Holdings: Applied statistics using SPSS, STATISTICA, MATLAB and R

Applied statistics using SPSS, STATISTICA, MATLAB and R:

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Bibliographic Details
Main Author:	Sá, Joaquim P. Marques de 1946- (Author)
Format:	Book
Language:	English
Published:	Berlin [u.a.] Springer 2007
Edition:	2. ed.
Subjects:	MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistik - Anwendung - MATLAB Statistik - Anwendung - R <Programm> Statistik - Anwendung - SPSS Statistik - Anwendung - STATISTICA Datenverarbeitung Mathematical statistics > Data processing Anwendung STATISTICA SPSS Statistik R > Programm
Online Access:	Inhaltsverzeichnis
Physical Description:	XXIV, 505 S. graph. Darst. 235 mm x 155 mm CD-ROM (12 cm)
ISBN:	9783540719717 3540719717

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adam_text	JOAQUIM P. MARQUES DE SA APPLIED STATISTICS USING SPSS, STATISTICA, MATLAB AND R WITH 195 FIGURES AND A CD 4Y SPRINGER CONTENTS PREFACE TO THE SECOND EDITION XV PREFACE TO THE FIRST EDITION XVII SYMBOLS AND ABBREVIATIONS XIX 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 STATISTICAL SIGNIFICANCE AND OTHER SIGNIFICANCES 17 1.7 DATASETS 19 1.8 SOFTWARE TOOLS 19 1.8.1 SPSS AND STATISTICA 20 1.8.2 MATLAB AND R 22 2 PRESENTING AND SUMMARISING THE DATA 29 2.1 PRELIMINARIES 29 2.1.1 READING IN THE DATA 29 2.1.2 OPERATING WITH THE DATA ?.. 34 2.2 PRESENTING THE DATA 39 2.2.1 COUNTS AND BAR GRAPHS 40 2.2.2 FREQUENCIES AND HISTOGRAMS 47 2.2.3 MULTIVARIATE TABLES, SCATTER PLOTS AND 3D PLOTS 52 2.2.4 CATEGORISED PLOTS 56 2.3 SUMMARISING THE DATA 58 2.3.1 ME.ASURES OF LOCATION 58 2.3.2 MEASURES OF SPREAD 62 2.3.3 MEASURES OF SHAPE 64 VIII CONTENTS 2.3.4 MEASURES OF ASSOCIATION FOR CONTINUOUS VARIABLES 66 2.3.5 MEASURES OF ASSOCIATION FOR ORDINAL VARIABLES 69 2.3.6 MEASURES OF ASSOCIATION FOR NOMINAL VARIABLES 73 EXERCISES 77 3 ESTIMATING DATA PARAMETERS ^ 81 3.1 POINT ESTIMATION AND INTERVAL ESTIMATION 81 3.2 ESTIMATING A MEAN 85 3.3 ESTIMATING A PROPORTION 92 3.4 ESTIMATING A VARIANCE 95 3.5 ESTIMATING A VARIANCE RATIO 97 3.6 BOOTSTRAP ESTIMATION 99 EXERCISES 107 4 PARAMETRIC TESTS OF HYPOTHESES 111 4.1 HYPOTHESIS TEST PROCEDURE ILL 4.2 TEST ERRORS AND TEST POWER 115 4.3 INFERENCE ON ONE POPULATION 121 4.3.1 TESTING A MEAN 121 4.3.2 TESTING A VARIANCE 125 4.4 INFERENCE ON TWO POPULATIONS 126 4.4.1 TESTING A CORRELATION 126 4.4.2 COMPARING TWO VARIANCES 129 4.4.3 COMPARING TWO MEANS 132 4.5 INFERENCE ON MORE THAN TWO POPULATIONS 141 4.5.1 INTRODUCTION TO THE ANALYSIS OF VARIANCE 141 4.5.2 ONE-WAY ANOVA 143 4.5.3 TWO-WAY ANOVA 156 EXERCISES 166 5 NON-PARAMETRIC TESTS OF HYPOTHESES 171 5.1 INFERENCE ON ONE POPULATION .?. 