LEADER 05511nam 2200673 a 450 001 9910141422503321 005 20230801224105.0 010 $a1-283-57135-8 010 $a9786613883803 010 $a1-118-35199-1 010 $a1-118-35198-3 010 $a1-118-35196-7 035 $a(CKB)2670000000237368 035 $a(EBL)894399 035 $a(OCoLC)808366457 035 $a(SSID)ssj0000706231 035 $a(PQKBManifestationID)11474675 035 $a(PQKBTitleCode)TC0000706231 035 $a(PQKBWorkID)10626331 035 $a(PQKB)10130014 035 $a(MiAaPQ)EBC894399 035 $a(Au-PeEL)EBL894399 035 $a(CaPaEBR)ebr10593122 035 $a(CaONFJC)MIL388380 035 $a(EXLCZ)992670000000237368 100 $a20120228d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aUsing the Weibull distribution$b[electronic resource] $ereliability, modeling, and inference /$fJohn I. McCool 210 $aHoboken, N.J. $cJohn Wiley & Sons$dc2012 215 $a1 online resource (368 p.) 225 0$aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 $a1-118-21798-5 320 $aIncludes bibliographical references and index. 327 $aUsing the Weibull Distribution; Contents; Preface; CHAPTER 1: Probability; 1.1 SAMPLE SPACES AND EVENTS; 1.2 MUTUALLY EXCLUSIVE EVENTS; 1.3 VENN DIAGRAMS; 1.4 UNIONS OF EVENTS AND JOINT PROBABILITY; 1.5 CONDITIONAL PROBABILITY; 1.6 INDEPENDENCE; 1.7 PARTITIONS AND THE LAW OF TOTAL PROBABILITY; 1.8 RELIABILITY; 1.9 SERIES SYSTEMS; 1.10 PARALLEL SYSTEMS; 1.11 COMPLEX SYSTEMS; 1.12 CROSSLINKED SYSTEMS; 1.13 RELIABILITY IMPORTANCE; REFERENCES; EXERCISES; CHAPTER 2: Discrete and Continuous Random Variables; 2.1 PROBABILITY DISTRIBUTIONS; 2.2 FUNCTIONS OF A RANDOM VARIABLE 327 $a2.3 JOINTLY DISTRIBUTED DISCRETE RANDOM VARIABLES2.4 CONDITIONAL EXPECTATION; 2.5 THE BINOMIAL DISTRIBUTION; 2.5.1 Confidence Limits for the Binomial Proportion p; 2.6 THE POISSON DISTRIBUTION; 2.7 THE GEOMETRIC DISTRIBUTION; 2.8 CONTINUOUS RANDOM VARIABLES; 2.8.1 The Hazard Function; 2.9 JOINTLY DISTRIBUTED CONTINUOUS RANDOM VARIABLES; 2.10 SIMULATING SAMPLES FROM CONTINUOUS DISTRIBUTIONS; 2.11 THE NORMAL DISTRIBUTION; 2.12 DISTRIBUTION OF THE SAMPLE MEAN; 2.12.1 P[X < Y] for Normal Variables; 2.13 THE LOGNORMAL DISTRIBUTION; 2.14 SIMPLE LINEAR REGRESSION; REFERENCES; EXERCISES 327 $aCHAPTER 3: Properties of the Weibull Distribution3.1 THE WEIBULL CUMULATIVE DISTRIBUTION FUNCTION (CDF), PERCENTILES, MOMENTS, AND HAZARD FUNCTION; 3.1.1 Hazard Function; 3.1.2 The Mode; 3.1.3 Quantiles; 3.1.4 Moments; 3.2 THE MINIMA OF WEIBULL SAMPLES; 3.3 TRANSFORMATIONS; 3.3.1 The Power Transformation; 3.3.2 The Logarithmic Transformation; 3.4 THE CONDITIONAL WEIBULL DISTRIBUTION; 3.5 QUANTILES FOR ORDER STATISTICS OF A WEIBULL SAMPLE; 3.5.1 The Weakest Link Phenomenon; 3.6 SIMULATING WEIBULL SAMPLES; REFERENCES; EXERCISES; CHAPTER 4: Weibull Probability Models; 4.1 SYSTEM RELIABILITY 327 $a4.1.1 Series Systems4.1.2 Parallel Systems; 4.1.3 Standby Parallel; 4.2 WEIBULL MIXTURES; 4.3 P(Y < X); 4.4 RADIAL ERROR; 4.5 PRO RATA WARRANTY; 4.6 OPTIMUM AGE REPLACEMENT; 4.6.1 Age Replacement; 4.6.2 MTTF for a Maintained System; 4.7 RENEWAL THEORY; 4.7.1 Block Replacement; 4.7.2 Free Replacement Warranty; 4.7.3 A Renewing Free Replacement Warranty; 4.8 OPTIMUM BIDDING; 4.9 OPTIMUM BURN-IN; 4.10 SPARE PARTS PROVISIONING; REFERENCES; EXERCISES; CHAPTER 5: Estimation in Single Samples; 5.1 POINT AND INTERVAL ESTIMATION; 5.2 CENSORING; 5.3 ESTIMATION METHODS; 5.3.1 Menon's Method 327 $a5.3.2 An Order Statistic Estimate of x0.105.4 GRAPHICAL ESTIMATION OF WEIBULL PARAMETERS; 5.4.1 Complete Samples; 5.4.2 Graphical Estimation in Censored Samples; 5.5 MAXIMUM LIKELIHOOD ESTIMATION; 5.5.1 The Exponential Distribution; 5.5.2 Confidence Intervals for the Exponential Distribution-Type II Censoring; 5.5.3 Estimation for the Exponential Distribution-Interval Censoring; 5.5.4 Estimation for the Exponential Distribution-Type I Censoring; 5.5.5 Estimation for the Exponential Distribution-The Zero Failures Case; 5.6 ML ESTIMATION FOR THE WEIBULL DISTRIBUTION; 5.6.1 Shape Parameter Known 327 $a5.6.2 Confidence Interval for the Weibull Scale Parameter-Shape Parameter Known, Type II Censoring 330 $aUnderstand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explai 410 0$aWiley Series in Probability and Statistics 606 $aWeibull distribution$vTextbooks 606 $aProbabilities$vTextbooks 615 0$aWeibull distribution 615 0$aProbabilities 676 $a519.2/4 700 $aMcCool$b John$f1936-$0875374 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141422503321 996 $aUsing the Weibull distribution$91954381 997 $aUNINA