Industrial Statistics with Minitab

✍ Scribed by Pere Grima Cintas, Lluis Marco Almagro, Xavier Tort?Martorell Llabres(auth.)

• Year: 2012
• Tongue: English
• Leaves: 413
• Category: Library

✦ Synopsis

Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented.

Industrial Statistics with MINITAB:

• Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.
• Explores statistical techniques and how they can be used effectively with the help of MINITAB 16.
• Contains extensive illustrative examples and case studies throughout and assumes no previous statistical knowledge.
• Emphasises data graphics and visualization, and the most used industrial statistical tools, such as Statistical Process Control and Design of Experiments.
• Is supported by an accompanying website featuring case studies and the corresponding datasets.

Six Sigma Green Belts and Black Belts will find explanations and examples of the most relevant techniques in DMAIC projects. The book can also be used as quick reference enabling the reader to be confident enough to explore other MINITAB capabilities.

Content:
Chapter 1 A First Look (pages 3–14):
Chapter 2 Graphics for Univariate Data (pages 15–30):
Chapter 3 Pareto Charts and Cause–Effect Diagrams (pages 31–36):
Chapter 4 Scatterplots (pages 37–51):
Chapter 5 Three Dimensional Plots (pages 52–61):
Chapter 6 Part One: Case Studies (pages 62–78):
Chapter 7 Random Numbers and Numbers Following a Pattern (pages 81–86):
Chapter 8 Computing Probabilities (pages 87–94):
Chapter 9 Hypothesis Testing for Means and Proportions. Normality Test (pages 95–102):
Chapter 10 Comparison of Two Means, Two Variances or Two Proportions (pages 103–109):
Chapter 11 Comparison of More than Two Means: Analysis of Variance (pages 110–119):
Chapter 12 Part Two: Case Studies (pages 120–135):
Chapter 13 Measurement System Study (pages 139–150):
Chapter 14 Capability Studies (pages 151–162):
Chapter 15 Capability Studies for Attributes (pages 163–167):
Chapter 16 Part Three: Case Studies (pages 168–180):
Chapter 17 Multi?Vari Charts (pages 183–187):
Chapter 18 Control Charts I: Individual Observations (pages 188–197):
Chapter 19 Control Charts II: Means and Ranges (pages 198–203):
Chapter 20 Control Charts for Attributes (pages 204–211):
Chapter 21 Part Four: Case Studies (pages 212–229):
Chapter 22 Correlation and Simple Regression (pages 235–246):
Chapter 23 Multiple Regression (pages 247–255):
Chapter 24 Multivariate Analysis (pages 256–271):
Chapter 25 Part Five: Case Studies (pages 272–292):
Chapter 26 Factorial Designs: Creation (pages 295–302):
Chapter 27 Factorial Designs: Analysis (pages 303–312):
Chapter 28 Response Surface Methodology (pages 313–324):
Chapter 29 Reliability (pages 325–334):
Chapter 30 Part Six: Case Studies (pages 335–370):