172 5.1.1 THE RUNS TEST 172 5.1.2 THE BINOMIAL TEST 174 5.1.3 THE CHI-SQUARE GOODNESS OF FIT TEST 179 5.1.4 THE KOLMOGOROV-SMIRNOV GOODNESS OF FIT TEST 183 5.1.5 THE LILLIEFORS TEST FOR NORMALITY 187 5.1.6 THE SHAPIRO-WILK TEST FOR NORMALITY 187 5.2 CONTINGENCY TABLES 189 5.2.1 THE 2X2 CONTINGENCY TABLE 189 5.2.2 THE RXC CONTINGENCY TABLE 193 CONTENTS 5.2.3 THE CHI-SQUARE TEST OF INDEPENDENCE 195 5.2.4 MEASURES OF ASSOCIATION REVISITED 197 5.3 INFERENCE ON TWO POPULATIONS 200 5.3.1 TESTS FOR TWO INDEPENDENT SAMPLES , 201 5.3.2 TESTS FOR TWO PAIRED SAMPLES 205 5.4 INFERENCE ON MORE THAN TWO POPULATIONS 212 5.4.1 THE KRUSKAL-WALLIS TEST FOR INDEPENDENT SAMPLES 212 5.4.2 THE FRIEDMANN TEST FOR PAIRED SAMPLES 215 5.4.3 THE COCHRAN Q TEST . . 217 EXERCISES 218 6 STATISTICAL CLASSIFICATION 223 6.1 DECISION REGIONS AND FUNCTIONS 223 6.2 LINEAR DISCRIMINANTS 225 6.2.1 MINIMUM EUCLIDIAN DISTANCE DISCRIMINANT 225 6.2.2 MINIMUM MAHALANOBIS DISTANCE DISCRIMINANT 228 6.3 BAYESIAN CLASSIFICATION 234 6.3.1 BAYES RULE FOR MINIMUM RISK 234 6.3.2 NORMAL BAYESIAN CLASSIFICATION 240 6.3.3 DIMENSIONALITY RATIO AND ERROR ESTIMATION 243 6.4 THE ROC CURVE 246 6.5 FEATURE SELECTION 253 6.6 CLASSIFIER EVALUATION 256 6.7 TREE CLASSIFIERS 259 EXERCISES 268 7 DATA REGRESSION . 271 7.1 SIMPLE LINEAR REGRESSION 272 7.1.1 SIMPLE LINEAR REGRESSION MODEL 272 7.1.2 ESTIMATING THE REGRESSION FUNCTION 273 7.1.3 INFERENCES IN REGRESSION ANALYSIS 279 7.1.4 ANOVA TESTS 285 7.2 MULTIPLE REGRESSION 289 7.2.1 GENERAL LINEAR REGRESSION MODEL 289 7.2.2 GENERAL LINEAR REGRESSION IN MATRIX FERMS 289 7.2.3 MULTIPLE CORRELATION 292 7.2.4 INFERENCES ON REGRESSION PARAMETERS 294 7.2.5 ANOVA AND EXTRA SUMS OF SQUARES 296 7.2.6 POLYNOMIAL REGRESSION AND OTHER MODELS 300 7.3 BUILDING AND EVALUATING THE REGRESSION MODEL 303 7.3.1 BUILDING THE MODEL 303 7.3.2 EVALUATING THE MODEL 306 7.3.3 CA SE STUDY ..308 7.4 REGRESSION THROUGH THE ORIGIN 314 CONTENTS 7.5 RIDGE REGRESSION 316 7.6 LOGIT AND PROBIT MODELS 322 EXERCISES 327 8 DATA STRUCTURE ANALYSIS 329 8.1 PRINCIPAL COMPONENTS 329 8.2 DIMENSIONAL REDUCTION 337 8.3 PRINCIPAL COMPONENTS OF CORRELATION MATRICES 339 8.4 FACTOR ANALYSIS 347 EXERCISES 350 9 SURVIVAL ANALYSIS 353 9.1 SURVIVOR FUNCTION AND HAZARD