LEADER 05678nam 2200757 a 450 001 9910812267903321 005 20240516151602.0 010 $a9786613883803 010 $a9781283571357 010 $a1283571358 010 $a9781118351994 010 $a1118351991 010 $a9781118351987 010 $a1118351983 010 $a9781118351963 010 $a1118351967 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(Perlego)1012681 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 $ereliability, modeling, and inference /$fJohn I. McCool 205 $a1st ed. 210 $aHoboken, N.J. $cJohn Wiley & Sons$dc2012 215 $a1 online resource (368 p.) 225 0$aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 08$a9781118217986 311 08$a1118217985 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-$01718131 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910812267903321 996 $aUsing the Weibull distribution$94114866 997 $aUNINA LEADER 01892ojm 2200277z- 450 001 9910136193703321 005 20251118110509.0 010 $a1-5159-9252-7 035 $a(CKB)3710000000916138 035 $a(BIP)060405275 035 $a(ODN)ODN0003026564 035 $a(EXLCZ)993710000000916138 100 $a20231107c2016uuuu -u- - 101 0 $aeng 200 10$aHound of the Sea : Wild Man. Wild Waves. Wild Wisdom 210 $cTantor Audio 330 8 $aBig Wave surfer Garrett McNamara set the world record for the sport, surfing a seventy-eight-foot wave in Nazare, Portugal, in 2011, a record he smashed two years later at the same break. Propelled by the challenge and promise of bigger, more difficult waves, this adrenaline-fueled loner and polarizing figure travels the globe to ride the most dangerous swells the oceans have to offer, from calving glaciers to hurricane swells.But what motivates McNamara to go to such extremes-to risk everything for one thrilling ride? Is riding giant waves the ultimate exercise in control or surrender?Personal and emotional, listeners will know McNamara as never before, seeing for the first time the personal alongside the professional in an exciting, intimate look at what drives this inventive, iconoclastic man. Surfing awesome giants isn't just thrill seeking, he explains-it's about vanquishing fears and defeating obstacles past and present. Surfers and non-surfers alike will embrace McNamara's story-as they have William Finnegan's Barbarian Days-and its intimate look at the enigmatic pursuit of riding waves, big and small. 517 $aHound of the Sea 676 $a797.32092 700 $aMcNamara$b Garrett$01435372 702 $aKarbo$b Karen 702 $aSanda$b Rudy$4nrt 906 $aAUDIO 912 $a9910136193703321 996 $aHound of the Sea : Wild Man. Wild Waves. Wild Wisdom$93592800 997 $aUNINA