{"product_id":"statistical-methods-for-six-sigma-in-r-d-and-manufacturing-hardback-9780471203421","title":"Statistical Methods for Six Sigma; In R\u0026D and Manufacturing (Hardback) 9780471203421","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eStatistical Methods for Six Sigma\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eIn R\u0026amp;D and Manufacturing\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eAnand M. Joglekar (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780471203421, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 7 October 2003\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e344 pages\u003cbr\u003e26.1 x 18.4 x 2.5 cm, 0.742 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\"I highly recommend this book to anyone interested in applying statistics to solve problems.\" (\u003ci\u003eJournal of Food Quality\u003c\/i\u003e, October 2004)  \u003cp\u003e\"…an interesting collection of material in nice summary form…\" (\u003ci\u003eJournal of the American Statistical Association\u003c\/i\u003e, December 2004)\u003c\/p\u003e \u003cp\u003e\"Overall, \u003ci\u003eStatistical Methods for Six Sigma in R \u0026amp; D and Manufacturing\u003c\/i\u003eoffers some good insights and practical views of the statistical concepts covered.\" (\u003ci\u003eTechnometrics\u003c\/i\u003e, August 2004, Vol. 46, No. 3)\u003c\/p\u003e \u003cp\u003e\"...covers a large number of useful statistical methods compactly...contains a wealth of case studies and examples...\" (\u003ci\u003eFood Trade Review\u003c\/i\u003e, May 2004)\u003c\/p\u003e \u003cp\u003e“...can be used as a reference or as a self-study...also as a textbook for an engineering statistics course...recommended...” (\u003ci\u003eE-Streams\u003c\/i\u003e, Vol. 7, No. 3)\u003c\/p\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eA guide to achieving business successes through statistical methods  \u003cp\u003eStatistical 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.\u003c\/p\u003e \u003cp\u003eWritten by a recognized educator in the field, Statistical Methods for Six Sigma: In R\u0026amp;D and Manufacturing is specifically geared to engineers, scientists, technical managers, and other technical professionals in industry. Emphasizing practical learning, applications, and performance improvement, Dr. Joglekar?s text shows today?s industry professionals how to:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eSummarize and interpret data to make decisions\u003c\/li\u003e \u003cli\u003eDetermine the amount of data to collect\u003c\/li\u003e \u003cli\u003eCompare product and process designs\u003c\/li\u003e \u003cli\u003eBuild equations relating inputs and outputs\u003c\/li\u003e \u003cli\u003eEstablish specifications and validate processes\u003c\/li\u003e \u003cli\u003eReduce risk and cost-of-process control\u003c\/li\u003e \u003cli\u003eQuantify and reduce economic loss due to variability\u003c\/li\u003e \u003cli\u003eEstimate process capability and plan process improvements\u003c\/li\u003e \u003cli\u003eIdentify key causes and their contributions to variability\u003c\/li\u003e \u003cli\u003eAnalyze and improve measurement systems\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThis long-awaited guide for students and professionals in research, development, quality, and manufacturing does not presume any prior knowledge of statistics. It covers a large number of useful statistical methods compactly, in a language and depth necessary to make successful applications. Statistical methods in this book include: variance components analysis, variance transmission analysis, risk-based control charts, capability and performance indices, quality planning, regression analysis, comparative experiments, descriptive statistics, sample size determination, confidence intervals, tolerance intervals, and measurement systems analysis. The book also contains a wealth of case studies and examples, and features a unique test to evaluate the reader?s understanding of the subject.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e1. Introduction.  \u003cp\u003e2. Basic Statistics.\u003c\/p\u003e \u003cp\u003e2.1 Descriptive Statistics.\u003c\/p\u003e \u003cp\u003e2.2 Statistical Distributions.\u003c\/p\u003e \u003cp\u003e2.3 Confidence Intervals.\u003c\/p\u003e \u003cp\u003e2.4 Sample Size.\u003c\/p\u003e \u003cp\u003e2.5  Tolerance Intervals.\u003c\/p\u003e \u003cp\u003e2.6 Normality, Independence and Homoscedasticity.\u003c\/p\u003e \u003cp\u003e3. Comparative Experiments and Regression Analysis.\u003c\/p\u003e \u003cp\u003e3.1 Hypothesis Testing Framework.\u003c\/p\u003e \u003cp\u003e3.2 Comparing Single Population.