LEADER 01325nam0 2200337 i 450 001 CFI0511777 005 20231121125454.0 010 $a8821424839 100 $a20150824d2001 ||||0itac50 ba 101 | $aita 102 $ait 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aPsicoterapie integrate$epiani di trattamento per psicoterapeuti, con interventi a breve, medio e lungo termine$fEdoardo Giusti, Claudia Montanari, Antonio Iannazzo 205 $aRist. riv. e corr 210 $aMilano$cMasson$d2001 215 $aXIII, 535 p.$d24 cm 300 $aSegue: Appendici. 606 $aPsicoterapia$2FIR$3RMLC002701$9I 700 1$aGiusti$b, Edoardo$3CFIV012947$4070$0154077 701 1$aMontanari$b, Claudia$f <1953- >$3RAVV092359$4070$01440320 701 1$aIannazzo$b, Antonio$3UMCV043992$4070$0542160 790 1$aMontanari$b, Claudia$c $3CFIV189803$zMontanari, Claudia <1953- > 801 3$aIT$bIT-01$c20150824 850 $aIT-FR0017 899 $aBiblioteca umanistica Giorgio Aprea$bFR0017 $eN 912 $aCFI0511777 950 0$aBiblioteca umanistica Giorgio Aprea$d 52MAG 10/151$e 52FSS0000073095 VMN RS $fA $h20180521$i20180521 977 $a 52 996 $aPsicoterapie integrate$93606128 997 $aUNICAS LEADER 05424nam 22006854a 450 001 9911018919103321 005 20200520144314.0 010 $a9786610367696 010 $a9781280367694 010 $a1280367695 010 $a9780470248041 010 $a0470248041 010 $a9780471465379 010 $a0471465372 010 $a9780471721215 010 $a0471721212 035 $a(CKB)111087027111040 035 $a(EBL)231738 035 $a(OCoLC)56576084 035 $a(SSID)ssj0000251090 035 $a(PQKBManifestationID)11237319 035 $a(PQKBTitleCode)TC0000251090 035 $a(PQKBWorkID)10248046 035 $a(PQKB)11121234 035 $a(MiAaPQ)EBC231738 035 $a(Perlego)2776445 035 $a(EXLCZ)99111087027111040 100 $a20030224d2003 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistical methods for six sigma $ein R&D and manufacturing /$fAnand M. Joglekar 210 $aHoboken, NJ $cWiley-Interscience$d2003 215 $a1 online resource (339 p.) 300 $aDescription based upon print version of record. 311 08$a9780471203421 311 08$a0471203424 320 $aIncludes bibliographical references (p. 317-318) and index. 327 $aStatistical Methods for Six Sigma; Contents; Preface; 1 Introduction; 2 Basic Statistics; 2.1 Descriptive Statistics; 2.1.1 Measures of Central Tendency; 2.1.2 Measures of Variability; 2.1.3 Histogram; 2.2 Statistical Distributions; 2.2.1 Normal Distribution; 2.2.2 Binomial Distribution; 2.2.3 Poisson Distribution; 2.3 Confidence Intervals; 2.3.1 Confidence Interval for m; 2.3.2 Confidence Interval for s; 2.3.3 Confidence Interval for p and l; 2.4 Sample Size; 2.4.1 Sample Size to Estimate m; 2.4.2 Sample Size to Estimate s; 2.4.3 Sample Size to Estimate p and l; 2.5 Tolerance Intervals 327 $a2.6 Normality, Independence, and Homoscedasticity2.6.1 Normality; 2.6.2 Independence; 2.6.3 Homoscedasticity; 3 Comparative Experiments and Regression Analysis; 3.1 Hypothesis Testing Framework; 3.2 Comparing Single Population; 3.2.1 Comparing Mean (Variance Known); 3.2.2 Comparing Mean (Variance Unknown); 3.2.3 Comparing Standard Deviation; 3.2.4 Comparing Proportion; 3.3 Comparing Two Populations; 3.3.1 Comparing Two Means (Variance Known); 3.3.2 Comparing Two Means (Variance Unknown but Equal); 3.3.3 Comparing Two Means (Variance Unknown and Unequal) 327 $a3.3.4 Comparing Two Means (Paired t-test)3.3.5 Comparing Two Standard Deviations; 3.3.6 Comparing Two Proportions; 3.4 Comparing Multiple Populations; 3.4.1 Completely Randomized Design; 3.4.2 Randomized Block Design; 3.4.3 Multiple Comparison Procedures; 3.4.4 Comparing Multiple Standard Deviations; 3.5 Correlation; 3.5.1 Scatter Diagram; 3.5.2 Correlation Coefficient; 3.6 Regression Analysis; 3.6.1 Fitting Equations to Data; 3.6.2 Accelerated Stability Tests; 4 Control Charts; 4.1 Role of Control Charts; 4.2 Logic of Control Limits; 4.3 Variable Control Charts 327 $a4.3.1 Average and Range Charts4.3.2 Average and Standard Deviation Charts; 4.3.3 Individual and Moving Range Charts; 4.4 Attribute Control Charts; 4.4.1 Fraction Defective (p) Chart; 4.4.2 Defects per Product (u) Chart; 4.5 Interpreting Control Charts; 4.5.1 Tests for the Chart of Averages; 4.5.2 Tests for Other Charts; 4.6 Key Success Factors; 5 Process Capability; 5.1 Capability and Performance Indices; 5.1.1 C(p) Index; 5.1.2 C(pk) Index; 5.1.3 P(p) Index; 5.1.4 P(pk) Index; 5.1.5 Relationships between C(p), C(pk), P(p), and P(pk); 5.2 Estimating Capability and Performance Indices 327 $a5.2.1 Point Estimates for Capability and Performance Indices5.2.2 Confidence Intervals for Capability and Performance Indices; 5.2.3 Connection with Tolerance Intervals; 5.3 Six-Sigma Goal; 5.4 Planning for Improvement; 6 Other Useful Charts; 6.1 Risk-based Control Charts; 6.1.1 Control Limits, Subgroup Size, and Risks; 6.1.2 Risk-Based X Chart; 6.1.3 Risk-Based Attribute Charts; 6.2 Modified Control Limit X Chart; 6.2.1 Chart Design; 6.2.2 Required Minimum C(pk); 6.3 Moving Average Control Chart; 6.4 Short-Run Control Charts; 6.4.1 Short-Run Individual and Moving Range Charts 327 $a6.4.2 Short-Run Average and Range Charts 330 $aA guide to achieving business successes through statistical methods Statistical methods are a key ingredient in providing data-based guidance to research and development as well as to manufacturing. Understanding the concepts and specific steps involved in each statistical method is critical for achieving consistent and on-target performance. Written by a recognized educator in the field, Statistical Methods for Six Sigma: In R&D and Manufacturing is specifically geared to engineers, scientists, technical managers, and other technical professionals in industry. Emphasizing practical learni 606 $aQuality control$xStatistical methods 606 $aProcess control$xStatistical methods 615 0$aQuality control$xStatistical methods. 615 0$aProcess control$xStatistical methods. 676 $a658.5/62 700 $aJoglekar$b Anand M$0289808 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911018919103321 996 $aStatistical methods for six sigma$9754055 997 $aUNINA