types of answers 50
2.4.4 Pre-processing of the answers 52
2.4.5 Pivoting the data 54
2.4.6 Charting the data 59
2.4.7 Changing the data or data source 60
Student exercises 61
Techniques in practice 61
Summary 62
Student exercise answers 63
Further reading 65
Textbook resources 65
Web resources 65
Formula summary 66
Part II Decision Making in Marketing,
Sales, and Business Development 67
3 Fundamentals of statistical decision making 69
Overview 69
Learning outcomes 69
3.1 Basic ideas of probability 70
3.1.1 Basic ideas 70
3.1.2 Relative frequency 71
3.1.3 Sample space 75
Student exercises 77
3.2 The probability laws and conditional probability 78
3.2.1 The general addition law 79
3.2.2 Multiplication law and conditional probability 80
3.2.3 Statistical independence 82
Student exercises 84
3.3 Introduction to tree diagrams and Bayes theorem 85
3.3.1 Introduction to a tree diagram in solving problems
involving probability 85
3.3.2 Introduction to Bayes theorem 85
Student exercises 88
3.4 From descriptive statistics to sampling 89
3.4.1 The concepts of population and sampling 89
3.4.2 Sampling with and without replacement 90
3.4.3 Finite and infinite populations and the effects on sampling 92
3.4.4 The sample mean 93
3.4.5 The sample standard deviation 94
3.4.6 The population mean and population standard deviation 96
3.4.7 The sample proportion 97
3.4.8 The population proportion 98
3.4.9 The finite population correction factor 98
3.4.10 Standard error of proportions 100
3.4.11 Central limit theorem 101
3.4.12 Biased and unbiased estimators 101
3.4.13 Standard error of the mean (SEM) 102
3.4.14 Types of sampling frames: probability and non-probability 104
3.4.15 Sampling data collection methods and process 104
3.5 Continuous probability distributions 106
3.5.1 The normal distribution and Excel 106
3.5.2 The standard normal distribution and Excel 109
3.5.3 Sampling from a normal population 112
3.5.4 Checking for normality using Excel 113
3.5.5 Other continuous probability distributions 116
3.5.6 Point and confidence interval estimates using Excel 117
3.5.7 Simple hypothesis testing using Excel 123
Student exercises 133
3.6 Discrete probability distributions 133
3.6.1 The binomial probability distribution and Excel 133
3.6.2 The Poisson probability distribution and Excel 137
3.6.3 Other discrete probability distributions 142
Student exercises 142
Techniques in practice 143
Summary 144
Student exercise answers 145
Further reading 147
Textbook resources 147
Web resources 147
Formula summary 148
Prediction and forecasting 150
Overview 150
Learning outcomes 150
4.1 Introduction to regression and time series models 150
4.2 Modelling linear relationships between data variables 154
4.2.1 Least squares regression using Excel 154
4.2.2 How good is our linear model 156
4.2.3 Linear regression in Excel 159
4.2.4 Fitting regression trend line to scatter plot using Excel 163
4.2.5 Prediction interval for an estimate of Y 165
Student exercises 167
4.3 Non-linear relationships and regression analysis 167
4.3.1 Identifying and fitting non-linear relationships (or trends)
using Excel 168
Student exercises 173
4.4 Trending data (single variable) and introduction to time series analysis 173
4.4.1 Fitting trend line using Excel 174
4.4.2 Difference between regression and time series analysis 179
4.4.3 A trend component 180
4.4.4 Using a trend chart function to forecast time series 181
4.4.5 Moving averages as a trend function 183
Student exercises 188
4.5 Classical time series decomposition 188
4.5.1 Cyclical time series only 189
4.5.2 Seasonal time series only 195
Student exercises 201
4.6 Smoothing methods 201
4.6.1 Exponential smoothing concept 202
4.6.2 Forecasting with exponential smoothing 204
4.6.3 Forecasting seasonal series with exponential smoothing 208
Student exercises 213
4.7 Forecast error analysis 214
4.7.1 Error measurement 214
4.7.2 Types of errors 216
4.7.3 Interpreting errors 218
4.7.4 Error inspection 219
Student exercises 220
Techniques in practice 221
Summary 221
Student exercise answers 222
Further reading 225
Web resources 226
Formula summary 226
Part III Decision Making in Manufacturing
and Quality 229
5 Optimization 231
Overview 231
Learning outcomes 232
5.1 Introduction to linear programming 232
5.1.1 Example uses of linear programming 233
5.1.2 Limitations of linear programming 233
5.1.3 Linear relationships 234
Student exercises 235
5.2 Linear programming with two variables 236
5.2.1 Example of maximization problem 236
5.2.2 Formulation of linear programme 236
5.2.3 Solution of two variable maximization linear programme 239
Student exercises 247
5.3 A two variable minimization problem 248
5.3.1 Example of minimization problem 249
5.3.2 Formulation of linear programme 249
5.3.3 Solution of two variable minimization linear programmes 250
Student exercises 254
5.4 Sensitivity of linear programmes 255
5.4.1 Constraint levels 255
5.4.2 Coefficients of objective 261
Student exercises 263
5.5 Use of Excel Solver for two variable problems 264
Student exercises 272
5.6 Multivariable problems 272
5.6.1 Formulation of transportation problems 273
5.6.2 Use of Excel Solver to solve transportation problems 274
Student exercises 276
Techniques in practice 277
Summary 279
Student exercise answers 280
Further reading 283
Textbook resources 283
