Minitab for Statistical Data Analysis Training Course

Chapter 1: Descriptive Statistics and Graphical Analysis

Introduction

1. Learning Objectives
2. Data Classifications

Foundational Concepts

1. Categories of Data
2. Assessment: Data Classifications

Analyzing Data Through Graphical Representation

1. Core Principles
2. Bar Charts and Pareto Diagrams
3. Pie Charts
4. Histograms
5. Dotplots
6. Individual Value Plots
7. Boxplots
8. Time Series Plots
9. Assessment: Analyzing Data Through Graphical Representation
10. Minitab Tools: Bar Chart
11. Minitab Tools: Pie Chart
12. Minitab Tools: Histogram
13. Minitab Tools: Dotplot
14. Minitab Tools: Individual Value Plot
15. Minitab Tools: Boxplot
16. Minitab Tools: Times Series Plot
17. Practical Task: Graphical Analysis

Analyzing Data Using Statistical Measures

1. Core Principles
2. Mean and Median
3. Range, Variance, and Standard Deviation
4. Assessment: Analyzing Data Using Statistical Measures
5. Minitab Tools: Display Descriptive Statistics
6. Practical Task: Descriptive Statistics

Summary and Objectives Review

Chapter 2: Statistical Inference

2.1 Introduction

2.1.1 Learning Objectives
2.2 Foundations of Statistical Inference
2.2.1 Basic Concepts
2.2.2 Random Samples
2.2.3 Assessment: Foundations of Statistical Inference
2.2.4 Minitab Tools: Random Sampling

2.3 Sampling Distributions

2.3.1 Basic Concepts
2.3.2 Sampling Distribution of the Mean
2.3.3 Assessment: Sampling Distributions

2.4 Normal Distribution

2.4.1 Basic Concepts
2.4.2 Probabilities Associated with a Normal Distribution
2.4.3 Probabilities Associated with the Sample Mean
2.4.4 Assessment: Normal Distribution
2.4.5 Minitab Tools: Cumulative Probabilities with a Normal Distribution
2.4.6 Practical Task: Probabilities and Normal Distributions

2.5 Summary

2.5.1 Objectives Review

Chapter 3: Hypothesis Tests and Confidence Intervals

3.1 Introduction

3.1.1 Learning Objectives

3.2 Hypothesis Testing and Confidence Intervals

3.2.1 Confidence Intervals
3.2.2 Hypothesis Testing
3.2.3 Decision-Making via Hypothesis Testing
3.2.4 Type I and Type II Errors and Statistical Power
3.2.5 Assessment: Hypothesis Testing and Confidence Intervals

3.3 One-Sample t-Test

3.3.1 Basic Concepts
3.3.2 Individual Value Plots
3.3.3 One-Sample t-Test Outcomes
3.3.4 Assumptions
3.3.5 Assessment: One-Sample t-Test
3.3.6 Minitab Tools: One-Sample t-Test
3.3.7 Practical Task: One-Sample t-Test

3.4 Two-Variance Test

3.4.1 Basic Concepts
3.4.2 Boxplots
3.4.3 Two-Variance Test Outcomes
3.4.4 Assumptions
3.4.5 Assessment: Two-Variance Test
3.4.6 Minitab Tools: Two-Variance Test
3.4.7 Practical Task: Two-Variance Test

3.5 Two-Sample t-Test

3.5.1 Basic Concepts
3.5.2 Individual Value Plot
3.5.3 Two-Sample t-Test Outcomes
3.5.4 Assumptions
3.5.5 Assessment: Two-Sample t-Test
3.5.6 Minitab Tools: Two-Sample t-Test
3.5.7 Practical Task: Two-Sample t-Test

3.6 Paired t-Test

3.6.1 Basic Concepts
3.6.2 Individual Value Plots
3.6.3 Paired t-Test Outcomes
3.6.4 Assumptions
3.6.5 Assessment: Paired t-Test
3.6.6 Minitab Tools: Paired t-Test
3.6.7 Practical Task: Paired t-Test

3.7 One-Proportion Test

3.7.1 Basic Concepts
3.7.2 One-Proportion Test Outcomes
3.7.3 Assumptions
3.7.4 Assessment: One-Proportion Test
3.7.5 Minitab Tools: One-Proportion Test
3.7.6 Practical Task: One-Proportion Test

3.8 Two-Proportion Test

3.8.1 Basic Concepts
3.8.2 Two-Proportion Test Outcomes
3.8.3 Assumptions
3.8.4 Assessment: Two-Proportion Test
3.8.5 Minitab Tools: Two-Proportion Test
3.8.6 Practical Task: Two-Proportion Test

