LEADER 05647nam 2200769Ia 450 001 9910133222103321 005 20200520144314.0 010 $a9786613282675 010 $a9781283282673 010 $a1283282674 010 $a9781118058107 010 $a1118058100 010 $a9781118058114 010 $a1118058119 010 $a9781118058091 010 $a1118058097 035 $a(CKB)3400000000015954 035 $a(EBL)697539 035 $a(SSID)ssj0000550606 035 $a(PQKBManifestationID)11360297 035 $a(PQKBTitleCode)TC0000550606 035 $a(PQKBWorkID)10524143 035 $a(PQKB)10276367 035 $a(MiAaPQ)EBC697539 035 $a(OCoLC)746324261 035 $a(CaSebORM)9780470590744 035 $a(OCoLC)798674372 035 $a(OCoLC)ocn798674372 035 $a(Perlego)1013745 035 $a(EXLCZ)993400000000015954 100 $a20110527d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical methods for quality improvement /$fThomas P. Ryan 205 $a3rd ed. 210 $aHoboken, N.J. $cWiley$dc2011 215 $a1 online resource (702 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 08$a9780470590744 311 08$a0470590742 320 $aIncludes bibliographical references and indexes. 327 $aStatistical Methods forQuality Improvement; Contents; Preface; Preface to the Second Edition; Preface to the First Edition; PART I FUNDAMENTAL QUALITY IMPROVEMENT AND STATISTICAL CONCEPTS; 1 Introduction; 1.1 Quality and Productivity; 1.2 Quality Costs (or Does It?); 1.3 The Need for Statistical Methods; 1.4 Early Use of Statistical Methods for Improving Quality; 1.5 Influential Quality Experts; 1.6 Summary; References; 2 Basic Tools for Improving Quality; 2.1 Histogram; 2.2 Pareto Charts; 2.3 Scatter Plots; 2.3.1 Variations of Scatter Plots; 2.4 Control Chart; 2.5 Check Sheet 327 $a2.6 Cause-and-Effect Diagram2.7 Defect Concentration Diagram; 2.8 The Seven Newer Tools; 2.8.1 Affinity Diagram; 2.8.2 Interrelationship Digraph; 2.8.3 Tree Diagram; 2.8.4 Prioritization Matrix; 2.8.5 Matrix Diagram; 2.8.6 Process Decision Program Chart; 2.8.7 Activity Network Diagram; 2.9 Software; 2.10 Summary; References; Exercises; 3 Basic Concepts in Statistics and Probability; 3.1 Probability; 3.2 Sample Versus Population; 3.3 Location; 3.4 Variation; 3.5 Discrete Distributions; 3.5.1 Binomial Distribution; 3.5.2 Beta-Binomial Distribution; 3.5.3 Poisson Distribution 327 $a3.5.4 Geometric Distribution3.5.5 Negative Binomial Distribution; 3.5.6 Hypergeometric Distribution; 3.6 Continuous Distributions; 3.6.1 Normal Distribution; 3.6.2 t Distribution; 3.6.3 Exponential Distribution; 3.6.4 Lognormal Distribution; 3.6.5 Weibull Distribution; 3.6.6 Extreme Value Distribution; 3.6.7 Gamma Distribution; 3.6.8 Chi-Square Distribution; 3.6.9 Truncated Normal Distribution; 3.6.10 Bivariate and Multivariate Normal Distributions; 3.6.11 F Distribution; 3.6.12 Beta Distribution; 3.6.13 Uniform Distribution; 3.7 Choice of Statistical Distribution; 3.8 Statistical Inference 327 $a3.8.1 Central Limit Theorem3.8.2 Point Estimation; 3.8.2.1 Maximum Likelihood Estimation; 3.8.3 Confidence Intervals; 3.8.4 Tolerance Intervals; 3.8.5 Hypothesis Tests; 3.8.5.1 Probability Plots; 3.8.5.2 Likelihood Ratio Tests; 3.8.6 Bonferroni Intervals; 3.9 Enumerative Studies Versus Analytic Studies; References; Exercises; PARTII CONTROL CHARTS AND PROCESS CAPABILITY; 4 Control Charts for Measurements With Subgrouping (for One Variable); 4.1 Basic Control Chart Principles; 4.2 Real-Time Control Charting Versus Analysis of Past Data 327 $a4.3 Control Charts: When to Use, Where to Use, How Many to Use4.4 Benefits from the Use of Control Charts; 4.5 Rational Subgroups; 4.6 Basic Statistical Aspects of Control Charts; 4.7 Illustrative Example; 4.7.1 R-Chart; 4.7.2 R-Chart with Probability Limits; 4.7.3 S-Chart; 4.7.4 S-Chart with Probability Limits; 4.7.5 S2-Chart; 4.7.6 X-Chart; 4.7.7 Recomputing Control Limits; 4.7.8 Applying Control Limits to Future Production; 4.7.9 Combining an X- and an S-Chart; 4.7.10 Standards for Control Charts; 4.7.11 Deleting Points; 4.7.12 Target Values; 4.8 Illustrative Example with Real Data 327 $a4.9 Determining the Point of a Parameter Change 330 $aPraise for the Second Edition ""As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available.""-Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improve 410 0$aWiley series in probability and statistics. 606 $aQuality control$xStatistical methods 606 $aProcess control$xStatistical methods 615 0$aQuality control$xStatistical methods. 615 0$aProcess control$xStatistical methods. 676 $a658.5/62 686 $aMAT029000$2bisacsh 700 $aRyan$b Thomas P.$f1945-$0522174 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910133222103321 996 $aStatistical methods for quality improvement$9835538 997 $aUNINA