Rövid leírás:
An invaluable self-teaching guide on Statistical Process Control (SPC)–the use of statistical techniques to measure and improve the quality of processes
Több
Hosszú leírás:
Monitor and improve quality quickly and easily
Here is an invaluable self-teaching guide for anyone struggling to understand Statistical Process Control (SPC)–the use of statistical techniques to measure and improve the quality of processes. Statistical Process Control Demystified explains QC 7 tools, estimation, hypothesis testing, control charts, simple linear regression, two-level factorial design, and the analysis of variance.
Professionals in manufacturing, sales, marketing, finance, service, or public sectors who are looking to improve performance, products, and services by analyzing their machine and process capabilities will benefit from this book. Free access to the authors' proprietary eZ SPC software is included.
Monitor and improve quality quickly and easily
Here is an invaluable self-teaching guide for anyone struggling to understand Statistical Process Control (SPC)–the use of statistical techniques to measure and improve the quality of processes. Statistical Process Control Demystified explains QC 7 tools, estimation, hypothesis testing, control charts, simple linear regression, two-level factorial design, and the analysis of variance.
Professionals in manufacturing, sales, marketing, finance, service, or public sectors who are looking to improve performance, products, and services by analyzing their machine and process capabilities will benefit from this book. Free access to the authors' proprietary eZ SPC software is included.
Több
Tartalomjegyzék:
1: Introduction to Importance of Quality Improvement
2: Data Analysis
–Descriptive Statistics
–Graphical Analysis
–Statistical Analysis
3: Control Chart
–Variable Control Chart
–Attribute Control Chart
–Special Control Chart
4: Simple Linear Regression
–Correlation Analysis
–Simple Linear Regression Analysis
5: Design of Experiments
–One-Way Analysis of Variance
–Two-Way Analysis of Variance
–Two-level Factorial Design Analysis
