Applied statistics using SPSS, STATISTICA and MATLAB:
"Aimed at students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB and STATISTICA, this text provides a comprehensive coverage of the main statistical analysis topics important for practical applications such...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin u.a.
Springer
2003
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | "Aimed at students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB and STATISTICA, this text provides a comprehensive coverage of the main statistical analysis topics important for practical applications such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. The relevant notions and methods are explained concisely, illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues. The solutions presented in the examples are obtained with one of the software packages in a pedagogical way. It provides guidance on how to use SPSS, MATLAB and STATISTICA in statistical analysis applications without having to delve in the manuals."--BOOK JACKET. |
| Beschreibung: | XXII, 452 S. Ill., graph. Darst. 1 CD-Rom (12 cm) |
| ISBN: | 3540011560 |
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| 245 | 1 | 0 | |a Applied statistics using SPSS, STATISTICA and MATLAB |c J. P. Marques de Sá |
| 264 | 1 | |a Berlin u.a. |b Springer |c 2003 | |
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| 520 | 1 | |a "Aimed at students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB and STATISTICA, this text provides a comprehensive coverage of the main statistical analysis topics important for practical applications such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. The relevant notions and methods are explained concisely, illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues. The solutions presented in the examples are obtained with one of the software packages in a pedagogical way. It provides guidance on how to use SPSS, MATLAB and STATISTICA in statistical analysis applications without having to delve in the manuals."--BOOK JACKET. | |
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Datensatz im Suchindex
| _version_ | 1805083664668688384 |
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| adam_text |
Contents
Preface vii
Symbols and Abbreviations xvii
1 Introduction 1
1.1 Deterministic Data and Random Data 1
1.2 Population, Sample and Statistics 5
1.3 Random Variables 8
1.4 Probabilities and Distributions 10
1.4.1 Discrete Variables 10
1.4.2 Continuous Variables 12
1.5 Beyond a Reasonable Doubt 13
1.6 STATISTICA, SPSS and MATLAB 17
2 Presenting and Summarising the Data 21
2.1 Preliminaries 21
2.1.1 Reading in the Data 21
2.1.2 Operating with the Data 25
2.2 Presenting the Data 28
2.2.1 Counts and Bar Graphs 28
2.2.2 Frequencies and Histograms 35
2.2.3 Multivariate Tables, Scatter Plots and 3D Plots 39
2.2.4 Categorised Plots 43
2.3 Summarising the Data 45
2.3.1 Measures of Location 45
2.3.2 Measures of Spread 48
2.3.3 Measures of Shape 50
2.3.4 Measures of Association for Continuous Variables 53
2.3.5 Measures of Association for Ordinal Variables 55
2.3.6 Measures of Association for Nominal Variables 59
Exercises 63
x Contents
3 Estimating Data Parameters 67
3.1 Point Estimation and Interval Estimation 67
3.2 Estimating a Mean 71
3.3 Estimating a Proportion 77
3.4 Estimating a Variance 80
3.5 Estimating a Variance Ratio 81
Exercises 83
4 Parametric Tests of Hypotheses 85
4.1 Hypothesis Test Procedure 85
4.2 Test Errors and Test Power 89
4.3 Inference on One Population 95
4.3.1 Testing a Mean 95
4.3.2 Testing a Variance 99
4.4 Inference on Two Populations 100
4.4.1 Testing a Correlation 100
