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.
Autorentext
Pere Grima, Professor, Department of the Technical University of Catalonia UPC, Barcelona, Spain.
Lluis Marco, Assistant Professor, Department of the Technical University of Catalonia UPC, Barcelona, Spain.
Xavier Tort-Martorell, Department Director Statistics Department,the Technical University of Catalonia UPC, Barcelona, Spain. Xavier Tort-Martorell is president elect of ENBIS
The authors possess a wide experience both in training and consulting. They have designed and delivered courses in various universities and at all levels, from undergraduate to postgraduate and professional training. Their activities have always been strongly linked to the business and industrial world. Most recently with a high focus on Six Sigma training and consulting they have certified more than 450 Black Belts in Spain and Latin America- . They have also advised many companies from different sectors on the implementation of quality improvement programs and the proper use of statistical methods. Among others: Hewlett-Packard, Samsung electronics, Alstom Transport, Siemens VDO, BBVA, Procter & Gamble and ITP.
Klappentext
Industrial Statistics with Minitab Pere Grima Cintas, Lluís Marco Almagro, Xavier Tort-Martorell Llabrés Universitat Politècnica de Catalunya - BarcelonaTech, Barcelona, Spain
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 visualisation, 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. This book can also be used as quick reference enabling the reader to be confident enough to explore other Minitab capabilities.
Zusammenfassung
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.
Inhalt
Preface xiii
Part One Introduction and Graphical Techniques 1
1 A First Look 3
1.1 Initial Screen 3
1.2 Entering Data 4
1.3 Saving Data: Worksheets and Projects 5
1.4 Data Operations: An Introduction 5
1.5 Deleting and Inserting Columns and Rows 7
1.6 First Statistical Analyses 8
1.7 Getting Help 10
1.8 Personal Configuration 12
1.9 Assistant 13
1.10 Any Difficulties? 14
2 Graphics for Univariate Data 15
2.1 File 'PULSE' 15
2.2 Histograms 16
2.3 Changing the Appearance of Histograms 17
2.4 Histograms for Various Data Sets 21
2.5 Dotplots 23
2.6 Boxplots 24
2.7 Bar Diagrams 25
2.8 Pie Charts 27
2.9 Updating Graphs Automatically 28
2.10 Adding Text or Figures to a Graph 29
3 Pareto Charts and Cause-Effect Diagrams 31
3.1 File 'DETERGENT' 31
3.2 Pareto Charts 32
3.4 Cause-and-Effect Diagrams 35
4 Scatterplots 37
4.1 File 'pulse' 37
4.2 Stratification 38
4.3 Identifying Points on a Graph 39
4.4 Using the 'Crosshairs' Option 45
4.5 Scatterplots with Panels 46
4.6 Scatterplots with Marginal Graphs 48
4.7 Creating an Array of Scatterplots 50
5 Three Dimensional Plots 52
5.1 3D Scatterplots 52
5.2 3D Surface Plots 55
5.3 Contour Plots 58
6 Part One: Case Studies - Introduction and Graphical Techniques 62
6.1 Cork 62
6.2 Copper 68
6.3 Bread 73
6.4 Humidity 76
Part Two Hypothesis Testing. Comparison of Treatments 79
7 Random Numbers and Numbers Following a Pattern 81
7.1 Introducing Values Following a Pattern 81
7.2 Sampling Random Data from a Column 83
7.3 Random Number Generation 83
7.4 Example: Solving a Problem Using Random Numbers 85
8 Computing Probabilities 87
8.1 Probability Distributions 87
8.2 Option 'Probability Density' or 'Probability' 88
8.3 Option 'Cumulative Probability' 89
8.4 Option 'Inverse Cumulative Probability' 89
8.5 Viewing the Shape of the Distributions 92
8.6 Equivalence between Sigmas of the Process and Defects per Millio…