Design of experiments: statistical principles of research design and analysis
Gespeichert in:
| Vorheriger Titel: | Kuehl, Robert O. Statistical principles of research design and analysis |
|---|---|
| 1. Verfasser: | |
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Pacific Grove [u.a.]
Duxbury
2000
|
| Ausgabe: | 2. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Rev. ed. of: Statistical principles of research design and analysis, c. 1994 |
| Beschreibung: | XVI, 666 S. graph. Darst. |
| ISBN: | 0534368344 9780534368340 |
Internformat
MARC
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| 245 | 1 | 0 | |a Design of experiments |b statistical principles of research design and analysis |c Robert O. Kuehl |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a Pacific Grove [u.a.] |b Duxbury |c 2000 | |
| 300 | |a XVI, 666 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Rev. ed. of: Statistical principles of research design and analysis, c. 1994 | ||
| 650 | 4 | |a Analyse numérique | |
| 650 | 7 | |a Análise numérica |2 larpcal | |
| 650 | 7 | |a Estatística |2 larpcal | |
| 650 | 7 | |a Experimenteel ontwerp |2 gtt | |
| 650 | 7 | |a Planejamento e análise de experimentos |2 larpcal | |
| 650 | 4 | |a Recherche - Méthodes statistiques | |
| 650 | 4 | |a Sciences - Expériences - Méthodes statistiques | |
| 650 | 4 | |a Statistique | |
| 650 | 7 | |a Statistische analyse |2 gtt | |
| 650 | 4 | |a Naturwissenschaft | |
| 650 | 4 | |a Statistik | |
| 650 | 4 | |a Numerical analysis | |
| 650 | 4 | |a Research |x Statistical methods | |
| 650 | 4 | |a Science |x Experiments |x Statistical methods | |
| 650 | 4 | |a Statistics | |
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Datensatz im Suchindex
| _version_ | 1804137267492552704 |
|---|---|
| adam_text | DESIGN OF EXPERIMENTS STATISTICAL PRINCIPLES OF RESEARCH DESIGN AND
ANALYSIS SECOND EDITION ROBERT O. KUEHL THE UNIVERSITY OF ARIZONA
DUXBURY THOMSON LEARNING* PACIFIC GROVE * ALBANY * BELMONT * BONN *
BOSTON * CINCINNATI * DETROIT * JOHANNESBURG * LONDON * MADRID MELBOURNE
* MEXICO CITY * NEW YORK * PARIS * SINGAPORE * TOKYO * TORONTO *
WASHINGTON CONTENTS RESEARCH DESIGN PRINCIPLES 1 - 1.1 THE LEGACY OF SIR
RONALD A. FISHER 1 1.2 PLANNING FOR RESEARCH 2 1.3 EXPERIMENTS,
TREATMENTS, AND EXPERIMENTAL UNITS 3 1.4 RESEARCH HYPOTHESES GENERATE
TREATMENT DESIGNS 5 1.5 LOCAL CONTROL OF EXPERIMENTAL ERRORS 8 1.6
REPLICATION FOR VALID EXPERIMENTS 16 1.7 HOW MANY REPLICATIONS? 18 1.8
RANDOMIZATION FOR VALID INFERENCES 20 1.9 RELATIVE EFFICIENCY OF
EXPERIMENT DESIGNS 25 1.10 FROM PRINCIPLES TO PRACTICE: A CASE STUDY 26
GETTING STARTED WITH COMPLETELY RANDOMIZED DESIGNS 37 2.1 ASSEMBLING THE
RESEARCH DESIGN 37 2.2 HOW TO RANDOMIZE 39 2.3 PREPARATION OF DATA FILES
FOR THE ANALYSIS 41 2.4 A STATISTICAL MODEL FOR THE EXPERIMENT 42 2.5
ESTIMATION OF THE MODEL PARAMETERS WITH LEAST SQUARES 47 2.6 SUMS OF
SQUARES TO IDENTIFY IMPORTANT SOURCES OF VARIATION 50 2.7 A TREATMENT
