LEADER 01431nas 2200445- 450 001 9910303548703321 005 20230217213020.0 011 $a2469-536X 035 $a(DE-599)ZDB2851990-5 035 $a(OCoLC)559250465 035 $a(CKB)110978966553512 035 $a(CONSER)--2015203096 035 $a(EXLCZ)99110978966553512 100 $a20100318a19729999 --- a 101 0 $aeng 135 $aurbn||||||abp 135 $aurbn||||||ada 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aRailroad history 210 1$aBoston, Massachusetts :$cThe Railway & Locomotive Historical Society, Inc.,$d[1972-] 215 $avolumes $cillustrations ;$d23 cm 300 $aRefereed/Peer-reviewed 300 $aOfficial journal of the Railway and Locomotive Historical Society. 311 08$aRailroad history 0090-7847 (DLC) 73642261 (OCoLC)1785797 517 1 $aRailway and Locomotive Historical Society railway history 531 0 $aRailr. hist. 606 $aRailroads$xHistory$vPeriodicals 606 $aRailroads$2fast$3(OCoLC)fst01088711 608 $aHistory.$2fast 608 $aPeriodicals.$2fast 615 0$aRailroads$xHistory 615 7$aRailroads. 676 $a385.09 712 02$aRailway & Locomotive Historical Society. 906 $aJOURNAL 912 $a9910303548703321 996 $aRailroad history$92268777 997 $aUNINA LEADER 05456nam 2200673Ia 450 001 9910830804103321 005 20230721023403.0 010 $a1-282-31683-4 010 $a9786612316838 010 $a0-470-54993-9 010 $a0-470-54992-0 035 $a(CKB)1000000000821955 035 $a(EBL)468584 035 $a(SSID)ssj0000354780 035 $a(PQKBManifestationID)11298739 035 $a(PQKBTitleCode)TC0000354780 035 $a(PQKBWorkID)10314581 035 $a(PQKB)10908515 035 $a(MiAaPQ)EBC468584 035 $a(OCoLC)463438643 035 $a(EXLCZ)991000000000821955 100 $a20090511d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical methods for groundwater monitoring$b[electronic resource] /$fRobert D. Gibbons, Dulal Bhaumik, Subhash Aryal 205 $a2nd ed. 210 $aHoboken, NJ $cWiley$dc2009 215 $a1 online resource (402 p.) 225 1 $aStatistics in Practice ;$vv.59 300 $aDescription based upon print version of record. 311 $a0-470-16496-4 320 $aIncludes bibliographical references and index. 327 $aSTATISTICAL METHODS FOR GROUNDWATER MONITORING; CONTENTS; Preface; Acknowledgments; Acronyms; 1 NORMAL PREDICTION INTERVALS; 1.1 Overview; 1.2 Prediction Intervals for the Next Single Measurement from a Normal Distribution; 1.3 Prediction Limits for the Next k Measurements from a Normal Distribution; 1.4 Normal Prediction Limits with Resampling; 1.5 Simultaneous Normal Prediction Limits for the Next ? Samples; 1.6 Simultaneous Normal Prediction Limits for the Next ? of m Measurements at Each of ? Monitoring Wells 327 $a1.7 Normal Prediction Limits for the Mean(s) of m > 1 Future Measurements at Each of k Monitoring Wells1.8 Summary; 2 NONPARAMETRIC PREDICTION INTERVALS; 2.1 Overview; 2.2 Pass 1 of m Samples; 2.3 Pass m - 1 of m Samples; 2.4 Pass First or All m - 1 Resamples; 2.5 Nonparametric Prediction Limits for the Median of m Future Measurements at Each of k Locations; 2.6 Summary; 3 PREDICTION INTERVALS FOR OTHER DISTRIBUTIONS; 3.1 Overview; 3.2 Lognormal Distribution; 3.2.1 UPL for a Single Future Observation; 3.2.2 Prediction Limits for m = 1 Future Measurement at Each of k Locations 327 $a3.3 Lognormal Prediction Limits for the Median of m Future Measurements3.4 Lognormal Prediction Limits for the Mean of m Future Measurements; 3.5 Poisson Distribution; 3.5.1 Poisson Prediction Limits; 3.5.2 Discussion; 3.6 Summary; 4 GAMMA PREDICTION INTERVALS AND SOME RELATED TOPICS; 4.1 Overview; 4.2 Gamma Distribution; 4.2.1 Prediction Limits for a Single Measurement from a Gamma Distribution; 4.2.2 Simultaneous Gamma Prediction Limits for the Next r of m Measurements at Each of k Monitoring Wells; 4.3 Comparison of the Gamma Mean to a Regulatory Standard; 4.4 Summary 327 $a5 TOLERANCE INTERVALS5.1 Overview; 5.2 Normal Tolerance Limits; 5.3 Poisson Tolerance Limits; 5.4 Gamma Tolerance Limits; 5.5 Nonparametric Tolerance Limits; 5.6 Summary; 6 METHOD DETECTION LIMITS; 6.1 Overview; 6.2 Single Concentration Designs; 6.2.1 Kaiser-Currie Method; 6.2.2 USEPA-Glaser et al. Method; 6.3 Calibration Designs; 6.3.1 Confidence Intervals for Calibration Lines; 6.3.2 Tolerance Intervals for Calibration Lines; 6.3.3 Prediction Intervals for Calibration Lines; 6.3.4 Hubaux and Vos Method; 6.3.5 The Procedure Due to Clayton and Co-Workers 327 $a6.3.6 A Procedure Based on Tolerance Intervals6.3.7 MDLs for Calibration Data with Nonconstant Variance; 6.3.8 Experimental Design of Detection Limit Studies; 6.3.9 Obtaining the Calibration Data; 6.4 Summary; 7 PRACTICAL QUANTITATION LIMITS; 7.1 Overview; 7.2 Operational Definition; 7.3 A Statistical Estimate of the PQL; 7.4 Derivation of the PQL; 7.5 A Simpler Alternative; 7.6 Uncertainty in ?*?; 7.7 The Effect of the Transformation; 7.8 Selecting N; 7.9 Summary; 8 INTERLABORATORY CALIBRATION; 8.1 Overview 327 $a8.2 General Random-Effects Regression Model for the Case of Heteroscedastic Measurement Errors 330 $aA new edition of the most comprehensive overview of statistical methods for environmental monitoring applications Thoroughly updated to provide current research findings, Statistical Methods for Groundwater Monitoring, Second Edition continues to provide a comprehensive overview and accessible treatment of the statistical methods that are useful in the analysis of environmental data. This new edition expands focus on statistical comparison to regulatory standards that are a vital part of assessment, compliance, and corrective action monitoring in the environmental sciences. 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