FUNCTION 353 9.2 NON-PARAMETRIC ANALYSIS OF SURVIVAL DATA 354 9.2.1 THE LIFE TABLE ANALYSIS 354 9.2.2 THE KAPLAN-MEIER ANALYSIS 359 9.2.3 STATISTICS FOR NON-PARAMETRIC ANALYSIS 362 9.3 COMPARING TWO GROUPS OF SURVIVAL DATA 364 9.4 MODELS FOR SURVIVAL DATA 367 9.4.1 THE EXPONENTIAL MODEL 367 9.4.2 THE WEIBULL MODEL 369 9.4.3 THE COX REGRESSION MODEL 371 EXERCISES 373 10 DIRECTIONAL DATA 375 10.1 REPRESENTING DIRECTIONAL DATA 375 10.2 DESCRIPTIVE STATISTICS 380 10.3 THE VON MISES DISTRIBUTIONS 383 10.4 ASSESSING THE DISTRIBUTION OF DIRECTIONAL DATA 387 10.4.1 GRAPHICAL ASSESSMENT OF UNIFORMITY 387 10.4.2 THE RAYLEIGH TEST OF UNIFORMITY 389 10.4.3 THE WATSON GOODNESS OF FIT TEST !T. 392 10.4.4 ASSESSING THE VON MISESNESS OF SPHERICAL DISTRIBUTIONS 393 10.5 TESTS ON VON MISES DISTRIBUTIONS 395 10.5.1 ONE-SAMPLE MEAN TEST 395 10.5.2 MEAN TEST FOR TWO INDEPENDENT SAMPLES 396 10.6 NON-PARAMETRIC TESTS 397 10.6.1 THE UNIFORM SCORES TEST FOR CIRCULAR DATA 397 10.6.2 THE WATSON TEST FOR SPHERICAL DATA 398 10.6.3 TESTING TWO PAIRED SAMPLES 399 EXERCISES 400 CONTENTS APPENDIX A - SHORT SURVEY ON PROBABILITY THEORY 403 A.I BASIC NOTIONS 403 A.1.1 EVENTS AND FREQUENCIES 403 A.1.2 PROBABILITY AXIOMS 404 A.2 CONDITIONAL PROBABILITY AND INDEPENDENCE 406 A.2.1 CONDITIONAL PROBABILITY AND INTERSECTION RULE 406 A.2.2 INDEPENDENT EVENTS .-:: 406 A.3 COMPOUND EXPERIMENTS 408 A.4 BAYES THEOREM 409 A.5 RANDOM VARIABLES AND DISTRIBUTIONS 410 A.5.1 DEFINITION OF RANDOM VARIABLE 410 A.5.2 DISTRIBUTION AND DENSITY FUNCTIONS 411 A.5.3 TRANSFORMATION OF A RANDOM VARIABLE 413 A.6 EXPECTATION, VARIANCE AND MOMENTS 414 A.6.1 DEFINITIONS AND PROPERTIES 414 A.6.2 MOMENT-GENERATING FUNCTION 417 A.6.3 CHEBYSHEV THEOREM 418 A.7 THE BINOMIAL AND NORMAL DISTRIBUTIONS 418 A.7.1 THE BINOMIAL DISTRIBUTION 418 A.7.2 THE LAWS OF LARGE NUMBERS 419 A.7.3 THE NORMAL DISTRIBUTION 420 A.8 MULTIVARIATE DISTRIBUTIONS 422 A.8.1 DEFINITIONS 422 A.8.2 MOMENTS 425 A.8.3 CONDITIONAL DENSITIES AND INDEPENDENCE 425 A.8.4 SUMS OF RANDOM VARIABLES 427 A.8.5 CENTRAL LIMIT THEOREM 428 APPENDIX B - DISTRIBUTIONS 431 B.I DISCRETE DISTRIBUTIONS 431 B.I.I BERNOULLI DISTRIBUTION 431 B.1.2 UNIFORM DISTRIBUTION 432 B.1.3 GEOMETRIC DISTRIBUTION 433 B.1.4 HYPERGEOMETRIC DISTRIBUTION 434 B.1.5 BINOMIAL DISTRIBUTION 435 B.I.6 MULTINOMIAL DISTRIBUTION 436 B.I.7 POISSON DISTRIBUTION 438 B.2 CONTINUOUS DISTRIBUTIONS 439 B.2.1 UNIFORM DISTRIBUTION 439 B.2.2 NORMAL DISTRIBUTION 441 B.2.3 EXPONENTIAL DISTRIBUTION 