EFFECTS MODEL 53 2.8 DEGREES OF FREEDOM 54 2.9 SUMMARIES IN THE ANALYSIS
OF VARIANCE TABLE 55 2.10 TESTS OF HYPOTHESES ABOUT LINEAR MODELS 5 6
2.11 SIGNIFICANCE TESTING AND TESTS OF HYPOTHESES 58 2.12 STANDARD
ERRORS AND CONFIDENCE INTERVALS FOR TREATMENT MEANS 59 2.13 UNEQUAL
REPLICATION OF THE TREATMENTS 60 2.14 HOW MANY REPLICATIONS FOR THE F
TEST? 63 VLL VLII CONTENTS 2A.1 APPENDIX: EXPECTED VALUES 70 2A.2
APPENDIX: EXPECTED MEAN SQUARES 71 TREATMENT COMPARISONS 73 3.1
TREATMENT COMPARISONS ANSWER RESEARCH QUESTIONS 73 3.2 PLANNING
COMPARISONS AMONG TREATMENTS 74 3.3 RESPONSE CURVES FOR QUANTITATIVE
TREATMENT FACTORS 83 3.4 MULTIPLE COMPARISONS AFFECT ERROR RATES 91 3.5
SIMULTANEOUS STATISTICAL INFERENCE 94 3.6 MULTIPLE COMPARISONS WITH THE
BEST TREATMENT 98 3.7 COMPARISON OF ALL TREATMENTS WITH A CONTROL 104
3.8 PAIRWISE COMPARISON OF ALL TREATMENTS 107 3.9 SUMMARY COMMENTS ON
MULTIPLE COMPARISONS 115 3 A APPENDIX: LINEAR FUNCTIONS OF RANDOM
VARIABLES 121 DIAGNOSING AGREEMENT BETWEEN THE DATA AND THE MODEL 123
4.1 VALID ANALYSIS DEPENDS ON VALID ASSUMPTIONS 123 4.2 EFFECTS OF
DEPARTURES FROM ASSUMPTIONS 123 4.3 RESIDUALS ARE THE BASIS OF
DIAGNOSTIC TOOLS 124 4.4 LOOKING FOR OUTLIERS WITH THE RESIDUALS 131 4.5
VARIANCE-STABILIZING TRANSFORMATIONS FOR DATA WITH ICNOWN DISTRIBUTIONS
133 4.6 POWER TRANSFORMATIONS TO STABILIZE VARIANCES 135 4.7
GENERALIZING THE LINEAR MODEL 140 4.8 MODEL EVALUATION WITH
RESIDUAL-FITTED SPREAD PLOTS 141 4A APPENDIX: DATA FOR EXAMPLE 4.1 147
EXPERIMENTS TO STUDY VARIANCES 148 5.1 RANDOM EFFECTS MODELS FOR
VARIANCES 148 5.2 A STATISTICAL MODEL FOR VARIANCE COMPONENTS 151 5.3
POINT ESTIMATES OF VARIANCE COMPONENTS 152 5.4 INTERVAL ESTIMATES FOR
VARIANCE COMPONENTS 153 5.5 COURSES OF ACTION WITH NEGATIVE VARIANCE
ESTIMATES 155 5.6 INTRACLASS CORRELATION MEASURES SIMILARITY IN A GROUP
155 5.7 UNEQUAL NUMBERS OF OBSERVATIONS IN THE GROUPS 157 5.8 HOW MANY
OBSERVATIONS TO STUDY VARIANCES? 158 5.9 RANDOM SUBSAMPLES TO PROCURE
DATA FOR THE EXPERIMENT 159 5.10 USING VARIANCE ESTIMATES TO ALLOCATE
SAMPLING EFFORTS 163 5.11 UNEQUAL NUMBERS OF REPLICATIONS AND SUBSAMPLES
164 5A APPENDIX: COEFFICIENT CALCULATIONS FOR EXPECTED MEAN SQUARES IN
TABLE 5.9 174 CONTENTS IX 6 FACTORIAL TREATMENT DESIGNS 175 6.1
EFFICIENT EXPERIMENTS WITH FACTORIAL TREATMENT DESIGNS 175 6.2 THREE
TYPES OF TREATMENT FACTOR EFFECTS 177 6.3 THE STATISTICAL MODEL FOR TWO
TREATMENT FACTORS 181 6.4 THE ANALYSIS FOR TWO FACTORS 183 6.5 USING
RESPONSE CURVES FOR QUANTITATIVE TREATMENT FACTORS 190 6.6 THREE
TREATMENT FACTORS 199 6.7 ESTIMATION OF ERROR VARIANCE WITH ONE
REPLICATION 205 6.8 HOW MANY REPLICATIONS TO TEST FACTOR EFFECTS? 208
6.9 UNEQUAL REPLICATION OF TREATMENTS 208 6A APPENDIX: LEAST SQUARES FOR
FACTORIAL TREATMENT DESIGNS 225 7 FACTORIAL TREATMENT DESIGNS: RANDOM
AND MIXED MODELS 232 7.1 RANDOM EFFECTS FOR FACTORIAL TREATMENT DESIGNS
232 7.2 MIXED MODELS 237 7.3 NESTED FACTOR DESIGNS: A VARIATION ON THE
THEME 243 7.4 NESTED AND CROSSED FACTORS DESIGNS 251 7.5 HOW MANY
