![minitab statistics minitab statistics](https://online.stat.psu.edu/stat415/sites/stat415/files//lesson35/Less35_Minitab11.gif)
14.8 A More Detailed Data Analysis (Capability Sixpack).14.7 Capability Study when the Sample Size Is Equal to One.14.6 ‘Within’ Variability and ‘Overall’ Variability.14.4 Interpreting the Obtained Information.14.3 Capability Analysis (Normal Distribution).14.1 Capability Analysis: Available Options.13.8 Calibration and Linearity Study of the Measurement System.13.6 Gage R&R Study for the Data in File ‘RR_NESTED’.13.4 R&R Study for the Data in File ‘RR_CROSSED’.13.1 Crossed Designs and Nested Designs.Part Three: Measurement Systems Studies And Capability Studies.Chapter 11: Comparison of More than Two Means: Analysis of Variance.Chapter 10: Comparison of Two Means, Two Variances or Two Proportions.9.2 Hypothesis Testing and Confidence Interval for a Proportion.Chapter 9: Hypothesis Testing for Means and Proportions.8.6 Equivalence between Sigmas of the Process and Defects per Million Parts Using ‘Cumulative Probability’.8.5 Viewing the Shape of the Distributions.8.4 Option ‘Inverse Cumulative Probability’.8.2 Option ‘Probability Density’ or ‘Probability’.7.4 Example: Solving a Problem Using Random Numbers.7.1 Introducing Values Following a Pattern.Chapter 7: Random Numbers and Numbers Following a Pattern.Chapter 3: Pareto Charts and Cause–Effect Diagrams.2.3 Changing the Appearance of Histograms.Chapter 2: Graphics for Univariate Data.1.5 Deleting and Inserting Columns and Rows.1.3 Saving Data: Worksheets and Projects.Part One: Introduction And Graphical Techniques.The book can also be used as quick reference enabling the reader to be confident enough to explore other MINITAB capabilities. Six Sigma Green Belts and Black Belts will find explanations and examples of the most relevant techniques in DMAIC projects. Is supported by an accompanying website featuring case studies and the corresponding datasets. Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.Įxplores statistical techniques and how they can be used effectively with the help of MINITAB 16.Ĭontains extensive illustrative examples and case studies throughout and assumes no previous statistical knowledge.Įmphasises data graphics and visualization, and the most used industrial statistical tools, such as Statistical Process Control and Design of Experiments. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented.
![minitab statistics minitab statistics](https://i.ytimg.com/vi/beXbdlAUxkg/maxresdefault.jpg)
This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context.