442 B.2.4 WEIBULL DISTRIBUTION 444 B.2.5 /GAMMA DISTRIBUTION 445 B.2.6 BETA DISTRIBUTION 446 B.2.7 CHI-SQUARE DISTRIBUTION 448 CONTENTS B.2.8 STUDENT S T DISTRIBUTION 449 B.2.9 F DISTRIBUTION 451 B.2.10 VON MISES DISTRIBUTIONS 452 APPENDIX C - POINT ESTIMATION 455 C.I DEFINITIONS 455 C.2 ESTIMATION OF MEAN AND VARIANCE 457 APPENDIX D - TABLES 459 D.I BINOMIAL DISTRIBUTION 459 D.2 NORMAL DISTRIBUTION 465 D.3 STUDENT S T DISTRIBUTION 466 D.4 CHI-SQUARE DISTRIBUTION 467 D.5 CRITICAL VALUES FOR THE F DISTRIBUTION 468 APPENDIX E - DATASETS 469 E.I BREAST TISSUE 469 E.2 CAR SALE . 469 E.3 CELLS 470 E.4 CLAYS : 470 E.5 CORK STOPPERS 471 E.6 CTG 472 E.7 CULTURE . 473 E.8 FATIGUE 473 E.9 FHR 474 E.10 FHR-APGAR 474 E.LL FIRMS 475 E.12 HOW RATE 475 E.13 FOETAL WEIGHT 475 E.14 FOREST FIRES 476 E.15 FRESHMEN 476 E.16 HEART VALVE .?. 477 E.17 INFARCT 478 E.18 JOINTS :. 478 E.19 METAL FIRMS 479 E.20 METEO 479 E.21 MOULDS 479 E.22 NEONATAL 480 E.23 PROGRAMMING.,-. 480 E.24 ROCKS 481 E.25 SIGNAL & NOISE 481 CONTENTS XIII E.26 SOIL POLLUTION 482 E.27 STARS 482 E.28 STOCK EXCHANGE 483 E.29 VCG 484 E.30 WAVE 484 E.31 WEATHER 484 E.32 WINES 485 APPENDIX F - TOOLS 487 F.I MATLAB FUNCTIONS 487 F.2 R FUNCTIONS 488 F.3 TOOLS EXCEL FILE 489 F.4 SCSIZE PROGRAM 489 REFERENCES 491 INDEX 499
adam_txt	JOAQUIM P. MARQUES DE SA APPLIED STATISTICS USING SPSS, STATISTICA, MATLAB AND R WITH 195 FIGURES AND A CD 4Y SPRINGER CONTENTS PREFACE TO THE SECOND EDITION XV PREFACE TO THE FIRST EDITION XVII SYMBOLS AND ABBREVIATIONS XIX 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 STATISTICAL SIGNIFICANCE AND OTHER SIGNIFICANCES 17 1.7 DATASETS 19 1.8 SOFTWARE TOOLS 19 1.8.1 SPSS AND STATISTICA 20 1.8.2 MATLAB AND R 22 2 PRESENTING AND SUMMARISING THE DATA 29 2.1 PRELIMINARIES 29 2.1.1 READING IN THE DATA 29 2.1.2 OPERATING WITH THE DATA ?. 34 2.2 PRESENTING THE DATA 39 2.2.1 COUNTS AND BAR GRAPHS 40 2.2.2 FREQUENCIES AND HISTOGRAMS 47 2.2.3 MULTIVARIATE TABLES, SCATTER PLOTS AND 3D PLOTS 52 2.2.4 CATEGORISED PLOTS 56 2.3 SUMMARISING THE DATA 58 2.3.1 ME.ASURES OF LOCATION 58 2.3.2 MEASURES OF SPREAD 62 2.3.3 MEASURES OF SHAPE 64 VIII CONTENTS 2.3.4 MEASURES OF ASSOCIATION FOR CONTINUOUS VARIABLES 66 2.3.5 MEASURES OF ASSOCIATION FOR ORDINAL VARIABLES 69 2.3.6 MEASURES OF ASSOCIATION FOR NOMINAL VARIABLES 73 EXERCISES 77 3 ESTIMATING DATA PARAMETERS ^ 81 3.1 POINT ESTIMATION AND INTERVAL ESTIMATION 81 3.2 ESTIMATING A MEAN 85 3.3 ESTIMATING A PROPORTION 92 