REPLICATIONS? 255 7.6 EXPECTED MEAN SQUARE RULES 255 8 COMPLETE BLOCK
DESIGNS 263 8.1 BLOCKING TO INCREASE PRECISION 263 8.2 RANDOMIZED
COMPLETE BLOCK DESIGNS USE ONE BLOCKING CRITERION 264 8.3 LATIN SQUARE
DESIGNS USE TWO BLOCKING CRITERIA 275 8.4 FACTORIAL EXPERIMENTS IN
COMPLETE BLOCK DESIGNS 289 8.5 MISSING DATA IN BLOCKED DESIGNS 291 8.6
EXPERIMENTS PERFORMED SEVERAL TIMES 292 8A . APPENDIX: SELECTED LATIN
SQUARES 307 9 INCOMPLETE BLOCK DESIGNS: AN INTRODUCTION 310 9.1
INCOMPLETE BLOCKS OF TREATMENTS TO REDUCE BLOCK SIZE 310 9.2 BALANCED
INCOMPLETE BLOCK (BIB) DESIGNS 312 9.3 HOW TO RANDOMIZE INCOMPLETE BLOCK
DESIGNS 313 9.4 ANALYSIS OF BIB DESIGNS 315 9.5 ROW-COLUMN DESIGNS FOR
TWO BLOCKING CRITERIA 320 9.6 REDUCE EXPERIMENT SIZE WITH PARTIALLY
BALANCED (PBIB) DESIGNS 322 9.7 EFFICIENCY OF INCOMPLETE BLOCK DESIGNS
325 9A.1 APPENDIX: SELECTED.BALANCED INCOMPLETE BLOCK DESIGNS 330 9A.2
APPENDIX: SELECTED INCOMPLETE LATIN SQUARE DESIGNS 332 9A.3 APPENDIX:
LEAST SQUARES ESTIMATES FOR BIB DESIGNS 336 X CONTENTS 10 INCOMPLETE
BLOCK DESIGNS: RESOLVABLE AND CYCLIC DESIGNS 339 10.1 -* _ RESOLVABLE
DESIGNS TO HELP MANAGE THE EXPERIMENT 339 10.2 RESOLVABLE ROW-COLUMN
DESIGNS FOR TWO BLOCKING CRITERIA 342 10.3 CYCLIC DESIGNS SIMPLIFY
DESIGN CONSTRUCTION 345 10.4 CHOOSING INCOMPLETE BLOCK DESIGNS 352 10A.1
APPENDIX: PLANS FOR CYCLIC DESIGNS 360 10A.2 APPENDIX: GENERATING ARRAYS
FOR A DESIGNS 360 11 INCOMPLETE BLOCK DESIGNS: FACTORIAL TREATMENT
DESIGNS 362 11.1 TAKING GREATER ADVANTAGE OF FACTORIAL TREATMENT DESIGNS
362 11.2 2 FACTORIALS TO EVALUATE MANY FACTORS 363 11.3 INCOMPLETE
BLOCK DESIGNS FOR 2 N FACTORIALS 369 11.4 A GENERAL METHOD TO CREATE
INCOMPLETE BLOCKS 378 3 11.5 INCOMPLETE BLOCK DESIGNS FOR 3 FACTORIALS
383 11.6 CONCLUDING REMARKS 387 11A APPENDIX: INCOMPLETE BLOCK DESIGN
PLANS FOR 2 N FACTORIALS 390 12 FRACTIONAL FACTORIAL DESIGNS 391 12.1
REDUCE EXPERIMENT SIZE WITH FRACTIONAL TREATMENT DESIGNS 391 12.2 THE
HALF FRACTION OF THE 2 FACTORIAL 393 12.3 DESIGN RESOLUTION RELATED TO
ALIASES 398 12.4 ANALYSIS OF HALF REPLICATE 2 N-1 DESIGNS 399 12.5 THE
QUARTER FRACTIONS OF 2 N FACTORIALS 406 12.6 CONSTRUCTION OF 2 N ~ P
DESIGNS WITH RESOLUTION III AND IV 409 12.7 GENICHI TAGUCHI AND QUALITY
IMPROVEMENT 413 12.8 CONCLUDING REMARKS 415 12A APPENDIX: FRACTIONAL
FACTORIAL DESIGN PLANS 421 13 RESPONSE SURFACE DESIGNS 423 13.1 DESCRIBE
RESPONSES WITH EQUATIONS AND GRAPHS 423 13.2 IDENTIFY IMPORTANT FACTORS
WITH 2 N FACTORIALS 426 13.3 DESIGNS TO ESTIMATE SECOND-ORDER RESPONSE
SURFACES 431 13.4 QUADRATIC RESPONSE SURFACE ESTIMATION 440 13.5
RESPONSE SURFACE EXPLORATION 444 13.6 DESIGNS FOR MIXTURES OF
INGREDIENTS 449 13.7 ANALYSIS OF MIXTURE EXPERIMENTS 453 13 A.I
APPENDIX: LEAST SQUARES ESTIMATION OF REGRESSION MODELS 463 13A.2
APPENDIX: LOCATION OF COORDINATES FOR THE STATIONARY POINT 466 13A.3
APPENDIX: CANONICAL FORM OF THE QUADRATIC EQUATION 467 CONTENTS XI 14
SPLIT-PLOT DESIGNS 469 14.1 PLOTS OF DIFFERENT SIZE IN THE SAME
