Chapter 1: Introduction to Minitab
- Lesson 1: What is Minitab?
- Lesson 2: History and Evolution of Minitab
- Lesson 3: Importance of Minitab in Data Analysis & Six Sigma
- Lesson 4: Installing Minitab (Windows, macOS)
- Lesson 5: Minitab Interface and Navigation
Chapter 2: Data Entry and Management in Minitab
- Lesson 1: Entering and Importing Data (Excel, CSV, TXT)
- Lesson 2: Data Types and Variable Classifications
- Lesson 3: Editing and Formatting Data in Minitab
- Lesson 4: Managing Missing Data
- Lesson 5: Data Validation and Cleaning
Chapter 3: Basic Statistics in Minitab
- Lesson 1: Descriptive Statistics (Mean, Median, Mode)
- Lesson 2: Measures of Dispersion (Variance, Standard Deviation)
- Lesson 3: Frequency Distribution and Histograms
- Lesson 4: Boxplots and Outlier Detection
- Lesson 5: Data Transformation and Normalization
Chapter 4: Graphing and Visualization
- Lesson 1: Creating Histograms and Bar Charts
- Lesson 2: Scatterplots and Line Graphs
- Lesson 3: Boxplots and Pareto Charts
- Lesson 4: Customizing Graphs in Minitab
- Lesson 5: Exporting and Sharing Graphs
Chapter 5: Probability and Distribution Analysis
- Lesson 1: Introduction to Probability Distributions
- Lesson 2: Normal Distribution Analysis
- Lesson 3: Binomial and Poisson Distributions
- Lesson 4: Confidence Intervals and Prediction Intervals
- Lesson 5: Distribution Fitting in Minitab
Chapter 6: Hypothesis Testing (Basics)
- Lesson 1: Introduction to Hypothesis Testing
- Lesson 2: One-Sample t-Test
- Lesson 3: Two-Sample t-Test and Paired t-Test
- Lesson 4: ANOVA (One-Way Analysis of Variance)
- Lesson 5: Interpreting P-Values and Significance
Chapter 7: Regression Analysis (Fundamentals)
- Lesson 1: Understanding Regression in Minitab
- Lesson 2: Simple Linear Regression
- Lesson 3: Correlation vs. Regression
- Lesson 4: Residual Analysis and Model Fit
- Lesson 5: Multiple Linear Regression (Introductory)
Chapter 8: Quality Control and Control Charts
- Lesson 1: Introduction to Statistical Process Control (SPC)
- Lesson 2: Creating and Interpreting Control Charts
- Lesson 3: Process Capability Analysis
- Lesson 4: Understanding Cp, Cpk, Pp, and Ppk
- Lesson 5: Identifying Process Variation
Chapter 9: Pareto Analysis and Root Cause Analysis
- Lesson 1: Importance of Pareto Analysis in Decision-Making
- Lesson 2: Creating and Interpreting Pareto Charts
- Lesson 3: Root Cause Analysis Using Minitab
- Lesson 4: Cause-and-Effect (Fishbone) Diagrams
- Lesson 5: Case Study: Using Pareto Analysis in Quality Improvement
Chapter 10: Measurement System Analysis (MSA) Basics
- Lesson 1: Understanding Measurement System Variation
- Lesson 2: Gage R&R Study (Basics)
- Lesson 3: Evaluating Repeatability and Reproducibility
- Lesson 4: Attribute Agreement Analysis
- Lesson 5: Interpreting MSA Reports
Chapter 1: Advanced Data Manipulation
- Lesson 1: Data Filtering and Subsetting
- Lesson 2: Data Binning and Recoding Variables
- Lesson 3: Working with Categorical vs. Continuous Data
- Lesson 4: Advanced Data Cleaning Techniques
- Lesson 5: Automating Data Preparation Tasks
Chapter 2: Advanced Hypothesis Testing
- Lesson 1: Chi-Square Test for Independence
- Lesson 2: Mann-Whitney and Wilcoxon Signed-Rank Tests
- Lesson 3: Two-Way ANOVA and Factorial ANOVA
- Lesson 4: Power and Sample Size Calculations
- Lesson 5: Non-Parametric Tests in Minitab
Chapter 3: Advanced Regression Techniques
- Lesson 1: Multiple Linear Regression (Detailed)
- Lesson 2: Logistic Regression in Minitab
- Lesson 3: Stepwise Regression and Model Selection
- Lesson 4: Polynomial Regression and Nonlinear Models
- Lesson 5: Identifying and Handling Multicollinearity
Chapter 4: Design of Experiments (DOE)
- Lesson 1: Introduction to DOE in Minitab
- Lesson 2: Full Factorial Design
- Lesson 3: Fractional Factorial Design
- Lesson 4: Response Surface Methodology
- Lesson 5: Taguchi Design and Optimization
Chapter 5: Time Series Analysis and Forecasting
- Lesson 1: Introduction to Time Series Data
- Lesson 2: Moving Averages and Smoothing Techniques
- Lesson 3: Autoregressive and Exponential Smoothing Models
- Lesson 4: Time Series Decomposition
- Lesson 5: Forecasting with Minitab
Chapter 6: Advanced Control Charts
- Lesson 1: EWMA and Cumulative Sum (CUSUM) Charts
- Lesson 2: Multivariate Control Charts
- Lesson 3: Process Stability and Capability Analysis
- Lesson 4: Control Chart Automation in Minitab
- Lesson 5: Case Study: Real-World Process Control
Chapter 7: Reliability and Survival Analysis
- Lesson 1: Introduction to Reliability Engineering
- Lesson 2: Weibull Distribution and Failure Rate Analysis
- Lesson 3: Survival Curves and Hazard Functions
- Lesson 4: Kaplan-Meier Estimation
- Lesson 5: Proportional Hazards Model
Chapter 8: Monte Carlo Simulation in Minitab
- Lesson 1: Understanding Monte Carlo Simulation
- Lesson 2: Running Simulations in Minitab
- Lesson 3: Risk Analysis with Monte Carlo Methods
- Lesson 4: Sensitivity Analysis
- Lesson 5: Case Study: Business Decision Optimization
Chapter 9: Six Sigma and Lean Methodologies
- Lesson 1: Introduction to Six Sigma Tools in Minitab
- Lesson 2: DMAIC Process Overview
- Lesson 3: Lean Manufacturing and Process Improvement
- Lesson 4: Implementing Kaizen with Minitab
- Lesson 5: Case Study: Applying Six Sigma in Manufacturing
Chapter 10: Automating Tasks with Minitab Macros
- Lesson 1: Introduction to Minitab Macros
- Lesson 2: Writing and Running Macros
- Lesson 3: Automating Reports with Macros
- Lesson 4: Custom Data Processing Using Macros
- Lesson 5: Integrating Macros with Other Tools
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