6 Inventory and stock control 284
Overview 284
Learning outcomes 285
6.1 Inventory usage 285
Student exercises 289
6.2 An inventory control model 289
Student exercises 291
6.3 Using the Excel Solver 291
Student exercises 294
Student exercises 295
Student exercises 297
6.4 The EOQ with non-instantaneous replenishment 297
Student exercise 300
6.5 The effect of quantity discounts 300
Student exercise 302
6.6 Probabilistic demand 302
Student exercise 304
6.7 Pareto analysis 304
6.8 Models to determine the EOQ and the selling price 305
Student exercise 307
Techniques in practice 307
Summary 308
Student exercise answers 308
Further reading 312
Formula summary 312
7 Statistical quality control 314
Overview 314
Learning objectives 314
7.1 Quality control versus quality assurance 315
7.2 Data cleaning, the z-score, Cherbyshev s theorem, and outliers 317
7.2.1 Data cleaning 317
7.2.2 Z-score 318
7.2.3 Cherbyshev s theorem 325
7.2.4 Managing outliers: a closer look 327
Student exercises 332
7.3 Two, three, four, and five data summaries 333
7.3.1 Two data summary: mean and standard deviation 333
7.3.2 Three data summary: mean, median, and mode 333
7.3.3 Four data summary 334
7.3.4 Five data summary 337
7.3.5 Box and whisker plots 340
Student exercises 344
7.4 Statistical process control 344
7.4.1 Control charts 345
7.4.2 When the process mean and standard deviation are
unknown 350
Student exercises 363
7.5 Exploiting sampling results and control charts in decision making 366
7.5.1 Acceptance and acceptance sampling in quality control 367
7.5.2 The null and alternative hypotheses in acceptance sampling 368
7.5.3 The binomial probability function for acceptance sampling 369
7.5.4 OC—Operating characteristic curve 371
7.5.5 Acceptance sampling as a process 374
Student exercises 375
Techniques in practice 375
Summary 377
Student exercise answers 378
Further reading 385
Textbook resources 385
Web resources 386
Formula summary 386
Appendix 7.1—Choosing the right control chart and method 389
8 Project planning and control 390
Overview 390
Learning outcomes 390
8.1 Project planning 391
8.1.1 Precedence tables 392
8.1.2 Constructing a network diagram 394
Student exercises 402
8.2 Managing and timing a project 404
8.2.1 Evaluating a network diagram 405
Student exercises 413
8.3 Uncertain activity times 414
Student exercises 425
8.4 Controlling a project 425
8.4.1 Crashing a network 426
Student exercises 437
8.4.2 Resource histogram 438
Student exercises 443
Techniques in practice 443
Summary 446
Student exercise answers 447
Further reading 459
Textbook resources 459
Web resources 459
Formula summary 459
Part iv Decision Making in Finance 461
9 Decision making in business 463
Overview 463
Learning outcomes 463
9.1 Introduction to decision making 464
Student exercises 466
9.2 Type 1: Decision makmg with certainty 466
Student exercises 467
9.3 Type 2: Decision making with uncertainty 467
Student exercises 476
9.4 Type 3: Decision making with risk 477
9.4.1 Calculating the expected monetary value, EMV 477
9.4.2 Calculating the expected opportunity loss, EOL 478
9.4.3 Expected value of perfect information 479
9.4.4 Return-to-risk ratio 483
Student exercises 484
9.5 Using decision trees 485
9.5.1 Decision trees 485
9.5.2 Decision trees and Bayes theorem 489
9.5.3 Undertake sensitivity analysis on a decision tree 491
Student exercises 494
9.6 Making a decision using the concept of utility 494
Student exercises 499
Techniques in practice 499
Summary 500
Student exercise answers 500
Further reading 502
Textbook resources 502
Web resources 502
Formula summary 502
10 Decision making in finance 503
Overview 503
Learning outcomes 503
10.1 Simple interest 504
Student exercises 505
10.2 Compound interest and depreciation 505
Student exercises 517
10.3 Increasing the sum invested 517
Student exercises 521
10.4 Sinking funds or future value of an ordinary annuity 521
Student exercises 524
10.5 The concept of present value 524
Student exercises 526
10.6 Trust funds and loan repayments or present value of an
ordinary annuity 526
Student exercises 530
10.7 The present value and net present value of a stream of earnings 530
Student exercises 535
10.8 Internal rate of return and investment decisions 535
Student exercises 541
10.9 Calculating the cost of a mortgage 541
Student exercises 546
Techniques in practice 546
Summary 547
Student exercise answers 547
Further reading 548
Textbook resources 548
Formula summary 548
11 Monte Carlo simulation using Excel 550
Overview 550
Learning outcomes 550
11.1 Introduction to simulation and probability distributions 551
11.1.1 Probability distributions and generating random numbers
using Excel 555
11.1.2 Key characteristics of probability distributions 555
11.1.3 Discrete or empirical distribution 556
11.1.4 Uniform distribution 558
11.1.5 Triangular distribution 562
11.1.6 Normal distribution 566
11.1.7 Binomial distribution 568
11.1.8 Poisson distribution 570
Student exercises 571
11.2 Introduction to Monte Carlo simulation 572
11.2.1 Creating a Monte Carlo simulation model 572
11.2.2 Calculating minimum sample size 583
11.2.3 Savage s flaw of averages 585
Student exercises 588
11.3 Monte Carlo simulation software 592
Techniques in practice 593
Summary 593
Student exercise answers 594
Further reading 595
Textbook resources 595