EXPERIMENT 469 14.2 TWO EXPERIMENTAL ERRORS FOR TWO PLOT SIZES 472 14.3
THE ANALYSIS FOR SPLIT-PLOT DESIGNS 473 14.4 STANDARD ERRORS FOR
TREATMENT FACTOR MEANS 478 14.5 FEATURES OF THE SPLIT-PLOT DESIGN 480
14.6 RELATIVE EFFICIENCY OF SUBPLOT AND WHOLE-PLOT COMPARISONS 481 14.7
THE SPLIT-SPLIT-PLOT DESIGN FOR THREE TREATMENT FACTORS 483 14.8 THE
SPLIT-BLOCK DESIGN 483 14.9 ADDITIONAL INFORMATION ABOUT SPLIT-PLOT
DESIGNS 486 15 REPEATED MEASURES DESIGNS 492 15.1 STUDIES OF TIME TRENDS
492 15.2 RELATIONSHIPS AMONG REPEATED MEASUREMENTS 495 15.3 A TEST FOR
THE HUYNH-FELDT ASSUMPTION 498 15.4 A UNIVARIATE ANALYSIS OF VARIANCE
FOR REPEATED MEASURES 499 15.5 ANALYSIS WHEN UNIVARIATE ANALYSIS
ASSUMPTIONS DO NOT HOLD 502 15.6 OTHER EXPERIMENTS WITH REPEATED
MEASURES PROPERTIES 510 15.7 OTHER MODELS FOR CORRELATION AMONG REPEATED
MEASURES 511 15A.I APPENDIX: THE MAUCHLY TEST FOR SPHERICITY 518 15A.2
APPENDIX: DEGREES OF FREEDOM ADJUSTMENTS FOR REPEATED MEASURES ANALYSIS
OF VARIANCE 519 16 CROSSOVER DESIGNS 520 16.1 ADMINISTER ALL TREATMENTS
TO EACH EXPERIMENTAL UNIT 520 16.2 ANALYSIS OF CROSSOVER DESIGNS 524
16.3 BALANCED DESIGNS FOR CROSSOVER STUDIES 530 16.4 CROSSOVER DESIGNS
FOR TWO TREATMENTS 536 16A.I APPENDIX: CODING DATA FILES FOR CROSSOVER
STUDIES 545 16A.2 APPENDIX: TREATMENT SUM OF SQUARES FOR BALANCED
DESIGNS 547 17 ANALYSIS OF COVARIANCE 550 17.1 LOCAL CONTROL WITH A
MEASURED COVARIATE 550 17.2 ANALYSIS OF COVARIANCE FOR COMPLETELY
RANDOMIZED DESIGNS 553 17.3 THE ANALYSIS OF COVARIANCE FOR BLOCKED
EXPERIMENT DESIGNS 565 17.4 PRACTICAL CONSEQUENCES OF COVARIANCE
ANALYSIS 570 REFERENCES 576 APPENDIX TABLES 587 ANSWERS TO SELECTED
EXERCISES 633 INDEX 661
|
| adam_txt |
DESIGN OF EXPERIMENTS STATISTICAL PRINCIPLES OF RESEARCH DESIGN AND
ANALYSIS SECOND EDITION ROBERT O. KUEHL THE UNIVERSITY OF ARIZONA
DUXBURY THOMSON LEARNING* PACIFIC GROVE * ALBANY * BELMONT * BONN *
BOSTON * CINCINNATI * DETROIT * JOHANNESBURG * LONDON * MADRID MELBOURNE
* MEXICO CITY * NEW YORK * PARIS * SINGAPORE * TOKYO * TORONTO *
WASHINGTON CONTENTS RESEARCH DESIGN PRINCIPLES 1 - 1.1 THE LEGACY OF SIR
RONALD A. FISHER 1 1.2 PLANNING FOR RESEARCH 2 1.3 EXPERIMENTS,
TREATMENTS, AND EXPERIMENTAL UNITS 3 1.4 RESEARCH HYPOTHESES GENERATE
TREATMENT DESIGNS 5 1.5 LOCAL CONTROL OF EXPERIMENTAL ERRORS 8 1.6
REPLICATION FOR VALID EXPERIMENTS 16 1.7 HOW MANY REPLICATIONS? 18 1.8
RANDOMIZATION FOR VALID INFERENCES 20 1.9 RELATIVE EFFICIENCY OF
EXPERIMENT DESIGNS 25 1.10 FROM PRINCIPLES TO PRACTICE: A CASE STUDY 26
GETTING STARTED WITH COMPLETELY RANDOMIZED DESIGNS 37 2.1 ASSEMBLING THE
RESEARCH DESIGN 37 2.2 HOW TO RANDOMIZE 39 2.3 PREPARATION OF DATA FILES
FOR THE ANALYSIS 41 2.4 A STATISTICAL MODEL FOR THE EXPERIMENT 42 2.5
ESTIMATION OF THE MODEL PARAMETERS WITH LEAST SQUARES 47 2.6 SUMS OF
SQUARES TO IDENTIFY IMPORTANT SOURCES OF VARIATION 50 2.7 A TREATMENT
EFFECTS MODEL 53 2.8 DEGREES OF FREEDOM 54 2.9 SUMMARIES IN THE ANALYSIS
OF VARIANCE TABLE 55 2.10 TESTS OF HYPOTHESES ABOUT LINEAR MODELS 5 6