4.4.2 Comparing Two Variances 102
4.4.3 Comparing Two Means 105
4.5 Inference on More Than Two Populations 113
4.5.1 Introduction to the Analysis of Variance 113
4.5.2 One Way ANOVA 114
4.5.3 Two Way ANOVA 127
Exercises 137
5 Non Parametric Tests of Hypotheses 141
5.1 Inference on One Population 142
5.1.1 The Runs Test 142
5.1.2 The Binomial Test 144
5.1.3 The Chi Square Goodness of Fit Test 148
5.1.4 The Kolmogorov Smirnov Goodness of Fit Test 152
5.1.5 The Lilliefors Test for Normality 156
5.1.6 The Shapiro Wilk Test for Normality 156
5.2 Contingency Tables 158
5.2.1 The 2x2 Contingency Table 158
5.2.2 The rxc Contingency Table 162
5.2.3 The Chi Square Test of Independence 164
5.2.4 Measures of Association Revisited 166
5.3 Inference on Two Populations 169
5.3.1 Tests for Two Independent Samples 169
5.3.2 Tests for Two Paired Samples 174
5.4 Inference on More Than Two Populations 180
Contents xi
5.4.1 The Kruskal Wallis Test for Independent Samples 180
5.4.2 The Friedmann Test for Paired Samples 183
5.4.3 The Cochran Q test 185
Exercises 186
6 Statistical Classification 191
6.1 Decision Regions and Functions 191
6.2 Linear Discriminants 193
6.2.1 Minimum Euclidian Distance Discriminant 193
6.2.2 Minimum Mahalanobis Distance Discriminant 196
6.3 Bayesian Classification 202
6.3.1 Bayes Rule for Minimum Risk 202
6.3.2 Normal Bayesian Classification 208
6.3.3 Dimensionality Ratio and Error Estimation 211
6.4 The ROC Curve 214
6.5 Feature Selection 220
6.6 Classifier Evaluation 224
6.7 Tree Classifiers 227
Exercises 233
7 Data Regression 237
7.1 Simple Linear Regression 238
7.1.1 Simple Linear Regression Model 238
7.1.2 Estimating the Regression Function 238
7.1.3 Inferences in Regression Analysis 243
7.1.4 ANOVA Tests 248
7.2 Multiple Regression 252
7.2.1 General Linear Regression Model 252
7.2.2 General Linear Regression in Matrix Terms 253
7.2.3 Inferences on Regression Parameters 256
7.2.4 ANOVA and Extra Sums of Squares 257
7.2.5 Polynomial Regression and Other Models 261
7.3 Building and Evaluating the Regression Model 263
7.3.1 Building the Model 263
7.3.2 Evaluating the Model 265
7.3.3 Case Study 267
7.4 Regression Through the Origin 273
7.5 Ridge Regression 274
7.6 Logit and Probit Models 276
Exercises 281
xii Contents
8 Data Structure Analysis 283
8.1 Principal Components 283
8.2 Dimensional Reduction 289
8.3 Principal Components of Correlation Matrices 292
8.4 Factor Analysis 299
Exercises 302
9 Survival Analysis 305
9.1 Survivor Function and Hazard Function 305
9.2 Non Parametric Analysis of Survival Data 306
9.2.1 The Life Table Analysis 306
9.2.2 The Kaplan Meier Analysis 311
9.2.3 Statistics for Non Parametric Analysis 313
9.3 Comparing Two Groups of Survival Data 315
9.4 Models for Survival Data 318
9.4.1 The Exponential Model 318
9.4.2 The Weibull Model 320
9.4.3 The Cox Regression Model 322
Exercises 324
10 Directional Data 327
10.1 Representing Directional Data 327
10.2 Descriptive Statistics 331
10.3 The von Mises Distributions 334
10.4 Assessing the Distribution of Directional Data 338
10.4.1 Graphical Assessment of Uniformity 338
10.4.2 The Rayleigh Test of Uniformity 340
10.4.3 The Watson Goodness of Fit Test 342
10.4.4 Assessing the von Misesness of Spherical Distributions 344
10.5 Tests on von Mises Distributions 346
10.5.1 One Sample Mean Test 346
10.5.2 Mean Test for Two Independent Samples 346
10.6 Non Parametric Tests 347
10.6.1 The Uniform Scores Test for Circular Data 347
10.6.2 The Watson Test for Spherical Data 348
10.6.3 Testing Two Paired Samples 350
Exercises 350
Appendix A Short Survey on Probability Theory 353
Contents xiii
A.1 Basic Notions 353