3.4 ESTIMATING A VARIANCE 95 3.5 ESTIMATING A VARIANCE RATIO 97 3.6 BOOTSTRAP ESTIMATION 99 EXERCISES 107 4 PARAMETRIC TESTS OF HYPOTHESES 111 4.1 HYPOTHESIS TEST PROCEDURE ILL 4.2 TEST ERRORS AND TEST POWER 115 4.3 INFERENCE ON ONE POPULATION 121 4.3.1 TESTING A MEAN 121 4.3.2 TESTING A VARIANCE 125 4.4 INFERENCE ON TWO POPULATIONS 126 4.4.1 TESTING A CORRELATION 126 4.4.2 COMPARING TWO VARIANCES 129 4.4.3 COMPARING TWO MEANS 132 4.5 INFERENCE ON MORE THAN TWO POPULATIONS 141 4.5.1 INTRODUCTION TO THE ANALYSIS OF VARIANCE 141 4.5.2 ONE-WAY ANOVA 143 4.5.3 TWO-WAY ANOVA 156 EXERCISES 166 5 NON-PARAMETRIC TESTS OF HYPOTHESES 171 5.1 INFERENCE ON ONE POPULATION .?. 172 5.1.1 THE RUNS TEST 172 5.1.2 THE BINOMIAL TEST 174 5.1.3 THE CHI-SQUARE GOODNESS OF FIT TEST 179 5.1.4 THE KOLMOGOROV-SMIRNOV GOODNESS OF FIT TEST 183 5.1.5 THE LILLIEFORS TEST FOR NORMALITY 187 5.1.6 THE SHAPIRO-WILK TEST FOR NORMALITY 187 5.2 CONTINGENCY TABLES 189 5.2.1 THE 2X2 CONTINGENCY TABLE 189 5.2.2 THE RXC CONTINGENCY TABLE 193 CONTENTS 5.2.3 THE CHI-SQUARE TEST OF INDEPENDENCE 195 5.2.4 MEASURES OF ASSOCIATION REVISITED 197 5.3 INFERENCE ON TWO POPULATIONS 200 5.3.1 TESTS FOR TWO INDEPENDENT SAMPLES , 201 5.3.2 TESTS FOR TWO PAIRED SAMPLES 205 5.4 INFERENCE ON MORE THAN TWO POPULATIONS 212 5.4.1 THE KRUSKAL-WALLIS TEST FOR INDEPENDENT SAMPLES 212 5.4.2 THE FRIEDMANN TEST FOR PAIRED SAMPLES 215 5.4.3 THE COCHRAN Q TEST .'. 217 EXERCISES 218 6 STATISTICAL CLASSIFICATION 223 6.1 DECISION REGIONS AND FUNCTIONS 223 6.2 LINEAR DISCRIMINANTS 225 6.2.1 MINIMUM EUCLIDIAN DISTANCE DISCRIMINANT 225 6.2.2 MINIMUM MAHALANOBIS DISTANCE DISCRIMINANT 228 6.3 BAYESIAN CLASSIFICATION 234 6.3.1 BAYES RULE FOR MINIMUM RISK 234 6.3.2 NORMAL BAYESIAN CLASSIFICATION 240 6.3.3 DIMENSIONALITY RATIO AND ERROR ESTIMATION 243 6.4 THE ROC CURVE 246 6.5 FEATURE SELECTION 253 6.6 CLASSIFIER EVALUATION 256 6.7 TREE CLASSIFIERS 259 EXERCISES 268 7 DATA REGRESSION . 271 7.1 SIMPLE LINEAR REGRESSION 272 7.1.1 SIMPLE LINEAR REGRESSION MODEL 272 7.1.2 ESTIMATING THE REGRESSION FUNCTION 273 7.1.3 INFERENCES IN REGRESSION ANALYSIS 279 7.1.4 ANOVA TESTS 285 7.2 MULTIPLE REGRESSION 289 7.2.1 GENERAL LINEAR REGRESSION MODEL 289 7.2.2 GENERAL LINEAR REGRESSION IN MATRIX FERMS 289 7.2.3 MULTIPLE CORRELATION 292 7.2.4 INFERENCES ON REGRESSION PARAMETERS 294 7.2.5 ANOVA AND EXTRA SUMS OF SQUARES 296 7.2.6 POLYNOMIAL REGRESSION AND OTHER MODELS 300 7.3 BUILDING AND EVALUATING THE REGRESSION MODEL 