2.11 SIGNIFICANCE TESTING AND TESTS OF HYPOTHESES 58 2.12 STANDARD
ERRORS AND CONFIDENCE INTERVALS FOR TREATMENT MEANS 59 2.13 UNEQUAL
REPLICATION OF THE TREATMENTS 60 2.14 HOW MANY REPLICATIONS FOR THE F
TEST? 63 VLL VLII CONTENTS 2A.1 APPENDIX: EXPECTED VALUES 70 2A.2
APPENDIX: EXPECTED MEAN SQUARES 71 TREATMENT COMPARISONS 73 3.1
TREATMENT COMPARISONS ANSWER RESEARCH QUESTIONS 73 3.2 PLANNING
COMPARISONS AMONG TREATMENTS 74 3.3 RESPONSE CURVES FOR QUANTITATIVE
TREATMENT FACTORS 83 3.4 MULTIPLE COMPARISONS AFFECT ERROR RATES 91 3.5
SIMULTANEOUS STATISTICAL INFERENCE 94 3.6 MULTIPLE COMPARISONS WITH THE
BEST TREATMENT 98 3.7 COMPARISON OF ALL TREATMENTS WITH A CONTROL 104
3.8 PAIRWISE COMPARISON OF ALL TREATMENTS 107 3.9 SUMMARY COMMENTS ON
MULTIPLE COMPARISONS 115 3 A APPENDIX: LINEAR FUNCTIONS OF RANDOM
VARIABLES 121 DIAGNOSING AGREEMENT BETWEEN THE DATA AND THE MODEL 123
4.1 VALID ANALYSIS DEPENDS ON VALID ASSUMPTIONS 123 4.2 EFFECTS OF
DEPARTURES FROM ASSUMPTIONS 123 4.3 RESIDUALS ARE THE BASIS OF
DIAGNOSTIC TOOLS 124 4.4 LOOKING FOR OUTLIERS WITH THE RESIDUALS 131 4.5
VARIANCE-STABILIZING TRANSFORMATIONS FOR DATA WITH ICNOWN DISTRIBUTIONS
133 4.6 POWER TRANSFORMATIONS TO STABILIZE VARIANCES 135 4.7
GENERALIZING THE LINEAR MODEL 140 4.8 MODEL EVALUATION WITH
RESIDUAL-FITTED SPREAD PLOTS 141 4A APPENDIX: DATA FOR EXAMPLE 4.1 147
EXPERIMENTS TO STUDY VARIANCES 148 5.1 RANDOM EFFECTS MODELS FOR
VARIANCES 148 5.2 A STATISTICAL MODEL FOR VARIANCE COMPONENTS 151 5.3
POINT ESTIMATES OF VARIANCE COMPONENTS 152 5.4 INTERVAL ESTIMATES FOR
VARIANCE COMPONENTS 153 5.5 COURSES OF ACTION WITH NEGATIVE VARIANCE
ESTIMATES 155 5.6 INTRACLASS CORRELATION MEASURES SIMILARITY IN A GROUP
155 5.7 UNEQUAL NUMBERS OF OBSERVATIONS IN THE GROUPS 157 5.8 HOW MANY
OBSERVATIONS TO STUDY VARIANCES? 158 5.9 RANDOM SUBSAMPLES TO PROCURE
DATA FOR THE EXPERIMENT 159 5.10 USING VARIANCE ESTIMATES TO ALLOCATE
SAMPLING EFFORTS 163 5.11 UNEQUAL NUMBERS OF REPLICATIONS AND SUBSAMPLES
164 5A APPENDIX: COEFFICIENT CALCULATIONS FOR EXPECTED MEAN SQUARES IN
TABLE 5.9 174 CONTENTS IX 6 FACTORIAL TREATMENT DESIGNS 175 6.1
EFFICIENT EXPERIMENTS WITH FACTORIAL TREATMENT DESIGNS 175 6.2 THREE
TYPES OF TREATMENT FACTOR EFFECTS 177 6.3 THE STATISTICAL MODEL FOR TWO
TREATMENT FACTORS 181 6.4 THE ANALYSIS FOR TWO FACTORS 183 6.5 USING
RESPONSE CURVES FOR QUANTITATIVE TREATMENT FACTORS 190 6.6 THREE
TREATMENT FACTORS 199 6.7 ESTIMATION OF ERROR VARIANCE WITH ONE
REPLICATION 205 6.8 HOW MANY REPLICATIONS TO TEST FACTOR EFFECTS? 208
6.9 UNEQUAL REPLICATION OF TREATMENTS 208 6A APPENDIX: LEAST SQUARES FOR
FACTORIAL TREATMENT DESIGNS 225 7 FACTORIAL TREATMENT DESIGNS: RANDOM
AND MIXED MODELS 232 7.1 RANDOM EFFECTS FOR FACTORIAL TREATMENT DESIGNS
232 7.2 MIXED MODELS 237 7.3 NESTED FACTOR DESIGNS: A VARIATION ON THE
THEME 243 7.4 NESTED AND CROSSED FACTORS DESIGNS 251 7.5 HOW MANY
REPLICATIONS? 255 7.6 EXPECTED MEAN SQUARE RULES 255 8 COMPLETE BLOCK
DESIGNS 263 8.1 BLOCKING TO INCREASE PRECISION 263 8.2 RANDOMIZED