3.9 Chi-Square Test

3.9.1 Basic Concepts
3.9.2 Chi-Square Test Outcomes
3.9.3 Assumptions
3.9.4 Assessment: Chi-Square Test
3.9.5 Minitab Tools: Chi-Square Test
3.9.6 Practical Task: Chi-Square Test

3.10 Summary

3.10.1 Objectives Review

Chapter 4: Control Charts

4.1 Introduction

4.1.1 Learning Objectives

4.2 Statistical Process Control

4.2.1 Basic Concepts
4.2.2 Identifying Patterns in Control Charts
4.2.3 Assessment: Statistical Process Control

4.3 Control Charts for Variable Data in Subgroups

4.3.1 Basic Concepts
4.3.2 Range (R) Charts
4.3.3 Standard Deviation (S) Charts
4.3.4 Mean (Xbar) Charts
4.3.5 Assessment: Control Charts for Variable Data in Subgroups
4.3.6 Minitab Tools: Xbar-R Chart
4.3.7 Practical Task: Xbar-R Chart

4.4 Control Charts for Individual Observations

4.4.1 Basic Concepts
4.4.2 Moving Range Charts
4.4.3 Individuals Charts
4.4.4 Assessment: Control Charts for Individual Observations
4.4.5 Minitab Tools: I-MR Chart
4.4.6 Practical Task: I-MR Chart

4.5 Control Charts for Attribute Data

4.5.1 Basic Concepts
4.5.2 NP and P Charts
4.5.3 C and U Charts
4.5.4 Assessment: Control Charts for Attribute Data
4.5.5 Minitab Tools: P Chart
4.5.6 Practical Task: P Chart

4.6 Summary and Objectives Review

Chapter 5: Process Capability

5.1 Introduction

5.1.1 Learning Objectives

5.2 Process Capability for Normal Data

5.2.1 Basic Concepts
5.2.2 Assumptions
5.2.3 Testing for Normality
5.2.4 Assessment: Process Capability for Normal Data
5.2.5 Minitab Tools: Normality Test
5.2.6 Practical Task: Assumptions for Process Capability

5.3 Capability Indices

5.3.1 Potential Capability: Cp and Cpk
5.3.2 Process Performance: Pp and Ppk
5.3.3 Sigma Level
5.3.4 Assessment: Capability Indices
5.3.5 Minitab Tools: Cp and Pp
5.3.6 Minitab Tools: Sigma Level
5.3.7 Practical Task: Process Capability for Normal Data

5.4 Process Capability for Nonnormal Data

5.4.1 Transformations and Alternate Distributions
5.4.2 Box-Cox Transformation
5.4.3 Johnson Transformation
5.4.4 Alternate Distributions
5.4.5 Assessment: Process Capability for Nonnormal Data
5.4.6 Minitab Tools: Box-Cox Transformation
5.4.7 Minitab Tools: Johnson Transformation
5.4.8 Minitab Tools: Capability Analysis with Johnson Transformation
5.4.9 Minitab Tools: Alternate Distributions
5.4.10 Minitab Tools: Capability Analysis with Alternate Distributions
5.4.11 Practical Task: Process Capability with Data Transformations
5.4.12 Practical Task: Process Capability with Alternate Distributions

5.5 Summary

5.5.1 Objectives Review

Chapter 6: Analysis of Variance (ANOVA)

6.1 Introduction and Learning Objectives

6.2 Fundamentals of ANOVA

6.2.1 Basic Concepts
6.2.2 Graphs and Summary Statistics
6.2.3 Assessment: Fundamentals of ANOVA

6.3 One-Way ANOVA

6.3.1 Hypothesis Tests
6.3.2 F-Statistics and P-Values
6.3.3 Multiple Comparisons
6.3.4 Assumptions and Residual Plots
6.3.5 Assessment: One-Way ANOVA
6.3.6 Minitab Tools: One-Way ANOVA
6.3.7 Practical Task: One-Way ANOVA

6.4 Two-Way ANOVA

6.4.1 Basic Concepts
6.4.2 Graphs
6.4.3 Hypothesis Tests
6.4.4 F-Statistics and P-Values
6.4.5 Assumptions and Residual Plots
6.4.6 Assessment: Two-Way ANOVA
6.4.7 Minitab Tools: Two-Way ANOVA
6.4.8 Practical Task: Two-Way ANOVA

6.5 Summary

Chapter 7: Correlation and Regression

7.1 Introduction

7.1.1 Learning Objectives

7.2 Relationship Between Two Quantitative Variables

7.2.1 Basic Concepts
7.2.2 Scatterplot
7.2.3 Correlation
7.2.4 Assessment: Relationship Between Two Quantitative Variables
7.2.5 Minitab Tools: Scatterplot
7.2.6 Minitab Tools: Correlation
7.2.7 Practical Task: Scatterplots and Correlation