303 7.3.1 BUILDING THE MODEL 303 7.3.2 EVALUATING THE MODEL 306 7.3.3 CA'SE STUDY .308 7.4 REGRESSION THROUGH THE ORIGIN 314 CONTENTS 7.5 RIDGE REGRESSION 316 7.6 LOGIT AND PROBIT MODELS 322 EXERCISES 327 8 DATA STRUCTURE ANALYSIS 329 8.1 PRINCIPAL COMPONENTS 329 8.2 DIMENSIONAL REDUCTION 337 8.3 PRINCIPAL COMPONENTS OF CORRELATION MATRICES 339 8.4 FACTOR ANALYSIS 347 EXERCISES 350 9 SURVIVAL ANALYSIS 353 9.1 SURVIVOR FUNCTION AND HAZARD FUNCTION 353 9.2 NON-PARAMETRIC ANALYSIS OF SURVIVAL DATA 354 9.2.1 THE LIFE TABLE ANALYSIS 354 9.2.2 THE KAPLAN-MEIER ANALYSIS 359 9.2.3 STATISTICS FOR NON-PARAMETRIC ANALYSIS 362 9.3 COMPARING TWO GROUPS OF SURVIVAL DATA 364 9.4 MODELS FOR SURVIVAL DATA 367 9.4.1 THE EXPONENTIAL MODEL 367 9.4.2 THE WEIBULL MODEL 369 9.4.3 THE COX REGRESSION MODEL 371 EXERCISES 373 10 DIRECTIONAL DATA 375 10.1 REPRESENTING DIRECTIONAL DATA 375 10.2 DESCRIPTIVE STATISTICS 380 10.3 THE VON MISES DISTRIBUTIONS 383 10.4 ASSESSING THE DISTRIBUTION OF DIRECTIONAL DATA 387 10.4.1 GRAPHICAL ASSESSMENT OF UNIFORMITY 387 10.4.2 THE RAYLEIGH TEST OF UNIFORMITY 389 10.4.3 THE WATSON GOODNESS OF FIT TEST !T. 392 10.4.4 ASSESSING THE VON MISESNESS OF SPHERICAL DISTRIBUTIONS 393 10.5 TESTS ON VON MISES DISTRIBUTIONS 395 10.5.1 ONE-SAMPLE MEAN TEST 395 10.5.2 MEAN TEST FOR TWO INDEPENDENT SAMPLES 396 10.6 NON-PARAMETRIC TESTS 397 10.6.1 THE UNIFORM SCORES TEST FOR CIRCULAR DATA 397 10.6.2 THE WATSON TEST FOR SPHERICAL DATA 398 10.6.3 TESTING TWO PAIRED SAMPLES 399 EXERCISES 400 CONTENTS APPENDIX A - SHORT SURVEY ON PROBABILITY THEORY 403 A.I BASIC NOTIONS 403 A.1.1 EVENTS AND FREQUENCIES 403 A.1.2 PROBABILITY AXIOMS 404 A.2 CONDITIONAL PROBABILITY AND INDEPENDENCE 406 A.2.1 CONDITIONAL PROBABILITY AND INTERSECTION RULE 406 A.2.2 INDEPENDENT EVENTS .-:: 406 A.3 COMPOUND EXPERIMENTS 408 A.4 BAYES' THEOREM 409 A.5 RANDOM VARIABLES AND DISTRIBUTIONS 410 A.5.1 DEFINITION OF RANDOM VARIABLE 410 A.5.2 DISTRIBUTION AND DENSITY FUNCTIONS 411 A.5.3 TRANSFORMATION OF A RANDOM VARIABLE 413 A.6 EXPECTATION, VARIANCE AND MOMENTS 414 A.6.1 DEFINITIONS AND PROPERTIES 414 A.6.2 MOMENT-GENERATING FUNCTION 417 A.6.3 CHEBYSHEV THEOREM 418 A.7 THE BINOMIAL AND NORMAL DISTRIBUTIONS 418 A.7.1 THE BINOMIAL DISTRIBUTION 418 A.7.2 THE LAWS OF LARGE NUMBERS 419 A.7.3 THE NORMAL DISTRIBUTION 420 A.8 MULTIVARIATE DISTRIBUTIONS 422 A.8.1 DEFINITIONS 422 A.8.2 MOMENTS 425 A.8.3 CONDITIONAL DENSITIES AND INDEPENDENCE 425 A.8.4 SUMS OF RANDOM VARIABLES 427 