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| 008 | 230510s2015 xx o ||||0 eng d | |
| 020 | ▼a9783319240466▼q(electronic bk.) | |
| 020 | ▼z9783319240442 | |
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| 050 | ▼aT57.6-57.97 | |
| 082 | ▼a658.56202855133 | |
| 100 | ▼aCano, Emilio L. | |
| 245 | 00 | ▼aQuality Control with R :▼bAn ISO Standards Approach. |
| 264 | ▼aCham :▼bSpringer International Publishing AG,▼c2015. | |
| 264 | ▼c©2015. | |
| 300 | ▼a1 online resource (373 pages) | |
| 336 | ▼atext▼btxt▼2rdacontent | |
| 337 | ▼acomputer▼bc▼2rdamedia | |
| 338 | ▼aonline resource▼bcr▼2rdacarrier | |
| 490 | ▼aUse R! Series | |
| 505 | ▼aIntro -- Foreword -- Preface -- Why Quality Control with R? -- Who Is This Book For? -- How to Read This Book -- Conventions -- The Production -- Resources -- About the Authors -- Acknowledgments -- Contents -- List of Figures -- List of Tables -- Acronyms -- Part I Fundamentals -- 1 An Intuitive Introduction to Quality Control with R -- 1.1 Introduction -- 1.2 A Brief History of Quality Control -- 1.3 What Is Quality Control -- 1.4 The Power of R for Quality Control -- Software for Quality Control -- What Is R? -- Why R? -- How to Obtain R -- 1.5 An Intuitive Example -- 1.6 A Roadmap to Getting Started with R for Quality Control -- Download R -- Install R -- Download RStudio -- Install RStudio -- Start RStudio -- Install the qcc Package -- Select and Set Your Working Directory (Optional) -- Create Your First Script -- Run Your Script -- Make a Reproducible Report (Optional) -- 1.7 Conclusions and Further Steps -- References -- 2 An Introduction to R for Quality Control -- 2.1 Introduction -- 2.2 R Interfaces -- 2.3 R Expressions -- 2.4 R Infrastructure -- 2.5 Introduction to RStudio -- The R(Studio) Console -- The Source Editor -- The R Graphical Output -- The R Commands History -- The R Workspace -- The Working Directory -- Packages -- R and RStudio Help -- 2.6 Working with Data in R -- Data Structures -- Classes and Data Types -- Vectors -- Creating Vectors -- Vectors and Factors -- Lengths and Names -- Accessing Vector Items -- Ordering Vectors -- Operating with Vectors -- Matrices -- Creating and Accessing Matrices -- Basic Matrix Operations -- Lists -- Creating Lists -- Accessing Lists -- Data Frames -- Creating Data Frames -- Accessing Data Frames -- Ordering, Filtering, and Aggregating Data Frames -- Editing Data Frames -- Special Data Values -- Missing Values -- Other Special Values in R -- Data Types Conversion -- Working with Dates. | |
| 505 | ▼a2.7 Data Import and Export with R -- Importing .csv Files -- Importing Data from Text Files -- Data Cleaning -- Exploratory Data Analysis -- Missing Values -- Outliers -- Wrong Values -- Exporting Data from R -- Importing Data from Other Sources -- 2.8 R Task View for Quality Control (Unofficial) -- Modeling Quality -- Visualizing Quality -- Control Charts -- Capability Analysis -- Acceptance Sampling -- Design of Experiments -- Quality Control Reports -- CRAN Packages -- Books -- Links -- 2.9 ISO Standards and R -- ISO Standards and Data -- R Certification -- References -- 3 The Seven Quality Control Tools in a Nutshell: R and ISO Approaches -- 3.1 Origin -- 3.2 Cause-and-Effect Diagram -- 3.3 Check Sheet -- 3.4 Control Chart -- 3.5 Histogram -- 3.6 Pareto Chart -- 3.7 Scatter Plot -- 3.8 Stratification -- 3.9 ISO Standards for the Seven Basic Quality Control Tools -- References -- 4 R and the ISO Standards for Quality Control -- 4.1 ISO Members and Technical Committees -- 4.2 ISO Standards and Quality -- 4.3 The ISO Standards Development Process -- 4.4 ISO TC69 Secretariat -- 4.5 ISO TC69/SC1: Terminology -- 4.6 ISO TC69/SC4: Application of Statistical Methods in Process Management -- 4.7 ISO TC69/SC5: Acceptance Sampling -- 4.8 ISO TC69/SC6: Measurement Methods and Results -- 4.9 ISO TC69/SC7: Applications of Statistical and Related Techniques… -- 4.10 ISO TC69/SC8: Application of Statistical and Related Methodology for New Technology and Product Development -- 4.11 The Role of R in Standards -- References -- Part II Statistics for Quality Control -- 5 Modelling Quality with R -- 5.1 The Description of Variability -- 5.1.1 Background -- 5.1.2 Graphical Description of Variation -- 5.1.2.1 Histogram -- 5.1.2.2 Run Chart -- 5.1.2.3 Other Important Charts in Quality Control -- 5.1.3 Numerical Description of Variation -- 5.1.3.1 Central Tendency. | |