A.1.1 Events and Frequencies 353
A.1.2 Probability Axioms 354
A.2 Conditional Probability and Independence 356
A.2.1 Conditional Probability and Intersection Rule 356
A.2.2 Independent Events 356
A.3 Compound Experiments 358
A.4 Bayes1 Theorem 359
A.5 Random Variables and Distributions 360
A.5.1 Definition of Random Variable 360
A.5.2 Distribution and Density Functions 361
A.5.3 Transformation of a Random Variable 363
A.6 Expectation, Variance and Moments 364
A.6.1 Definitions and Properties 364
A.6.2 Moment Generating Function 367
A.6.3 Chebyshev Theorem 368
A.7 The Binomial and Normal Distributions 368
A.7.1 The Binomial Distribution 368
A.7.2 The Laws of Large Numbers 369
A.7.3 The Normal Distribution 370
A.8 Multivariate Distributions 372
A.8.1 Definitions 372
A.8.2 Moments 374
A.8.3 Conditional Densities and Independence 375
A.8.4 Sums of Random Variables 377
A.8.5 Central Limit Theorem 378
Appendix B Distributions 381
B.1 Discrete Distributions 381
B.1.1 Bernoulli Distribution 381
B.1.2 Uniform Distribution 382
B.1.3 Geometric Distribution 383
B.1.4 Hypergeometric Distribution 384
B.1.5 Binomial Distribution 385
B.1.6 Multinomial Distribution 386
B.1.7 Poisson Distribution 388
B.2 Continuous Distributions 389
B.2.1 Uniform Distribution 389
B.2.2 Normal Distribution 391
B.2.3 Exponential Distribution 392
B.2.4 Weibull Distribution 394
B.2.5 Gamma Distribution 395
B.2.6 Beta Distribution 396
B.2.7 Chi Square Distribution 398
xiv Contents
B.2.8 Student's t Distribution 399
B.2.9 F Distribution 401
B.2.10 Von Mises Distributions 402
Appendix C Point Estimation 405
C.1 Definitions 405
C.2 Estimation of Mean and Variance 406
Appendix D Tables 409
D.1 Binomial Distribution 409
D.2 Normal Distribution 415
D.3 Student's t Distribution 416
D.4 Chi Square Distribution 417
D.5 Critical Values for the F Distribution 418
Appendix E Datasets 419
E.1 Breast Tissue 419
E.2 Car Sale 419
E.3 Cells 420
E.4 Clays 420
E.5 Cork Stoppers 421
E.6 CTG 422
E.7 Culture 423
E.8 Fatigue 423
E.9 FHR 424
E.10 FHR Apgar 424
E.11 Firms 425
E.12 Flow Rate 425
E.13 Foetal Weight 425
E.14 Forest Fires 426
E.15 Freshmen 426
E.16 Heart Valve 427
E.17 Infarct 428
E.18 Joints 428
E.19 Metal Firms 429
E.20 Meteo 429
E.21 Moulds 429
E.22 Neonatal 430
E.23 Programming 430
E.24 Rocks 431
Contents xv
E.25 Signal Noise 431
E.26 Soil Pollution 432
E.27 Stars 432
E.28 Stock Exchange 433
E.29 VCG 434
E.30 Wave 434
E.31 Weather 434
E.32 Wines 435
Appendix F Tools 437
F.1 MATLAB Functions 437
F.2 Tools EXCEL File 438
F.3 SCSIZE Program 438
References 439
Index 447 |
| any_adam_object | 1 |
| author | Sá, Joaquim P. Marques de 1946- |
| author_GND | (DE-588)123013747 |
| author_facet | Sá, Joaquim P. Marques de 1946- |
| author_role | aut |
| author_sort | Sá, Joaquim P. Marques de 1946- |
| author_variant | j p m d s jpmd jpmds |
| building | Verbundindex |
| bvnumber | BV017258874 |
| callnumber-first | Q - Science |
| callnumber-label | QA276 |
| callnumber-raw | QA276.4 |
| callnumber-search | QA276.4 |
| callnumber-sort | QA 3276.4 |
| callnumber-subject | QA - Mathematics |
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| ctrlnum | (OCoLC)883578508 (DE-599)BVBBV017258874 |
| dewey-full | 519.5/0285 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/0285 |
| dewey-search | 519.5/0285 |
| dewey-sort | 3519.5 3285 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Psychologie Mathematik Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV017258874 |
| illustrated | Illustrated |
| indexdate | 2024-07-20T07:52:09Z |
| institution | BVB |
| isbn | 3540011560 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-010402815 |