A.8.5 CENTRAL LIMIT THEOREM 428 APPENDIX B - DISTRIBUTIONS 431 B.I DISCRETE DISTRIBUTIONS 431 B.I.I BERNOULLI DISTRIBUTION 431 B.1.2 UNIFORM DISTRIBUTION 432 B.1.3 GEOMETRIC DISTRIBUTION 433 B.1.4 HYPERGEOMETRIC DISTRIBUTION 434 B.1.5 BINOMIAL DISTRIBUTION 435 B.I.6 MULTINOMIAL DISTRIBUTION 436 B.I.7 POISSON DISTRIBUTION 438 B.2 CONTINUOUS DISTRIBUTIONS 439 B.2.1 UNIFORM DISTRIBUTION 439 B.2.2 NORMAL DISTRIBUTION 441 B.2.3 EXPONENTIAL DISTRIBUTION 442 B.2.4 WEIBULL DISTRIBUTION 444 B.2.5 /GAMMA DISTRIBUTION 445 B.2.6 BETA DISTRIBUTION 446 B.2.7 CHI-SQUARE DISTRIBUTION 448 CONTENTS B.2.8 STUDENT'S T DISTRIBUTION 449 B.2.9 F DISTRIBUTION 451 B.2.10 VON MISES DISTRIBUTIONS 452 APPENDIX C - POINT ESTIMATION 455 C.I DEFINITIONS 455 C.2 ESTIMATION OF MEAN AND VARIANCE 457 APPENDIX D - TABLES 459 D.I BINOMIAL DISTRIBUTION 459 D.2 NORMAL DISTRIBUTION 465 D.3 STUDENT'S T DISTRIBUTION 466 D.4 CHI-SQUARE DISTRIBUTION 467 D.5 CRITICAL VALUES FOR THE F DISTRIBUTION 468 APPENDIX E - DATASETS 469 E.I BREAST TISSUE 469 E.2 CAR SALE . 469 E.3 CELLS 470 E.4 CLAYS : 470 E.5 CORK STOPPERS 471 E.6 CTG 472 E.7 CULTURE . 473 E.8 FATIGUE 473 E.9 FHR 474 E.10 FHR-APGAR 474 E.LL FIRMS 475 E.12 HOW RATE 475 E.13 FOETAL WEIGHT 475 E.14 FOREST FIRES 476 E.15 FRESHMEN 476 E.16 HEART VALVE .?. 477 E.17 INFARCT 478 E.18 JOINTS :. 478 E.19 METAL FIRMS 479 E.20 METEO 479 E.21 MOULDS 479 E.22 NEONATAL 480 E.23 PROGRAMMING.,-. 480 E.24 ROCKS 481 E.25 SIGNAL & NOISE 481 CONTENTS XIII E.26 SOIL POLLUTION 482 E.27 STARS 482 E.28 STOCK EXCHANGE 483 E.29 VCG 484 E.30 WAVE 484 E.31 WEATHER 484 E.32 WINES 485 APPENDIX F - TOOLS 487 F.I MATLAB FUNCTIONS 487 F.2 R FUNCTIONS 488 F.3 TOOLS EXCEL FILE 489 F.4 SCSIZE PROGRAM 489 REFERENCES 491 INDEX 499
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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	BV022450032
callnumber-first	Q - Science
callnumber-label	QA276
callnumber-raw	QA276.4
callnumber-search	QA276.4
callnumber-sort	QA 3276.4
callnumber-subject	QA - Mathematics
classification_rvk	ST 600 ST 601 ST 610
classification_tum	DAT 600f DAT 307f DAT 306f
ctrlnum	(OCoLC)255966409 (DE-599)DNB983624720
dewey-full	519.5
dewey-hundreds	500 - Natural sciences and mathematics
dewey-ones	519 - Probabilities and applied mathematics
dewey-raw	519.5
dewey-search	519.5
dewey-sort	3519.5
dewey-tens	510 - Mathematics
discipline	Allgemeines Informatik Mathematik
discipline_str_mv	Allgemeines Informatik Mathematik
edition	2. ed.
