A01=D.H. Stamatis
advanced industrial quality statistics
Author_D.H. Stamatis
Bernoulli Trials
Canonical Correlation
Category=KJMV5
Category=PBT
Cross-tabulation Table
data analysis techniques
Data Set
Dependent Variable
deviation
Discriminant Analysis
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
error
failure rate analysis
FREQUENCY Command
Frequency Table
Hold
Hotelling's T2
Hotelling’s T2
hypothesis
hypothesis testing methods
Identification Number
iii
Independent Groups
Independent Variable
KOLMOGOROV SMIRNOV Test
mean
Monte Carlo Optimization
Multiple Comparison Procedures
Multiple Independent Variables
Multivariate Data Reduction
normal
Null Hypothesis
Observed Significance Level
Payoff Matrix
Population Means
process optimization
regression modeling
sample
Sample Means
sampling strategies
Sign Test
standard
Standard Error
volume
Product details
- ISBN 9781574443127
- Dimensions: 156 x 234mm
- Publication Date: 28 Aug 2002
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
Secure
checkout
Fast Shipping
Easy returns
Researchers and professionals in all walks of life need to use the many tools offered by the statistical world, but often do not have the necessary experience in both concept and application. No matter what your profession, sooner or later numbers need to be crunched, and often you need to understand how to do it, and why it is important. Quality control is no different. Six Sigma and Beyond: Statistics and Probability covers the concepts of some useful statistical tools, appropriate formulae for specific tools, the connection of statistics to probability, and how to use them.
This volume introduces the relationship of statistics, probability, and reliability as they apply to quality in general and to Six Sigma in particular. The author brings the theoretical into the practical by providing statistical techniques, tests, and methods that the reader can use in any organization. He reviews basic parametric and non-parametric statistics, probability concepts and applications, and addresses topics for both measurable and attribute characteristics. He delineates the importance of collecting, analyzing, and interpreting data not from an academic point of view but from a practical perspective.
This is not a textbook but a guide for anyone interested in statistical, probability, and reliability to improve processes and profitability in their organizations. When you begin a study of something, you want to do it well. You want to design a good study, analyze the results properly, and prepare a cogent report that summarizes what you've found. Six Sigma and Beyond: Statistics and Probability shows you how to use statistical tools to improve your processes and give your organization the competitive edge.
