Quality control with R : an ISO standards approach / Emilio L. Cano, Javier M. Moguerza and Mariano Prieto Corcoba.
Series: Use R!Publication details: Cham : Springer, 2015.Description: xxviii, 349 p. ; illustrations (some color)ISBN:- 9783319240442
- 000SA.055 23 C227
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.055 C227 (Browse shelf(Opens below)) | Available | 137117 |
Browsing ISI Library, Kolkata shelves Close shelf browser (Hides shelf browser)
| No cover image available | ||||||||
| 000SA.05=4 C397 Colloque sur l'analyse statistique | 000SA.055 Ad237 R in a nutshell : a desktop quick references / | 000SA.055 Ag284 Panel data analysis using eviews / | 000SA.055 C227 Quality control with R : | 000SA.055 C512 Computational statistics in the earth sciences : | 000SA.055 C911 Statistics : an introduction using R / | 000SA.055 C911 Statistics : an introduction using R / |
Includes bibliographical references and index.
1. An Intuitive Introduction to Quality Control with R --
2. An Introduction to R for Quality Control --
3. The Seven Quality Control Tools in a Nutshell: R and ISO Approaches --
4. R and ISO Standards for Quality Control --
5. Modeling Quality with R --
6. Data Sampling for Quality Control with R --
7. Acceptance Sampling with R --
8. Quality Specifications and Process Capability Analysis with R --
9. Control Charts with R --
10. Nonlinear Profiles with R.
Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control professionals and statisticians, examples throughout are structured to simplify complex equations and data structures, and to demonstrate their applications to quality control processes, such as ISO standards. The volume balances its treatment of key aspects of quality control, statistics, and programming in R, making the text accessible to beginners and expert quality control professionals alike. Several appendices serve as useful references for ISO standards and common tasks performed while applying quality control with R.
There are no comments on this title.
