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Preface
Part One Introduction: Graphical Techniques
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 An Introduction to Data Management: Delete and Insert
1.6 First Statistical Analyses
1.7 Getting Help
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
2.4 Histograms for Various Data Sets
2.5 Dotplots
2.6 Boxplots
2.7 Bar Diagrams
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
3.3 Changing Appearance of Pareto Charts
3.4 Cause-and-Effect Diagrams
4 Scatterplots
4.1 Scatterplots
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
5 Three Dimensional Plots
5.1 3D Scatterplots
5.2 Stratification
5.3 3D Surface Plots
5.4 Contour Plots
6 Part One Case Studies – Introduction: Graphical Techniques
6.1 Cork
6.2 Copper
6.3 Bread
6.4 Humidity
Part Two Hypothesis Testing: Comparison of Treatments
7 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: The Normality Test
9.1 Hypothesis Testing for One Mean
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
10.2 Comparison of Two Variances
10.3 Comparison of Two Proportions
11 Comparison of More Than Two Means: Analysis of Variance
11.1 ANOVA (Analysis of Variance)
11.2 ANOVA with a Single Factor
11.3 ANOVA with Two Factors
11.4 Test for Homogeneity of Variances
12 Part Two Case Studies - Hypothesis Testing: Comparison of Treatments
12.1 Welding
12.2 Rivets
12.3 Almonds
12.4 Arrow
12.5 U Piece
12.6 Pores
Part Three Measurement Systems Studies and Capability studies
13 Measurement System Study
13.1 Crossed Designs and Nested Designs
13.2 File ‘RR_CROSSED’
13.3 Graphical Analysis
13.4 R&R Study for the Data in File ‘RR_CROSSED’
13.5 File ‘RR_NESTED’
13.6 Gage R&R Study for the Data in File ‘RR_NESTED’
13.7 File ‘GAGELIN’
13.8 Calibration and Linearity Study of the Measurement System
14 Capability Studies
14.1 Available Options
14.2 File ‘VITA_C’
14.3 Capability Analysis (Normal Distribution)
14.4 Interpreting the Obtained Information
14.5 Customizing the Study
14.6 ‘Within’ Variability and ‘Overall’ Variability
14.7 Capability Study when the Sample Size Is Equal to One
14.8 A More Detailed Data Analysis (Capability Sixpack)
15 Capability Studies for Attributes
15.1 File ‘BANK’
15.2 Capability Study for Variables that Follow a Binomial Distribution
15.3 File ‘OVEN_PAINTED’
15.4 Capability Study for Variables that Follow a Poisson Distribution
16 Part Three Case Studies – R&R Studies and Capability Studies
16.1 Diameter_measure
16.2 Diameter_capability_1
16.3 Diameter_capability_2
16.4 Web_visits
Part Four Multi-Vari Charts and Statistical Process Control
17 Multi-Vari Charts
17.1 File ‘MUFFIN’
17.2 Multi-Vari Chart with Three Sources of Variation
17.3 Multi-Vari Chart with Four Sources of Variation
18 Control Charts I: Individual Observations
18.1 File ‘CHLORINE’
18.2 Graph of Individual Observations
18.3 Customizing the Graph
18.4 I Chart Options
18.5 Graphs of Moving Ranges
18.6 Graph of Individual Observations – Moving Ranges
19 Control Charts II: Means and Ranges
19.1 Use of File ‘VITA_C’
19.2 Means Chart
19.3 Graphs of Ranges and Standard Deviations
19.4 Graphs of Means-Ranges
19.5 Some Ideas on How to Use MINITAB as a Simulator of Processes for Didactic Reasons
20 Control Charts for Attributes
20.1 File ‘MOTORS’
20.2 Plotting the Proportion of Defective Units (P)
20.3 File ‘CATHETER’
20.4 Plotting the Number of Defective Units (NP)
20.5 Plotting the Number of Defects per Constant Unit of Measurement (C)
20.6 File ‘FABRIC’
20.7 Plotting the Number of Defects per Variable Unit of Measurement (U)
21 Part Four Case Studies – Multi-Vari Charts and Statistical Process Control
21.1 Bottles
21.2 Mattresses (1st Part)
21.3 Mattresses (2nd Part)
21.4 Plastic (1st Part)
21.5 Plastic (2nd Part)
Part Five Regression and Multivariate Analysis
22 Correlation and Simple Regression
22.1 Correlation Coefficient
22.2 Simple Regression
22.3 Simple Regression with ‘Fitted Line Plot’
22.4 Simple Regression with ‘Regression’
23 Multiple Regression
23.1 File ‘CARS2’
23.3 Exploratory Analysis
23.3 Multiple Regression
23.4 Option Buttons
23.5 Selection of the Best Equation: Best Subsets
23.6 Selection of the Best Equation: Stepwise
24 Multivariate Analysis
24.1 File ‘LATIN_AMERICA’
24.2 Principal Components
24.3 Cluster Analysis for Observations
24.4 Cluster Analysis for Variables
24.5 Discriminant Analysis
25 Part Five Case Studies – Regression and Multivariate Analysis
25.1 Tree
25.2 Power Plant
25.3 Wear
25.4 TV Failure
Part Six Experimental Design and Reliability
26 Selection of the Experimental Plan Using a Factorial Design
26.1 Creation of the Design Matrix
26.2 Definition of a Design Matrix when the Data is Previously Entered in the Worksheet
27 Analysis and Interpretation of the Results of a Factorial Design
27.1 Calculating the Effects and Determining the Significant Ones
28 Response Surface Methodology
28.1 Matrix Design Creation and Data Collection
28.2 Analysis of the Results
28.3 Contour Plots and Response Surface Plots
29 Reliability
29.1 File ‘INJECTION’
29.2 Nonparametric Analysis
29.3 Identification of the Best Model for the Data
29.4 Parametric Analysis
29.5 General Graphical Display of Reliability Data
30 Part Six Case Studies – Design of Experiments and Reliability
30.1 Cardigan
30.2 Steering Wheel – 1
30.3 Steering Wheel – 2
30.4 Paper Helicopters
30.5 Microorganisms
30.6 Jam
30.7 Photocopies
Appendix 1 Answers to Questions that Arise at the Beginning
Appendix 2 Managing Data
A2.1 Copy Columns with Restrictions (File: ‘PULSE’)
A2.2 Selection of Data when Plotting a Graph
A2.3 Stacking and Unstacking of Columns (File ‘BREAD’)
A2.4 Coding and Sorting Data
Appendix 3 Customization of MINITAB
A3.1 Configuration Options
A3.2 Use of Toolbars
A3.3 Add Elements to an Existing Toolbar
A3.4 Create Custom Toolbars
Index
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Add Industrial Statistics with Minitab, 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 th, Industrial Statistics with Minitab to your collection on WonderClub |