MATLAB in quality assurance sciences
Author(s)
Bibliographic Information
MATLAB in quality assurance sciences
（Woodhead Publishing in mechanical engineering）
Woodhead, c2015
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
MATLAB (R) in Quality Assurance Sciences fills a gap in the highly topical field of quality assurance (QA). It is a compact guide for students, engineers, and scientists in this field. It concentrates on MATLAB (R) fundamentals with examples of application to a wide range of current problems from general, nano and bio-technology, and statistical control, to medicine and industrial management. Examples cover both the school and advanced level; comprising calculations of total quality management, six sigma, time series, process improvement, metrology, quality control, human factors in quality assurance, measurement and testing techniques, quality project and function management, and customer satisfaction.
This book covers key topics, including: the basics of software with examples; graphics and representations; numerical computation, scripts and functions for QA calculations; ODE and PDEPE solvers applied to QA problems; curve fitting and time series tool interfaces in calculations of quality; and statistics calculations applied to quality testing.
Table of Contents
Dedication
List of figures and tables
Preface
About the author
1: Introduction
Abstract
MATLAB (R) and other software
The purpose and principal audience for this book
About the topics
About chapter design and questions for self-checking
The MATLAB (R) versions
Order of presentation
2: Basics
Abstract
2.1 Starting with MATLAB (R) software
2.2 Vectors, matrices, and arrays
2.3 Flow control
2.4 Questions for self-checking
2.5 Answers to selected questions
3: MATLAB (R) graphics
Abstract
3.1 Generation of XY plots
3.2 Generation of XYZ plots
3.3 Specialized two- and three-dimensional plots
3.4 Application examples
3.5 Questions for self-checking
3.6 Answers to selected questions
4: Commands for probability distributions, random numbers, and special graphs
Abstract
4.1 Density, cumulative, and inverse cumulative functions for probability distributions
4.2 Command for random number generation
4.3 Supplementary commands for random numbers and probability distributions
4.4 Application examples
4.5 Specialized commands for graphical representation
4.6 Application examples
4.7 Questions for self-checking
4.8 Answers to selected questions
5: Script, function files, and some useful MATLAB (R) functions
Abstract
5.1 Script file
5.2 Functions and function files
5.3 Some useful MATLAB (R) functions
5.4 Application examples
5.5 Questions for self-checking
5.6 Answers to selected questions
6: Hypothesis tests
Abstract
6.1 Hypothesis testing outlines
6.2 The t-test with the ttest command
6.3 Wilcoxon rank sum test
6.4 Sample size and power of test
6.5 Supplementary commands for the hypothesis tests
6.6 Application examples
6.7 Questions for self-checking
6.8 Answers to selected questions
7: Ordinary differential equations and tools for their solution
Abstract
7.1 The ODE solvers for solving ordinary differential equations
7.2 Numerical methods and the ODE solvers
7.3 The ODE solver command forms and steps for their solution
7.4 Additional forms of the ODE solver commands
7.5 Application examples
7.6 Questions for self-checking
7.7 Answers to selected questions
Appendix: MATLAB (R) characters, operators, and commands
Index
by "Nielsen BookData"