7.3 Simple Regression

7.3.1 Basic Concepts
7.3.2 Regression
7.3.3 Hypothesis Tests and R-squared
7.3.4 Assumptions and Residual Plots
7.3.5 Assessment: Simple Regression
7.3.6 Minitab Tools: Simple Regression
7.3.7 Practical Task: Simple Regression

7.4 Summary and Objectives Review

Chapter 8: Measurement Systems Analysis

8.1 Introduction

8.1.1 Learning Objectives

8.2 Fundamentals of Measurement Systems Analysis

8.2.1 Basic Concepts
8.2.2 Accuracy
8.2.3 Precision
8.2.4 Comparing Accuracy and Precision
8.2.5 Assessment: Fundamentals of Measurement Systems Analysis

8.3 Repeatability and Reproducibility

8.3.1 Basic Concepts
8.3.2 Gage R&R Studies
8.3.3 Assessment: Repeatability and Reproducibility

8.4 Graphical Analysis of a Gage R&R Study

8.4.1 Basic Concepts
8.4.2 Components of Variation
8.4.3 Xbar and R Charts
8.4.4 Interaction between Operator and Part
8.4.5 Comparative Plots
8.4.6 Gage Run Charts
8.4.7 Assessment: Graphical Analysis of a Gage R&R Study
8.4.8 Minitab Tools: Crossed Gage R&R Study
8.4.9 Minitab Tools: Gage Run Chart
8.4.10 Practical Task: Graphical Analysis of a Gage R&R Study

8.5 Variation

8.5.1 Standard Deviation and Study Variation
8.5.2 Tolerance
8.5.3 Process Variation 
8.5.4 Assessment: Variation
8.5.5 Practical Task: Numerical Analysis of a Gage R&R Study

8.6 ANOVA with a Gage R&R Study

8.6.1 Variance Components
8.6.2 Analysis of Variance Tables
8.6.3 Assessment: ANOVA with a Gage R&R Study
8.6.4 Practical Task: ANOVA Output for a Gage R&R Study

8.7 Gage Linearity and Bias Study

8.7.1 Basic Concepts
8.7.2 Gage Linearity
8.7.3 Gage Bias
8.7.4 Assessment: Gage Linearity and Bias Study
8.7.5 Minitab Tools: Gage Linearity and Bias Study
8.7.6 Practical Task: Gage Linearity and Bias Study

8.8 Attribute Agreement Analysis

8.8.1 Basic Concepts
8.8.2 Binary Data
8.8.3 Nominal Data
8.8.4 Ordinal Data
8.8.5 Assessment: Attribute Agreement Analysis
8.8.6 Minitab Tools: Attribute Agreement Analysis with Binary Data
8.8.7 Minitab Tools: Attribute Agreement Analysis with Nominal Data
8.8.8 Minitab Tools: Attribute Agreement Analysis with Ordinal Data
8.8.9 Practical Task: Attribute Agreement Analysis

8.9 Summary

8.9.1 Objectives Review

Chapter 9: Design of Experiments

9.1 Introduction and Learning Objectives

9.2 Factorial Designs

9.2.1 Basic Concepts
9.2.2 Creating Full Factorial Designs
9.2.3 Analyzing Full Factorial Designs
9.2.4 Assessment: Factorial Designs
9.2.5 Minitab Tools: Create a Full Factorial Design
9.2.6 Minitab Tools: Analyze a Full Factorial Design
9.2.7 Practical Task: Create a Full Factorial Design
9.2.8 Practical Task: Analyze a Full Factorial Design

9.3 Blocking and Incorporating Center Points

9.3.1 Blocking
9.3.2 Center Points
9.3.3 Analyzing Designs with Blocks and Center Points
9.3.4 Assessment: Blocking and Incorporating Center Points
9.3.5 Minitab Tools: Create a Factorial Design with Blocks and Center Points
9.3.6 Minitab Tools: Analyze a Factorial Design with Blocks and Center Points
9.3.7 Practical Task: Create a Factorial Design with Blocks and Center Points
9.3.8 Practical Task: Analyze a Factorial Design with Blocks and Center Points

9.4 Fractional Factorial Designs

9.4.1 Basic Concepts
9.4.2 Creating Fractional Factorial Designs
9.4.3 Analyzing Fractional Factorial Designs
9.4.4 Assessment: Fractional Factorial Designs
9.4.5 Minitab Tools: Create a Fractional Factorial Design
9.4.6 Minitab Tools: Analyze a Fractional Factorial Design

9.5 Response Optimization

9.5.1 Response Optimization
9.5.2 Assessment: Response Optimization
9.5.3 Minitab Tools: Response Optimization
9.5.4 Practical Task: Response Optimization

9.6 Summary and Objectives Review