| 505 | ▼a5.1.3.2 Variability -- 5.1.3.3 Frequency Tables -- 5.2 Probability Distributions -- 5.2.1 Discrete Distributions -- 5.2.1.1 Hypergeometric Distribution -- 5.2.1.2 Binomial Distribution -- 5.2.1.3 Poisson Distribution -- 5.2.2 Continuous Distributions -- 5.2.2.1 Normal Distribution -- 5.2.2.2 Other Important Continuous Distributions -- 5.2.2.3 Data Transformation -- 5.3 Inference About Distribution Parameters -- 5.3.1 Confidence Intervals -- 5.3.1.1 Sampling Distribution and Point Estimation -- 5.3.1.2 Proportion Confidence Interval -- 5.3.1.3 Mean Confidence Interval -- 5.3.1.4 Variance Confidence Interval -- 5.3.2 Hypothesis Testing -- 5.3.2.1 Means -- 5.3.2.2 Variances -- 5.3.2.3 Proportions -- 5.3.2.4 Normality -- 5.4 ISO Standards for Quality Modeling with R -- References -- 6 Data Sampling for Quality Control with R -- 6.1 The Importance of Sampling -- 6.2 Different Kinds of Sampling -- 6.2.1 Simple Random Sampling -- 6.2.2 Stratified Sampling -- 6.2.3 Cluster Sampling -- 6.2.4 Systematic Sampling -- 6.3 Sample Size, Test Power, and OC Curves with R -- 6.4 ISO Standards for Sampling with R -- References -- Part III Delimiting and Assessing Quality -- 7 Acceptance Sampling with R -- 7.1 Introduction -- 7.2 Sampling Plans for Attributes -- 7.3 Sampling Plans for Variables -- 7.4 ISO Standards for Acceptance Sampling and R -- References -- 8 Quality Specifications and Process Capability Analysis with R -- 8.1 Introduction -- 8.2 Tolerance Limits and Specifications Design -- 8.2.1 The Voice of the Customer -- 8.2.2 Process Tolerance -- 8.3 Capability Analysis -- 8.3.1 The Voice of the Process -- 8.3.2 Process Performance Indices -- 8.3.3 Capability Indices -- 8.4 ISO Standards for Capability Analysis and R -- References -- Part IV Control Charts -- 9 Control Charts with R -- 9.1 Introduction -- 9.1.1 The Elements of a Control Chart. | |
| 505 | ▼a9.1.2 Control Chart Design -- 9.1.3 Reading a Control Chart -- 9.2 Control Charts for Variables -- 9.2.1 Introduction -- 9.2.2 Estimation of σ for Control Charts -- 9.2.3 Control Charts for Grouped Data -- 9.2.3.1 Mean Chart (X-Bar Chart) -- 9.2.3.2 Range Chart (R Chart) -- 9.2.3.3 Standard Deviation Chart (S Chart) -- 9.2.4 Control Charts for Non-grouped Data -- 9.2.4.1 Individual Values Chart and Moving Range Chart -- 9.2.5 Special Control Charts -- 9.2.5.1 CUSUM Chart -- 9.2.5.2 EWMA Chart -- 9.3 Control Charts for Attributes -- 9.3.1 Introduction -- 9.3.2 Attributes Control Charts for Groups -- 9.3.2.1 The p Chart -- 9.3.2.2 The np Chart -- 9.3.3 Control Charts for Events -- 9.3.3.1 The c Chart -- 9.3.3.2 The u Chart -- 9.4 Control Chart Selection -- 9.5 ISO Standards for Control Charts -- References -- 10 Nonlinear Profiles with R -- 10.1 Introduction -- 10.2 Nonlinear Profiles Basics -- 10.3 Phase I and Phase II Analysis -- 10.3.1 Phase I -- 10.3.2 Phase II -- 10.4 A Simple Profiles Control Chart -- 10.5 ISO Standards for Nonlinear Profiles and R -- References -- A Shewhart Constants for Control Charts -- B ISO Standards Published by the ISO/TC69: Application of Statistical Methods -- TC69/SCS: Secretariat -- TC69/SC1: Terminology and Symbols -- TC69/SC4: Applications of Statistical Methods in Process Management -- TC69/SC5: Acceptance Sampling -- TC69/SC6: Measurement Methods and Results -- TC69/SC7: Applications of Statistical and Related Techniques for the Implementation of Six Sigma -- TC69/SC8: Application of Statistical and Related Methodology for New Technology and Product Development -- C R Cheat Sheet for Quality Control -- R Console -- RStudio -- Help -- General -- Math Operators -- Integer Operations -- Comparison Functions -- Math Functions -- Vectors -- Matrices -- Factors -- Dates -- Character String -- Lists -- Data Frames. | |
| 505 | ▼aFiles -- Data Simulation -- Graphics -- Descriptive Statistics -- Acceptance Sampling -- Control Charts -- qcc Library -- Process Capability -- qcc Package -- SixSigma Package -- qualityTools Package -- Pareto Analysis -- qcc Package -- qualityTools Package -- SixSigma Package -- Probability -- Objects -- Vectorized Functions -- Programming -- Reports -- xtable Package -- Package knitr -- Useful Links -- R Packages and Functions Used in the Book -- ISO Standards Referenced in the Book -- Subject Index. | |
| 588 | ▼aDescription based on publisher supplied metadata and other sources. | |
| 590 | ▼aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2023. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. | |
| 650 | ▼aMathematical optimization. | |
| 655 | ▼aElectronic books. | |
| 700 | ▼aMartinez Moguerza, Javier. | |
| 700 | ▼aPrieto, Mariano. | |
| 776 | ▼iPrint version:▼aCano, Emilio L.▼tQuality Control with R▼dCham : Springer International Publishing AG,c2015▼z9783319240442 | |
| 797 | ▼aProQuest (Firm) | |
| 830 | ▼aUse R! Series | |
| 856 | ▼uhttps://ebookcentral.proquest.com/lib/dongakr/detail.action?docID=4099123▼zClick to View |
Quality Control with R :An ISO Standards Approach
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Quality Control with R :An ISO Standards Approach
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