COMPLETE BLOCK DESIGNS USE ONE BLOCKING CRITERION 264 8.3 LATIN SQUARE
DESIGNS USE TWO BLOCKING CRITERIA 275 8.4 FACTORIAL EXPERIMENTS IN
COMPLETE BLOCK DESIGNS 289 8.5 MISSING DATA IN BLOCKED DESIGNS 291 8.6
EXPERIMENTS PERFORMED SEVERAL TIMES 292 8A . APPENDIX: SELECTED LATIN
SQUARES 307 9 INCOMPLETE BLOCK DESIGNS: AN INTRODUCTION 310 9.1
INCOMPLETE BLOCKS OF TREATMENTS TO REDUCE BLOCK SIZE 310 9.2 BALANCED
INCOMPLETE BLOCK (BIB) DESIGNS 312 9.3 HOW TO RANDOMIZE INCOMPLETE BLOCK
DESIGNS 313 9.4 ANALYSIS OF BIB DESIGNS 315 9.5 ROW-COLUMN DESIGNS FOR
TWO BLOCKING CRITERIA 320 9.6 REDUCE EXPERIMENT SIZE WITH PARTIALLY
BALANCED (PBIB) DESIGNS 322 9.7 EFFICIENCY OF INCOMPLETE BLOCK DESIGNS
325 9A.1 APPENDIX: SELECTED.BALANCED INCOMPLETE BLOCK DESIGNS 330 9A.2
APPENDIX: SELECTED INCOMPLETE LATIN SQUARE DESIGNS 332 9A.3 APPENDIX:
LEAST SQUARES ESTIMATES FOR BIB DESIGNS 336 X CONTENTS 10 INCOMPLETE
BLOCK DESIGNS: RESOLVABLE AND CYCLIC DESIGNS 339 10.1 -* _ RESOLVABLE
DESIGNS TO HELP MANAGE THE EXPERIMENT 339 10.2 RESOLVABLE ROW-COLUMN
DESIGNS FOR TWO BLOCKING CRITERIA 342 10.3 CYCLIC DESIGNS SIMPLIFY
DESIGN CONSTRUCTION 345 10.4 CHOOSING INCOMPLETE BLOCK DESIGNS 352 10A.1
APPENDIX: PLANS FOR CYCLIC DESIGNS 360 10A.2 APPENDIX: GENERATING ARRAYS
FOR A DESIGNS 360 11 INCOMPLETE BLOCK DESIGNS: FACTORIAL TREATMENT
DESIGNS 362 11.1 TAKING GREATER ADVANTAGE OF FACTORIAL TREATMENT DESIGNS
362 11.2 2" FACTORIALS TO EVALUATE MANY FACTORS 363 11.3 INCOMPLETE
BLOCK DESIGNS FOR 2 N FACTORIALS 369 11.4 A GENERAL METHOD TO CREATE
INCOMPLETE BLOCKS 378 3 11.5 INCOMPLETE BLOCK DESIGNS FOR 3" FACTORIALS
383 11.6 CONCLUDING REMARKS 387 11A APPENDIX: INCOMPLETE BLOCK DESIGN
PLANS FOR 2 N FACTORIALS 390 12 FRACTIONAL FACTORIAL DESIGNS 391 12.1
REDUCE EXPERIMENT SIZE WITH FRACTIONAL TREATMENT DESIGNS 391 12.2 THE
HALF FRACTION OF THE 2" FACTORIAL 393 12.3 DESIGN RESOLUTION RELATED TO
ALIASES 398 12.4 ANALYSIS OF HALF REPLICATE 2 N-1 DESIGNS 399 12.5 THE
QUARTER FRACTIONS OF 2 N FACTORIALS 406 12.6 CONSTRUCTION OF 2 N ~ P
DESIGNS WITH RESOLUTION III AND IV 409 12.7 GENICHI TAGUCHI AND QUALITY
IMPROVEMENT 413 12.8 CONCLUDING REMARKS 415 12A APPENDIX: FRACTIONAL
FACTORIAL DESIGN PLANS 421 13 RESPONSE SURFACE DESIGNS 423 13.1 DESCRIBE
RESPONSES WITH EQUATIONS AND GRAPHS 423 13.2 IDENTIFY IMPORTANT FACTORS
WITH 2 N FACTORIALS 426 13.3 DESIGNS TO ESTIMATE SECOND-ORDER RESPONSE
SURFACES 431 13.4 QUADRATIC RESPONSE SURFACE ESTIMATION 440 13.5
RESPONSE SURFACE EXPLORATION 444 13.6 DESIGNS FOR MIXTURES OF
INGREDIENTS 449 13.7 ANALYSIS OF MIXTURE EXPERIMENTS 453 13 A.I
APPENDIX: LEAST SQUARES ESTIMATION OF REGRESSION MODELS 463 13A.2
APPENDIX: LOCATION OF COORDINATES FOR THE STATIONARY POINT 466 13A.3
APPENDIX: CANONICAL FORM OF THE QUADRATIC EQUATION 467 CONTENTS XI 14
SPLIT-PLOT DESIGNS 469 14.1 PLOTS OF DIFFERENT SIZE IN THE SAME
EXPERIMENT 469 14.2 TWO EXPERIMENTAL ERRORS FOR TWO PLOT SIZES 472 14.3
THE ANALYSIS FOR SPLIT-PLOT DESIGNS 473 14.4 STANDARD ERRORS FOR