format	Book
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id	DE-604.BV022450032
illustrated	Illustrated
index_date	2024-07-02T17:36:02Z
indexdate	2024-07-09T20:57:51Z
institution	BVB
isbn	9783540719717 3540719717
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-015657919
oclc_num	255966409
open_access_boolean
owner	DE-M49 DE-BY-TUM DE-N2 DE-824 DE-20 DE-945 DE-29T DE-1102 DE-1051 DE-91 DE-BY-TUM DE-83 DE-92 DE-19 DE-BY-UBM
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physical	XXIV, 505 S. graph. Darst. 235 mm x 155 mm CD-ROM (12 cm)
publishDate	2007
publishDateSearch	2007
publishDateSort	2007
publisher	Springer
record_format	marc
spelling	Sá, Joaquim P. Marques de 1946- Verfasser (DE-588)123013747 aut Applied statistics using SPSS, STATISTICA, MATLAB and R Joaquim P. Marques de Sá 2. ed. Berlin [u.a.] Springer 2007 XXIV, 505 S. graph. Darst. 235 mm x 155 mm CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistik - Anwendung - MATLAB Statistik - Anwendung - R <Programm> Statistik - Anwendung - SPSS Statistik - Anwendung - STATISTICA Datenverarbeitung Mathematical statistics Data processing Anwendung (DE-588)4196864-5 gnd rswk-swf MATLAB (DE-588)4329066-8 gnd rswk-swf STATISTICA (DE-588)4429730-0 gnd rswk-swf SPSS (DE-588)4056588-9 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf R Programm (DE-588)4705956-4 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 R Programm (DE-588)4705956-4 s HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015657919&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Sá, Joaquim P. Marques de 1946- Applied statistics using SPSS, STATISTICA, MATLAB and R MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistik - Anwendung - MATLAB Statistik - Anwendung - R <Programm> Statistik - Anwendung - SPSS Statistik - Anwendung - STATISTICA Datenverarbeitung Mathematical statistics Data processing Anwendung (DE-588)4196864-5 gnd MATLAB (DE-588)4329066-8 gnd STATISTICA (DE-588)4429730-0 gnd SPSS (DE-588)4056588-9 gnd Statistik (DE-588)4056995-0 gnd R Programm (DE-588)4705956-4 gnd
subject_GND	(DE-588)4196864-5 (DE-588)4329066-8 (DE-588)4429730-0 (DE-588)4056588-9 (DE-588)4056995-0 (DE-588)4705956-4
title	Applied statistics using SPSS, STATISTICA, MATLAB and R
title_auth	Applied statistics using SPSS, STATISTICA, MATLAB and R
title_exact_search	Applied statistics using SPSS, STATISTICA, MATLAB and R
title_exact_search_txtP	Applied statistics using SPSS, STATISTICA, MATLAB and R
title_full	Applied statistics using SPSS, STATISTICA, MATLAB and R Joaquim P. Marques de Sá
title_fullStr	Applied statistics using SPSS, STATISTICA, MATLAB and R Joaquim P. Marques de Sá
title_full_unstemmed	Applied statistics using SPSS, STATISTICA, MATLAB and R Joaquim P. Marques de Sá
title_short	Applied statistics using SPSS, STATISTICA, MATLAB and R
title_sort	applied statistics using spss statistica matlab and r
topic	MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistik - Anwendung - MATLAB Statistik - Anwendung - R <Programm> Statistik - Anwendung - SPSS Statistik - Anwendung - STATISTICA Datenverarbeitung Mathematical statistics Data processing Anwendung (DE-588)4196864-5 gnd MATLAB (DE-588)4329066-8 gnd STATISTICA (DE-588)4429730-0 gnd SPSS (DE-588)4056588-9 gnd Statistik (DE-588)4056995-0 gnd R Programm (DE-588)4705956-4 gnd
topic_facet	MATLAB SPSS (Computer file) STATISTICA (Computer file) Statistik - Anwendung - MATLAB Statistik - Anwendung - R <Programm> Statistik - Anwendung - SPSS Statistik - Anwendung - STATISTICA Datenverarbeitung Mathematical statistics Data processing Anwendung STATISTICA SPSS Statistik R Programm
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015657919&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT sajoaquimpmarquesde appliedstatisticsusingspssstatisticamatlabandr

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