Course Outline
Chapter 1: Descriptive Statistics and Graphical Analysis
Introduction
- Learning Objectives
- Data Types
Foundational Concepts
- Categories of Data
- Quiz: Data Types
Utilising Graphs for Data Analysis
- Core Concepts
- Bar Charts and Pareto Charts
- Pie Charts
- Histograms
- Dotplots
- Individual Value Plots
- Boxplots
- Time Series Plots
- Quiz: Visual Data Analysis
- Minitab Tool: Bar Chart
- Minitab Tool: Pie Chart
- Minitab Tool: Histogram
- Minitab Tool: Dotplot
- Minitab Tool: Individual Value Plot
- Minitab Tool: Boxplot
- Minitab Tool: Time Series Plot
- Practical Exercise: Graphical Analysis
Applying Statistics for Data Analysis
- Core Concepts
- Mean and Median
- Range, Variance, and Standard Deviation
- Quiz: Statistical Data Analysis
- Minitab Tool: Display Descriptive Statistics
- Practical Exercise: Descriptive Statistics
Summary and Objectives Recap
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 Sampling
2.2.3 Quiz: Inference Fundamentals
2.2.4 Minitab Tool: Random Sampling
2.3 Sampling Distributions
2.3.1 Core Concepts
2.3.2 Distribution of the Sample Mean
2.3.3 Quiz: Sampling Distributions
2.4 Normal Distribution
2.4.1 Core Concepts
2.4.2 Probabilities in 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 for Normal Distribution
2.4.6 Practical Exercise: Probabilities and Normal Distributions
2.5 Summary
2.5.1 Objectives Recap
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 Principles
3.2.3 Decision-Making via Hypothesis Testing
3.2.4 Type I and Type II Errors and Power
3.2.5 Quiz: Testing and Confidence Intervals
3.1- Sample t-Test
3.3.1 Core Concepts
3.3.2 Individual Value Plots
3.3.3 1-Sample t-Test Outcomes
3.3.4 Underlying Assumptions
3.3.5 Quiz: 1-Sample t-Test
3.3.6 Minitab Tool: 1-Sample t-Test
3.3.7 Practical Exercise: 1-Sample t-Test
3.4 Variance Test
3.4.1 Core Concepts
3.4.2 Boxplots
3.4.3 2 Variance Test Outcomes
3.4.4 Underlying Assumptions
3.4.5 Quiz: 2 Variance Test
3.4.6 Minitab Tool: 2 Variance Test
3.4.7 Practical Exercise: 2 Variance Test
3.5 2-Sample t-Test
3.5.1 Core Concepts
3.5.2 Individual Value Plot
3.5.3 2-Sample t-Test Outcomes
3.5.4 Underlying Assumptions
3.5.5 Quiz: 2-Sample t-Test
3.5.6 Minitab Tool: 2-Sample t-Test
3.5.7 Practical Exercise: 2-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 Outcomes
3.6.4 Underlying Assumptions
3.6.5 Quiz: Paired t-Test
3.6.6 Minitab Tool: Paired t-Test
3.6.7 Practical Exercise: Paired t-Test
3.7 1-Proportion Test
3.7.1 Core Concepts
3.7.2 1-Proportion Test Outcomes
3.7.3 Underlying Assumptions
3.7.4 Quiz: 1-Proportion Test
3.7.5 Minitab Tool: 1-Proportion Test
3.7.6 Practical Exercise: 1-Proportion Test
3.8 2-Proportions Test
3.8.1 Core Concepts
3.8.2 2-Proportions Test Outcomes
3.8.3 Underlying Assumptions
3.8.4 Quiz: 2-Proportions Test
3.8.5 Minitab Tool: 2-Proportions Test
3.8.6 Practical Exercise: 2-Proportions Test
3.9 Chi-Square Test
3.9.1 Core Concepts
3.9.2 Chi-Square Test Outcomes
3.9.3 Underlying Assumptions
3.9.4 Quiz: Chi-Square Test
3.9.5 Minitab Tool: Chi-Square Test
3.9.6 Practical Exercise: Chi-Square Test
3.10 Summary
3.10.1 Objectives Recap
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 Identifying Patterns in Control Charts
4.2.3 Quiz: Statistical Process Control
4.3 Control Charts for Subgrouped Variable Data
4.3.1 Core Concepts
4.3.2 R Charts
4.3.3 S Charts
4.3.4 Xbar Charts
4.3.5 Quiz: Subgrouped Variable Data Charts
4.3.6 Minitab Tool: Xbar-R Chart
4.3.7 Practical Exercise: 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: Individual Observation Charts
4.4.5 Minitab Tool: I-MR Chart
4.4.6 Practical Exercise: 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: Attribute Data Charts
4.5.5 Minitab Tool: P Chart
4.5.6 Practical Exercise: P Chart
4.6 Summary and Objectives Recap
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 Underlying Assumptions
5.2.3 Testing for Normality
5.2.4 Quiz: Capability for Normal Data
5.2.5 Minitab Tool: Normality Test
5.2.6 Practical Exercise: Assumptions for 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 Exercise: Capability for Normal Data
5.4 Process Capability for Non-Normal Data
5.4.1 Transformations and Alternative Distributions
5.4.2 Box-Cox Transformation
5.4.3 Johnson Transformation
