Minitab Demystified

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Get started using Minitab right way with help from this hands-on guide. Minitab Demystified walks you through essential Minitab features and shows you how to apply them to solve statistical analysis problems.

Featuring coverage of Minitab 16, this practical guide explores the Minitab interface and the full range of Minitab graphics, Distribution models, statistical intervals, hypothesis testing, and sample size calculations are clearly explained. The book covers modeling tools of regression and the design of experiments (DOE) as well as the industrial quality tools of measurement systems analysis, control charts, capability analysis, acceptance sampling, and reliability analysis. Detailed examples and concise explanations make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce key concepts.

It's a no-brainer! You'll learn about:

• Accessing powerful Minitab functions with the Minitab assistant
• Confidence, prediction, and tolerance intervals
• Designing and analyzing experiments with hard-to-change variables
• Statistical process control (SPC), Six Sigma applications, and quality control
• Predicting the economic impact of sampling
• Analyzing life data with additional variables

Simple enough for a beginner, challenging enough for an advanced student, and thorough enough for a Six Sigma professional, Minitab Demystified is your shortcut to statistical analysis success!

Author: Andrew Sleeper
Publisher: McGraw-Hill Companies
Published: 08/31/2011
Pages: 576
Binding Type: Paperback
Weight: 1.65lbs
Size: 9.23h x 7.34w x 1.07d
ISBN: 9780071762298

About the Author

Andrew Sleeper is a statistical consultant and trainer who has headed his own company since 2002. His industrial career includes work as a design engineer, reliability engineer, project manager, and Six Sigma Black Belt. Sleeper has presented numerous papers and articles on statistical tools in the quality industry. He is the author of two statistical tools books by McGraw-Hill, Design for Six Sigma Statistics, and Six Sigma Distribution Modeling.

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