\u003c\/p\u003e \u003cp\u003e3.3 Comparing Two Populations.\u003c\/p\u003e \u003cp\u003e3.4 Comparing Multiple Populations.\u003c\/p\u003e \u003cp\u003e3.5 Correlation.\u003c\/p\u003e \u003cp\u003e3.6 Regression Analysis.\u003c\/p\u003e \u003cp\u003e4. Control Charts.\u003c\/p\u003e \u003cp\u003e4.1 Role of Control Charts.\u003c\/p\u003e \u003cp\u003e4.2 Logic of Control Limits.\u003c\/p\u003e \u003cp\u003e4.3 Variable Control Charts.\u003c\/p\u003e \u003cp\u003e4.4 Attribute Control Charts.\u003c\/p\u003e \u003cp\u003e4.5 Interpreting Control Charts.\u003c\/p\u003e \u003cp\u003e4.6 Key Success Factors.\u003c\/p\u003e \u003cp\u003e5. Process Capability.\u003c\/p\u003e \u003cp\u003e5.1 Capability and Performance Indices.\u003c\/p\u003e \u003cp\u003e5.2 E stimating Capability and Performance Indices.\u003c\/p\u003e \u003cp\u003e5.3 Six-Sigma Goal.\u003c\/p\u003e \u003cp\u003e5.4 Planning for Improvement.\u003c\/p\u003e \u003cp\u003e6. Other Useful Charts.\u003c\/p\u003e \u003cp\u003e6.1 Risk-based Control Ch arts.\u003c\/p\u003e \u003cp\u003e6.2 Modified Control Limit   Chart.\u003c\/p\u003e \u003cp\u003e6.3 Moving Average Control Chart.\u003c\/p\u003e \u003cp\u003e6.4 Short Run Control Charts\u003c\/p\u003e \u003cp\u003e6.5 Charts for Non-Normal Distributions.\u003c\/p\u003e \u003cp\u003e7. Variance Components Analysis.\u003c\/p\u003e \u003cp\u003e7.1   Chart (Random Factor).\u003c\/p\u003e \u003cp\u003e7.2 One-way Classification (Fixed Factor).\u003c\/p\u003e \u003cp\u003e7.3 Structured Studies and Variance Components.\u003c\/p\u003e \u003cp\u003e8. Quality Planning with Variance Components.\u003c\/p\u003e \u003cp\u003e8.1 Typical Manufacturing Application.\u003c\/p\u003e \u003cp\u003e8.2 Economic Loss Functions.\u003c\/p\u003e \u003cp\u003e8.3 Planning for Quality Improvement.\u003c\/p\u003e \u003cp\u003e8.4 Application to Multi-Lane Manufacturing Process.\u003c\/p\u003e \u003cp\u003e8.5 Variance Transmission Analysis.\u003c\/p\u003e \u003cp\u003e8.6 Application to a Factorial Design.\u003c\/p\u003e \u003cp\u003e8.7 Variance Components and Specifications.\u003c\/p\u003e \u003cp\u003e9. Measurement Systems Analysis.\u003c\/p\u003e \u003cp\u003e9.1 Statistical Properties of Measurement Systems.\u003c\/p\u003e \u003cp\u003e9.2 Acceptance Criteria.\u003c\/p\u003e \u003cp\u003e9.3 Calibration Study.\u003c\/p\u003e \u003cp\u003e9.4 Stability and Bias Study.\u003c\/p\u003e \u003cp\u003e9.5 Repeatability and Reproducibility (R\u0026amp;R) Study.\u003c\/p\u003e \u003cp\u003e9.6 Robustness and Intermediate Precision Studies.\u003c\/p\u003e \u003cp\u003e9.7 Linearity Study.\u003c\/p\u003e \u003cp\u003e9.8 Method Transfer Study.\u003c\/p\u003e \u003cp\u003e9.9 Calculating Significant Figures.\u003c\/p\u003e \u003cp\u003e10. What Color is Your Belt?\u003c\/p\u003e \u003cp\u003e10.1 Test.\u003c\/p\u003e \u003cp\u003e10.2 Answers.\u003c\/p\u003e \u003cp\u003eAppendix A: Tail Area of Unit Normal Distribution.\u003c\/p\u003e \u003cp\u003eAppendix B: Probability Points of the \u003ci\u003et\u003c\/i\u003e Distribution with \u003ci\u003ev\u003c\/i\u003e Degrees of Freedom.\u003c\/p\u003e \u003cp\u003eAppendix C: Probability Points of the \u003ci\u003ex\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e Distribution with \u003ci\u003ev\u003c\/i\u003e Degrees of Freedom.\u003c\/p\u003e \u003cp\u003eAppendix D1.\u003ci\u003ek \u003c\/i\u003e Values for Two-Sided Normal Tolerance Limits.\u003c\/p\u003e \u003cp\u003eAppendix D2.\u003ci\u003ek \u003c\/i\u003e Values for One-Sided Normal Tolerance Limits.\u003c\/p\u003e \u003cp\u003eAppendix E1: Percentage Points of the \u003ci\u003eF\u003c\/i\u003e Distribution: Upper 5% Points.\u003c\/p\u003e \u003cp\u003eAppendix E2: Percentage Points of the \u003ci\u003eF\u003c\/i\u003e Distribution: Upper 2.5% Points.\u003c\/p\u003e \u003cp\u003eAppendix F: Critical Values of Hartley's Maximum F Ratio Test for Homogeneity of Variances.\u003c\/p\u003e \u003cp\u003eAppendix G: Table of Control Chart Constants.\u003c\/p\u003e \u003cp\u003eGlossary Of Symbols.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Chemistry [\u003ca title=\"See our other books on Chemistry\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Chemistry%20%5BPN%5D%22\"\u003ePN\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Interscience","offers":[{"title":"Brand New","offer_id":52286308155672,"sku":"9780471203421","price":112.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780471203421.jpg?v=1781549528","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/statistical-methods-for-six-sigma-in-r-d-and-manufacturing-hardback-9780471203421","provider":"Freshly Printed Books","version":"1.0","type":"link"}