TREATMENT FACTOR MEANS 478 14.5 FEATURES OF THE SPLIT-PLOT DESIGN 480
14.6 RELATIVE EFFICIENCY OF SUBPLOT AND WHOLE-PLOT COMPARISONS 481 14.7
THE SPLIT-SPLIT-PLOT DESIGN FOR THREE TREATMENT FACTORS 483 14.8 THE
SPLIT-BLOCK DESIGN 483 14.9 ADDITIONAL INFORMATION ABOUT SPLIT-PLOT
DESIGNS 486 15 REPEATED MEASURES DESIGNS 492 15.1 STUDIES OF TIME TRENDS
492 15.2 RELATIONSHIPS AMONG REPEATED MEASUREMENTS 495 15.3 A TEST FOR
THE HUYNH-FELDT ASSUMPTION 498 15.4 A UNIVARIATE ANALYSIS OF VARIANCE
FOR REPEATED MEASURES 499 15.5 ANALYSIS WHEN UNIVARIATE ANALYSIS
ASSUMPTIONS DO NOT HOLD 502 15.6 OTHER EXPERIMENTS WITH REPEATED
MEASURES PROPERTIES 510 15.7 OTHER MODELS FOR CORRELATION AMONG REPEATED
MEASURES 511 15A.I APPENDIX: THE MAUCHLY TEST FOR SPHERICITY 518 15A.2
APPENDIX: DEGREES OF FREEDOM ADJUSTMENTS FOR REPEATED MEASURES ANALYSIS
OF VARIANCE 519 16 CROSSOVER DESIGNS 520 16.1 ADMINISTER ALL TREATMENTS
TO EACH EXPERIMENTAL UNIT 520 16.2 ANALYSIS OF CROSSOVER DESIGNS 524
16.3 BALANCED DESIGNS FOR CROSSOVER STUDIES 530 16.4 CROSSOVER DESIGNS
FOR TWO TREATMENTS 536 16A.I APPENDIX: CODING DATA FILES FOR CROSSOVER
STUDIES 545 16A.2 APPENDIX: TREATMENT SUM OF SQUARES FOR BALANCED
DESIGNS 547 17 ANALYSIS OF COVARIANCE 550 17.1 LOCAL CONTROL WITH A
MEASURED COVARIATE 550 17.2 ANALYSIS OF COVARIANCE FOR COMPLETELY
RANDOMIZED DESIGNS 553 17.3 THE ANALYSIS OF COVARIANCE FOR BLOCKED
EXPERIMENT DESIGNS 565 17.4 PRACTICAL CONSEQUENCES OF COVARIANCE
ANALYSIS 570 REFERENCES 576 APPENDIX TABLES 587 ANSWERS TO SELECTED
EXERCISES 633 INDEX 661 |
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| author | Kuehl, Robert O. |
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| discipline | Allgemeines Mathematik Geographie |
| discipline_str_mv | Allgemeines Mathematik Geographie |
| edition | 2. ed. |
| format | Book |
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| genre_facet | Lehrbuch |
| id | DE-604.BV023039361 |
| illustrated | Illustrated |
| index_date | 2024-07-02T19:20:04Z |
| indexdate | 2024-07-09T21:09:35Z |
| institution | BVB |
| isbn | 0534368344 9780534368340 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016242969 |
| oclc_num | 41142956 |
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| owner_facet | DE-703 DE-522 DE-19 DE-BY-UBM DE-188 |
| physical | XVI, 666 S. graph. Darst. |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Duxbury |
| record_format | marc |
| spelling | Kuehl, Robert O. Verfasser aut Design of experiments statistical principles of research design and analysis Robert O. Kuehl 2. ed. Pacific Grove [u.a.] Duxbury 2000 XVI, 666 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Rev. ed. of: Statistical principles of research design and analysis, c. 1994 Analyse numérique Análise numérica larpcal Estatística larpcal Experimenteel ontwerp gtt Planejamento e análise de experimentos larpcal Recherche - Méthodes statistiques Sciences - Expériences - Méthodes statistiques Statistique Statistische analyse gtt Naturwissenschaft Statistik