Applied Statistics Using SPSS, STATISTICA, MATLAB and R (eBook)

Contents 6
Preface to the Second Edition 13
Preface to the First Edition 14
Symbols and Abbreviations 16
1 Introduction 22
1.1 Deterministic Data and Random Data 22
1.2 Population, Sample and Statistics 26
1.3 Random Variables 29
1.4 Probabilities and Distributions 31
1.5 Beyond a Reasonable Doubt... 34
1.6 Statistical Significance and Other Significances 38
1.7 Datasets 40
1.8 Software Tools 40
2 Presenting and Summarising the Data 50
2.1 Preliminaries 50
2.2 Presenting the Data 60
2.3 Summarising the Data 79
3 Estimating Data Parameters 102
3.1 Point Estimation and Interval Estimation 102
3.2 Estimating a Mean 106
3.3 Estimating a Proportion 113
3.4 Estimating a Variance 116
3.5 Estimating a Variance Ratio 118
3.6 Bootstrap Estimation 120
Exercises 128
4 Parametric Tests of Hypotheses 131
4.1 Hypothesis Test Procedure 131
4.2 Test Errors and Test Power 135
4.3 Inference on One Population 141
4.4 Inference on Two Populations 146
4.5 Inference on More than Two Populations 161
Exercises 186
5 Non-Parametric Tests of Hypotheses 190
5.1 Inference on One Population 191
5.2 Contingency Tables 208
5.3 Inference on Two Populations 219
5.4 Inference on More Than Two Populations 231
Exercises 237
6 Statistical Classification 242
6.1 Decision Regions and Functions 242
6.2 Linear Discriminants 244
6.3 Bayesian Classification 253
6.4 The ROC Curve 265
6.5 Feature Selection 272
6.6 Classifier Evaluation 275
6.7 Tree Classifiers 278
Exercises 287
7 Data Regression 290
7.1 Simple Linear Regression 291
7.2 Multiple Regression 308
7.3 Building and Evaluating the Regression Model 322
7.4 Regression Through the Origin 333
7.5 Ridge Regression 335
7.6 Logit and Probit Models 341
Exercises 346
8 Data Structure Analysis 348
8.1 Principal Components 348
8.2 Dimensional Reduction 356
8.3 Principal Components of Correlation Matrices 358
8.4 Factor Analysis 366
Exercises 369
9 Survival Analysis 372
9.1 Survivor Function and Hazard Function 372
9.2 Non-Parametric Analysis of Survival 373
9.2 Non-Parametric Analysis of Survival Data 373
9.3 Comparing Two Groups of Survival Data 383
9.4 Models for Survival Data 386
10 Directional Data 394
10.1 Representing Directional Data 394
10.2 Descriptive Statistics 399
10.3 The von Mises Distributions 402
10.4 Assessing the Distribution of Directional Data 406
10.5 Tests on von Mises Distributions 414
10.6 Non-Parametric Tests 416
Exercises 419
Appendix A - Short Survey on Probability Theory 421
A.1 Basic Notions 421
A.2 Conditional Probability and Independence 424
A.3 Compound Experiments 426
A.5 Random Variables and Distributions 428
A.6 Expectation, Variance and Moments 432
A.7 The Binomial and Normal Distributions 436
A.8 Multivariate Distributions 440
Appendix B - Distributions 448
B.1 Discrete Distributions 448
B.2 Continuous Distributions 456
Appendix C - Point Estimation 472
C.1 Definitions 472
C.2 Estimation of Mean and Variance 474
Appendix D - Tables 476
D.1 Binomial Distribution 476
D.2 Normal Distribution 482
D.3 Student´s t Distribution 483
D.4 Chi-Square Distribution 484
D.5 Critical Values for the F Distribution 485
Appendix E - Datasets 486
E.1 Breast Tissue 486
E.2 Car Sale 486
E.3 Cells 487
E.4 Clays 487
E.5 Cork Stoppers 488
E.6 CTG 489
E.7 Culture 490
E.8 Fatigue 490
E.9 FHR 491
E.10 FHR-Apgar 491
E.11 Firms 492
E.12 Flow Rate 492
E.13 Foetal Weight 492
E.14 Forest Fires 493
E.15 Freshmen 493
E.16 Heart Valve 494
E.17 Infarct 495
E.18 Joints 495
E.19 Metal Firms 496
E.20 Meteo 496
E.21 Moulds 496
E.22 Neonatal 497
E.23 Programming 497
E.24 Rocks 498
E.25 Signal & Noise
E.26 Soil Pollution 499
E.27 Stars 499
E.28 Stock Exchange 500
E.29 VCG 501
E.30 Wave 501
E.31 Weather 501
E.32 Wines 502
Appendix F - Tools 503
F.1 MATLAB Functions 503
F.2 R Functions 504
F.3 Tools EXCEL File 505
F.4 SCSize Program 505
References 507
Index 514