Web resources 595
Formula summary 596
Glossary of key terms 599
Index 615
|
| any_adam_object | 1 |
| author | Davis, Glyn Pecar, Branko |
| author_facet | Davis, Glyn Pecar, Branko |
| author_role | aut aut |
| author_sort | Davis, Glyn |
| author_variant | g d gd b p bp |
| building | Verbundindex |
| bvnumber | BV041985629 |
| classification_rvk | SK 830 |
| ctrlnum | (OCoLC)827198114 (DE-599)HBZHT017692758 |
| dewey-full | 658.40300721 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.40300721 |
| dewey-search | 658.40300721 |
| dewey-sort | 3658.40300721 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Mathematik Wirtschaftswissenschaften |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01494nam a2200385 c 4500</leader><controlfield tag="001">BV041985629</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20150107 </controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">140721s2013 ad|| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780199694068</subfield><subfield code="c">(pbk.)</subfield><subfield code="9">978-0-19-969406-8</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)827198114</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)HBZHT017692758</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-11</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">658.40300721</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">SK 830</subfield><subfield code="0">(DE-625)143259:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Davis, Glyn</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Quantitative methods for decision making using Excel</subfield><subfield code="c">Glyn Davis ; Branko Pecar</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Oxford</subfield><subfield code="b">Oxford Univ. Press</subfield><subfield code="c">2013</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XXI, 629 S.</subfield><subfield code="b">Ill., graph. Darst.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Entscheidungsfindung</subfield><subfield code="0">(DE-588)4113446-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">EXCEL</subfield><subfield code="0">(DE-588)4138932-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Quantitative Methode</subfield><subfield code="0">(DE-588)4232139-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Entscheidungsfindung</subfield><subfield code="0">(DE-588)4113446-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Quantitative Methode</subfield><subfield code="0">(DE-588)4232139-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">EXCEL</subfield><subfield code="0">(DE-588)4138932-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pecar, Branko</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">HBZ Datenaustausch</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027427982&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027427982</subfield></datafield></record></collection> |
| id | DE-604.BV041985629 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T01:09:55Z |
| institution | BVB |
| isbn | 9780199694068 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027427982 |
| oclc_num | 827198114 |
| open_access_boolean | |
| owner | DE-11 |
| owner_facet | DE-11 |
| physical | XXI, 629 S. Ill., graph. Darst. |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Oxford Univ. Press |
| record_format | marc |
| spelling | Davis, Glyn Verfasser aut Quantitative methods for decision making using Excel Glyn Davis ; Branko Pecar Oxford Oxford Univ. Press 2013 XXI, 629 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Entscheidungsfindung (DE-588)4113446-1 gnd rswk-swf EXCEL (DE-588)4138932-3 gnd rswk-swf Quantitative Methode (DE-588)4232139-6 gnd rswk-swf Entscheidungsfindung (DE-588)4113446-1 s Quantitative Methode (DE-588)4232139-6 s EXCEL (DE-588)4138932-3 s DE-604 Pecar, Branko Verfasser aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027427982&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Davis, Glyn Pecar, Branko Quantitative methods for decision making using Excel Entscheidungsfindung (DE-588)4113446-1 gnd EXCEL (DE-588)4138932-3 gnd Quantitative Methode (DE-588)4232139-6 gnd |
| subject_GND | (DE-588)4113446-1 (DE-588)4138932-3 (DE-588)4232139-6 |
| title | Quantitative methods for decision making using Excel |
| title_auth | Quantitative methods for decision making using Excel |
| title_exact_search | Quantitative methods for decision making using Excel |
| title_full | Quantitative methods for decision making using Excel Glyn Davis ; Branko Pecar |
| title_fullStr | Quantitative methods for decision making using Excel Glyn Davis ; Branko Pecar |
| title_full_unstemmed | Quantitative methods for decision making using Excel Glyn Davis ; Branko Pecar |
| title_short | Quantitative methods for decision making using Excel |
| title_sort | quantitative methods for decision making using excel |
| topic | Entscheidungsfindung (DE-588)4113446-1 gnd EXCEL (DE-588)4138932-3 gnd Quantitative Methode (DE-588)4232139-6 gnd |
| topic_facet | Entscheidungsfindung EXCEL Quantitative Methode |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027427982&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT davisglyn quantitativemethodsfordecisionmakingusingexcel AT pecarbranko quantitativemethodsfordecisionmakingusingexcel |