Industrial Statistics with Minitab; Contents; Preface; Part OneINTRODUCTION ANDGRAPHICALTECHNIQUES; 1 A First Look; 1.1 Initial Screen; 1.2 Entering Data; 1.3 Saving Data: Worksheets and Projects; 1.4 Data Operations: An Introduction; 1.5 Deleting and Inserting Columns and Rows; 1.6 First Statistical Analyses; 1.7 Getting Help; 1.7.1 The Main Help Menu; 1.7.2 Contextual Help; 1.7.3 StatGuideTM; 1.8 Personal Configuration; 1.9 Assistant; 1.10 Any Difficulties?; 2 Graphics for Univariate Data; 2.1 File 'PULSE'; 2.2 Histograms; 2.3 Changing the Appearance of Histograms
2.3.1 Changes in the Scale of the Horizontal Axis2.3.2 Changes in the Vertical Axis; 2.3.3 Appearance of the Bars; 2.3.4 Defining Intervals on which Bars are Located; 2.3.5 Appearance of the GraphWindow; 2.3.6 Changes in the Proportions of a Graph; 2.4 Histograms for Various Data Sets; 2.5 Dotplots; 2.6 Boxplots; 2.7 Bar Diagrams Count; 2.8 Pie Charts; 2.9 Updating Graphs Automatically; 2.10 Adding Text or Figures to a Graph; 3 Pareto Charts and Cause-Effect Diagrams; 3.1 File 'DETERGENT'; 3.2 Pareto Charts; 3.2.1 Changing Appearance of Pareto Charts; 3.3 Cause-and-Effect Diagrams
4 Scatterplots4.1 File 'Pulse'; 4.2 Stratification; 4.3 Identifying Points on a Graph; 4.4 Using the 'Crosshairs' Option; 4.5 Scatterplots with Panels; 4.6 Scatterplots with Marginal Graphs; 4.7 Creating an Array of Scatterplots; 4.7.1 Square Matrix; 4.7.2 Matrix Created Selecting a Subset of Variables; 5 Three Dimensional Plots; 5.1 3D Scatterplots; 5.1.1 Stratification; 5.2 3D Surface Plots; 5.3 Contour Plots; 5.3.1 Contour Plot Options; 6 Part One: Case Studies Introduction and Graphical Techniques; 6.1 Cork; 6.2 Copper; 6.3 Bread; 6.4 Humidity
Part Two HYPOTHESIS TESTING. COMPARISON OF TREATMENTS7 Random Numbers and Numbers Following a Pattern; 7.1 Introducing Values Following a Pattern; 7.2 Sampling Random Data from a Column; 7.3 Random Number Generation; 7.4 Example: Solving a Problem Using Random Numbers; 8 Computing Probabilities; 8.1 Probability Distributions; 8.2 Option 'Probability Density' or 'Probability'; 8.3 Option 'Cumulative Probability'; 8.4 Option 'Inverse Cumulative Probability'; 8.5 Viewing the Shape of the Distributions
8.6 Equivalence between Sigmas of the Process and Defects per Million Parts Using 'Cumulative Probability'9 Hypothesis Testing for Means and Proportions. Normality Test; 9.1 Hypothesis Testing for One Mean; 9.1.1 Case 1: Known Population Standard Deviation; 9.1.2 Case 2: Unknown Population Standard Deviation (Estimated from the Sample Data); 9.2 Hypothesis Testing and Confidence Interval for a Proportion; 9.3 Normality Test; 10 Comparison of Two Means, Two Variances or Two Proportions; 10.1 Comparison of Two Means; 10.1.1 Case 1: Independent Samples; 10.1.2 Case 2: Paired Data
Summary
"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."-- Provided by publisher
Notes
Includes index
Print version record and CIP data provided by publisher
