Minitab for Statistical Data Analysis Training Course

Chapter 1: Descriptive Statistics and Graphical Analysis

Introduction

1. Learning Objectives
2. Data Types

Basic Concepts

1. Types of Data
2. Quiz: Data Types

Utilising Graphs for Data Analysis

1. Core Concepts
2. Bar Charts and Pareto Charts
3. Pie Charts
4. Histograms
5. Dotplots
6. Individual Value Plots
7. Boxplots
8. Time Series Plots
9. Quiz: Utilising Graphs for Data Analysis
10. Minitab Tool: Bar Chart
11. Minitab Tool: Pie Chart
12. Minitab Tool: Histogram
13. Minitab Tool: Dotplot
14. Minitab Tool: Individual Value Plot
15. Minitab Tool: Boxplot
16. Minitab Tool: Time Series Plot
17. Practical: Graphical Analysis

Utilising Statistics for Data Analysis

1. Core Concepts
2. Mean and Median
3. Range, Variance, and Standard Deviation
4. Quiz: Utilising Statistics for Data Analysis
5. Minitab Tool: Display Descriptive Statistics
6. Practical: Descriptive Statistics

Summary and Objectives Review

Chapter 2: Statistical Inference

2.1 Introduction

2.1.1 Learning Objectives
2.2 Fundamentals of Statistical Inference
2.2.1 Core Concepts
2.2.2 Random Samples
2.2.3 Quiz: Fundamentals of Statistical Inference
2.2.4 Minitab Tool: Random Sampling

2.3 Sampling Distributions

2.3.1 Core Concepts
2.3.2 Sampling Distribution of the Mean
2.3.3 Quiz: Sampling Distributions

2.4 Normal Distribution

2.4.1 Core Concepts
2.4.2 Probabilities Associated with a Normal Distribution
2.4.3 Probabilities Associated with the Sample Mean
2.4.4 Quiz: Normal Distribution
2.4.5 Minitab Tool: Cumulative Probabilities with a Normal Distribution
2.4.6 Practical: 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 Tests and Confidence Intervals

3.2.1 Confidence Intervals
3.2.2 Hypothesis Testing
3.2.3 Decision-Making Using Hypothesis Testing
3.2.4 Type I and Type II Errors and Power
3.2.5 Quiz: Tests and Confidence Intervals

3.3 One-Sample t-Test

3.3.1 Core Concepts
3.3.2 Individual Value Plots
3.3.3 One-Sample t-Test Results
3.3.4 Assumptions
3.3.5 Quiz: One-Sample t-Test
3.3.6 Minitab Tool: One-Sample t-Test
3.3.7 Practical: One-Sample t-Test

3.4 Two Variances Test

3.4.1 Core Concepts
3.4.2 Boxplots
3.4.3 Two Variances Test Results 3.4.4 Assumptions
3.4.5 Quiz: Two Variances Test
3.4.6 Minitab Tool: Two Variances Test
3.4.7 Practical: Two Variances Test

3.5 Two-Sample t-Test

3.5.1 Core Concepts
3.5.2 Individual Value Plot
3.5.3 Two-Sample t-Test Results
3.5.4 Assumptions
3.5.5 Quiz: Two-Sample t-Test
3.5.6 Minitab Tool: Two-Sample t-Test
3.5.7 Practical: Two-Sample t-Test

3.6 Paired t-Test

3.6.1 Core Concepts
3.6.2 Individual Value Plots
3.6.3 Paired t-Test Results
3.6.4 Assumptions
3.6.5 Quiz: Paired t-Test
3.6.6 Minitab Tool: Paired t-Test
3.6.7 Practical: Paired t-Test

3.7 One Proportion Test

3.7.1 Core Concepts
3.7.2 One Proportion Test Results
3.7.3 Assumptions
3.7.4 Quiz: One Proportion Test
3.7.5 Minitab Tool: One Proportion Test
3.7.6 Practical: One Proportion Test

3.8 Two Proportions Test

3.8.1 Core Concepts
3.8.2 Two Proportions Test Results
3.8.3 Assumptions
3.8.4 Quiz: Two Proportions Test
3.8.5 Minitab Tool: Two Proportions Test
3.8.6 Practical: Two Proportions Test

3.9 Chi-Square Test

3.9.1 Core Concepts
3.9.2 Chi-Square Test Results
3.9.3 Assumptions
3.9.4 Quiz: Chi-Square Test
3.9.5 Minitab Tool: Chi-Square Test
3.9.6 Practical: 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 Core Concepts
4.2.2 Patterns in Control Charts
4.2.3 Quiz: Statistical Process Control

4.3 Control Charts for Variables Data in Subgroups

4.3.1 Core Concepts
4.3.2 R Charts
4.3.3 S Charts
4.3.4 Xbar Charts
4.3.5 Quiz: Control Charts for Variables Data in Subgroups
4.3.6 Minitab Tool: Xbar-R Chart
4.3.7 Practical: Xbar-R Chart

4.4 Control Charts for Individual Observations

4.4.1 Core Concepts
4.4.2 Moving Range Charts
4.4.3 Individuals Charts
4.4.4 Quiz: Control Charts for Individual Observations
4.4.5 Minitab Tool: I-MR Chart
4.4.6 Practical: I-MR Chart