5.4.4 Alternative Distributions
5.4.5 Quiz: 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: Alternative Distributions
5.4.10 Minitab Tool: Capability Analysis with Alternative Distributions
5.4.11 Practical Exercise: Capability with Data Transformations
5.4.12 Practical Exercise: Capability with Alternative Distributions
5.5 Summary
5.5.1 Objectives Recap
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: ANOVA Fundamentals
6.3 One-Way ANOVA
6.3.1 Hypothesis Testing
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 Exercise: One-Way ANOVA
6.4 Two-Way ANOVA
6.4.1 Core Concepts
6.4.2 Graphs
6.4.3 Hypothesis Testing
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 Exercise: 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 Scatterplots
7.2.3 Correlation
7.2.4 Quiz: Quantitative Relationships
7.2.5 Minitab Tool: Scatterplot
7.2.6 Minitab Tool: Correlation
7.2.7 Practical Exercise: Scatterplots and Correlation
7.3 Simple Regression
7.3.1 Core Concepts
7.3.2 Regression Analysis
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 Exercise: Simple Regression
7.4 Summary and Objectives Recap
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: MSA Fundamentals
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 Gage R&R Studies
8.4.1 Core Concepts
8.4.2 Components of Variation
8.4.3 Xbar and R Charts
8.4.4 Operator-Part Interaction
8.4.5 Comparative Plots
8.4.6 Gage Run Charts
8.4.7 Quiz: Gage R&R Graphical Analysis
8.4.8 Minitab Tool: Crossed Gage R&R Study
8.4.9 Minitab Tool: Gage Run Chart
8.4.10 Practical Exercise: Gage R&R Graphical Analysis
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 Exercise: Numerical Gage R&R Analysis
8.6 ANOVA in Gage R&R Studies
8.6.1 Variance Components
8.6.2 ANOVA Tables
8.6.3 Quiz: ANOVA in Gage R&R
8.6.4 Practical Exercise: ANOVA Output for Gage R&R
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: Linearity and Bias
8.7.5 Minitab Tool: Gage Linearity and Bias Study
8.7.6 Practical Exercise: Gage Linearity and Bias
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
8.8.6 Minitab Tool: Attribute Agreement (Binary Data)
8.8.7 Minitab Tool: Attribute Agreement (Nominal Data)
8.8.8 Minitab Tool: Attribute Agreement (Ordinal Data)
8.8.9 Practical Exercise: Attribute Agreement
8.9 Summary
8.9.1 Objectives Recap
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 Full Factorial Design
9.2.6 Minitab Tool: Analyze Full Factorial Design
9.2.7 Practical Exercise: Creating Full Factorial Design
9.2.8 Practical Exercise: Analyzing Full Factorial Design
9.3 Blocking and 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 Center Points
9.3.5 Minitab Tool: Create Factorial Design with Blocks and Center Points
9.3.6 Minitab Tool: Analyze Factorial Design with Blocks and Center Points
9.3.7 Practical Exercise: Creating Factorial Design with Blocks and Center Points
9.3.8 Practical Exercise: Analyzing 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 Fractional Factorial Design
9.4.6 Minitab Tool: Analyze Fractional Factorial Design
9.5 Response Optimization
9.5.1 Response Optimization Principles
9.5.2 Quiz: Response Optimization
9.5.3 Minitab Tool: Response Optimization
9.5.4 Practical Exercise: Response Optimization
9.6 Summary and Objectives Recap
Requirements
A basic understanding of Excel and statistics is required.
Testimonials (7)
I liked the excercises and how great it was to follow
Elizabeth Seed - Terumo Aortic
Course - Minitab for Statistical Data Analysis
Going through all the different examples and explaining each of the terms.
Lewis Print - Terumo Aortic
Course - Minitab for Statistical Data Analysis
Interactive, well explained and not overly in-depth with each section required to cover each section
Christopher Beattie - Terumo Aortic
Course - Minitab for Statistical Data Analysis
The practical demonstrations
Simson McCreath - Terumo Aortic
Course - Minitab for Statistical Data Analysis
The trainer had an excellent understanding of the subject matter, and was able to answer any questions easily and concisely.
Craig Renfrew - Terumo Aortic
Course - Minitab for Statistical Data Analysis
Gaining practical experience of Minitab software.
Layna Thompson - Terumo Aortic
Course - Minitab for Statistical Data Analysis
Trainer was very knowledgeable