Numerical analysis Research Statistical methods Science Experiments Statistical methods Statistics Versuchsplanung (DE-588)4078859-3 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Versuchsplanung (DE-588)4078859-3 s DE-604 Früher u.d.T. Kuehl, Robert O. Statistical principles of research design and analysis GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016242969&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kuehl, Robert O. Design of experiments statistical principles of research design and analysis Analyse numérique Análise numérica larpcal Estatística larpcal Experimenteel ontwerp gtt Planejamento e análise de experimentos larpcal Recherche - Méthodes statistiques Sciences - Expériences - Méthodes statistiques Statistique Statistische analyse gtt Naturwissenschaft Statistik Numerical analysis Research Statistical methods Science Experiments Statistical methods Statistics Versuchsplanung (DE-588)4078859-3 gnd |
| subject_GND | (DE-588)4078859-3 (DE-588)4123623-3 |
| title | Design of experiments statistical principles of research design and analysis |
| title_auth | Design of experiments statistical principles of research design and analysis |
| title_exact_search | Design of experiments statistical principles of research design and analysis |
| title_exact_search_txtP | Design of experiments statistical principles of research design and analysis |
| title_full | Design of experiments statistical principles of research design and analysis Robert O. Kuehl |
| title_fullStr | Design of experiments statistical principles of research design and analysis Robert O. Kuehl |
| title_full_unstemmed | Design of experiments statistical principles of research design and analysis Robert O. Kuehl |
| title_old | Kuehl, Robert O. Statistical principles of research design and analysis |
| title_short | Design of experiments |
| title_sort | design of experiments statistical principles of research design and analysis |
| title_sub | statistical principles of research design and analysis |
| topic | Analyse numérique Análise numérica larpcal Estatística larpcal Experimenteel ontwerp gtt Planejamento e análise de experimentos larpcal Recherche - Méthodes statistiques Sciences - Expériences - Méthodes statistiques Statistique Statistische analyse gtt Naturwissenschaft Statistik Numerical analysis Research Statistical methods Science Experiments Statistical methods Statistics Versuchsplanung (DE-588)4078859-3 gnd |
| topic_facet | Analyse numérique Análise numérica Estatística Experimenteel ontwerp Planejamento e análise de experimentos Recherche - Méthodes statistiques Sciences - Expériences - Méthodes statistiques Statistique Statistische analyse Naturwissenschaft Statistik Numerical analysis Research Statistical methods Science Experiments Statistical methods Statistics Versuchsplanung Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016242969&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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