4.5 Control Charts for Attribute Data

4.5.1 Core Concepts
4.5.2 NP and P Charts
4.5.3 C and U Charts
4.5.4 Quiz: Control Charts for Attributes Data
4.5.5 Minitab Tool: P Chart
4.5.6 Practical: 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 Core Concepts
5.2.2 Assumptions
5.2.3 Testing for Normality
5.2.4 Quiz: Process Capability for Normal Data
5.2.5 Minitab Tool: Normality Test
5.2.6 Practical: 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 Quiz: Capability Indices
5.3.5 Minitab Tool: Cp and Pp
5.3.6 Minitab Tool: Sigma Level
5.3.7 Practical: Process Capability for Normal Data

5.4 Process Capability for Non-Normal 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 Quiz: Process Capability for Non-Normal Data
5.4.6 Minitab Tool: Box-Cox Transformation
5.4.7 Minitab Tool: Johnson Transformation
5.4.8 Minitab Tool: Capability Analysis with Johnson Transformation
5.4.9 Minitab Tool: Alternate Distributions
5.4.10 Minitab Tool: Capability Analysis with Alternate Distributions
5.4.11 Practical: Process Capability with Data Transformations
5.4.12 Practical: 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 Core Concepts
6.2.2 Graphs and Summary Statistics
6.2.3 Quiz: 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 Quiz: One-Way ANOVA
6.3.6 Minitab Tool: One-Way ANOVA
6.3.7 Practical: One-Way ANOVA

6.4 Two-Way ANOVA

6.4.1 Core 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 Quiz: Two-Way ANOVA
6.4.7 Minitab Tool: Two-Way ANOVA
6.4.8 Practical: 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 Core Concepts
7.2.2 Scatterplot
7.2.3 Correlation
7.2.4 Quiz: Relationship Between Two Quantitative Variables
7.2.5 Minitab Tool: Scatterplot
7.2.6 Minitab Tool: Correlation
7.2.7 Practical: Scatterplots and Correlation

7.3 Simple Regression

7.3.1 Core Concepts
7.3.2 Regression
7.3.3 Hypothesis Tests and R-squared
7.3.4 Assumptions and Residual Plots
7.3.5 Quiz: Simple Regression
7.3.6 Minitab Tool: Simple Regression
7.3.7 Practical: 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 Core Concepts
8.2.2 Accuracy
8.2.3 Precision
8.2.4 Comparing Accuracy and Precision
8.2.5 Quiz: Fundamentals of Measurement Systems Analysis

8.3 Repeatability and Reproducibility

8.3.1 Core Concepts
8.3.2 Gage R&R Studies
8.3.3 Quiz: Repeatability and Reproducibility

8.4 Graphical Analysis of a Gage R&R Study

8.4.1 Core 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 Quiz: Graphical Analysis of a Gage R&R Study
8.4.8 Minitab Tool: Crossed Gage R&R Study
8.4.9 Minitab Tool: Gage Run Chart
8.4.10 Practical: 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 Quiz: Variation
8.5.5 Practical: 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 Quiz: ANOVA with a Gage R&R Study
8.6.4 Practical: ANOVA Output for a Gage R&R Study

8.7 Gage Linearity and Bias Study

8.7.1 Core Concepts
8.7.2 Gage Linearity
8.7.3 Gage Bias
8.7.4 Quiz: Gage Linearity and Bias Study
8.7.5 Minitab Tool: Gage Linearity and Bias Study
8.7.6 Practical: Gage Linearity and Bias Study

8.8 Attribute Agreement Analysis

8.8.1 Core Concepts
8.8.2 Binary Data
8.8.3 Nominal Data
8.8.4 Ordinal Data
8.8.5 Quiz: Attribute Agreement Analysis
8.8.6 Minitab Tool: Attribute Agreement Analysis with Binary Data
8.8.7 Minitab Tool: Attribute Agreement Analysis with Nominal Data
8.8.8 Minitab Tool: Attribute Agreement Analysis with Ordinal Data
8.8.9 Practical: 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 Core Concepts
9.2.2 Creating Full Factorial Designs
9.2.3 Analyzing Full Factorial Designs
9.2.4 Quiz: Factorial Designs
9.2.5 Minitab Tool: Create a Full Factorial Design
9.2.6 Minitab Tool: Analyze a Full Factorial Design
9.2.7 Practical: Create a Full Factorial Design
9.2.8 Practical: 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 Quiz: Blocking and Incorporating Center Points
9.3.5 Minitab Tool: Create a Factorial Design with Blocks and Center Points
9.3.6 Minitab Tool: Analyze a Factorial Design with Blocks and Center Points
9.3.7 Practical: Create a Factorial Design with Blocks and Center Points
9.3.8 Practical: Analyze a Factorial Design with Blocks and Center Points

9.4 Fractional Factorial Designs

9.4.1 Core Concepts
9.4.2 Creating Fractional Factorial Designs
9.4.3 Analyzing Fractional Factorial Designs
9.4.4 Quiz: Fractional Factorial Designs
9.4.5 Minitab Tool: Create a Fractional Factorial Design
9.4.6 Minitab Tool: Analyze a Fractional Factorial Design

9.5 Response Optimisation

9.5.1 Response Optimisation
9.5.2 Quiz: Response Optimisation
9.5.3 Minitab Tool: Response Optimisation
9.5.4 Practical: Response Optimisation

9.6 Summary and Objectives Review