| oclc_num | 883578508 |
| open_access_boolean | |
| owner | DE-898 DE-BY-UBR DE-91G DE-BY-TUM DE-11 DE-188 DE-578 |
| owner_facet | DE-898 DE-BY-UBR DE-91G DE-BY-TUM DE-11 DE-188 DE-578 |
| physical | XXII, 452 S. Ill., graph. Darst. 1 CD-Rom (12 cm) |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Springer |
| record_format | marc |
| spelling | Sá, Joaquim P. Marques de 1946- Verfasser (DE-588)123013747 aut Applied statistics using SPSS, STATISTICA and MATLAB J. P. Marques de Sá Berlin u.a. Springer 2003 XXII, 452 S. Ill., graph. Darst. 1 CD-Rom (12 cm) txt rdacontent n rdamedia nc rdacarrier "Aimed at students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using SPSS, MATLAB and STATISTICA, this text provides a comprehensive coverage of the main statistical analysis topics important for practical applications such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. The relevant notions and methods are explained concisely, illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues. The solutions presented in the examples are obtained with one of the software packages in a pedagogical way. It provides guidance on how to use SPSS, MATLAB and STATISTICA in statistical analysis applications without having to delve in the manuals."--BOOK JACKET. MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistique mathématique - Informatique Datenverarbeitung Mathematical statistics Data processing SPSS (DE-588)4056588-9 gnd rswk-swf MATLAB (DE-588)4329066-8 gnd rswk-swf STATISTICA (DE-588)4429730-0 gnd rswk-swf Anwendung (DE-588)4196864-5 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Statistik (DE-588)4056995-0 s Anwendung (DE-588)4196864-5 s SPSS (DE-588)4056588-9 s DE-604 STATISTICA (DE-588)4429730-0 s MATLAB (DE-588)4329066-8 s HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010402815&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Sá, Joaquim P. Marques de 1946- Applied statistics using SPSS, STATISTICA and MATLAB MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistique mathématique - Informatique Datenverarbeitung Mathematical statistics Data processing SPSS (DE-588)4056588-9 gnd MATLAB (DE-588)4329066-8 gnd STATISTICA (DE-588)4429730-0 gnd Anwendung (DE-588)4196864-5 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4056588-9 (DE-588)4329066-8 (DE-588)4429730-0 (DE-588)4196864-5 (DE-588)4056995-0 |
| title | Applied statistics using SPSS, STATISTICA and MATLAB |
| title_auth | Applied statistics using SPSS, STATISTICA and MATLAB |
| title_exact_search | Applied statistics using SPSS, STATISTICA and MATLAB |
| title_full | Applied statistics using SPSS, STATISTICA and MATLAB J. P. Marques de Sá |
| title_fullStr | Applied statistics using SPSS, STATISTICA and MATLAB J. P. Marques de Sá |
| title_full_unstemmed | Applied statistics using SPSS, STATISTICA and MATLAB J. P. Marques de Sá |
| title_short | Applied statistics using SPSS, STATISTICA and MATLAB |
| title_sort | applied statistics using spss statistica and matlab |
| topic | MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistique mathématique - Informatique Datenverarbeitung Mathematical statistics Data processing SPSS (DE-588)4056588-9 gnd MATLAB (DE-588)4329066-8 gnd STATISTICA (DE-588)4429730-0 gnd Anwendung (DE-588)4196864-5 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistique mathématique - Informatique Datenverarbeitung Mathematical statistics Data processing SPSS STATISTICA Anwendung Statistik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010402815&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT sajoaquimpmarquesde appliedstatisticsusingspssstatisticaandmatlab |