Lecture 1 - Introduction of Quality
Lecture 2 - Voice of the Customer and Kano Model
Lecture 3 - Quality Function Deployment
Lecture 4 - Critical to Quality Characteristics
Lecture 5 - Data Visualization for Quality Control and Improvement
Lecture 6 - Importance of Pareto Chart and Cause and Effect Diagram
Lecture 7 - Design Failure Mode and Effect Analysis
Lecture 8 - Introduction to Statistical Process Control
Lecture 9 - X-bar and R Chart
Lecture 10 - X-bar and S Chart
Lecture 11 - Individual Moving Range Chart and Attribute Chart
Lecture 12 - Attribute Control Charts and Process Capability
Lecture 13 - Process Capability Index
Lecture 14 - Process Performance and Sigma Level
Lecture 15 - Process Capability for Attribute data
Lecture 16 - Basic Statistics and Confidence Interval
Lecture 17 - Hypothesis Testing
Lecture 18 - One-sample t Test
Lecture 19 - Two-sample t Test
Lecture 20 - Paired t Test and ANOVA
Lecture 21 - One-way ANOVA
Lecture 22 - One-way ANOVA (Continued...)
Lecture 23 - ANCOVA and Nonparametric Test
Lecture 24 - Linear Regression
Lecture 25 - Linear Regression (Continued...) and Multiple Regression
Lecture 26 - Best Subset Regression, Multicollinearity
Lecture 27 - Multicollinearity, Best Subset Regression, Multiple Regression, Basics on Design of Experiment
Lecture 28 - Design of Experiment, One-factor-at-a-time experiment
Lecture 29 - Two-factor asymmetric Design, Symmetric Factorial Design, Two-way ANOVA
Lecture 30 - Two-factor symmetric Design, Robust setting, Two-way ANOVA
Lecture 31 - Measurement System Analysis
Lecture 32 - Measurement System Analysis (Continued...)
Lecture 33 - Measurement System Analysis (Continued...), Introduction to Factorial Experiments
Lecture 34 - Factorial Experiments
Lecture 35 - Factorial Experiments (Continued...)
Lecture 36 - Factorial Experiments (Continued...)
Lecture 37 - Blocking in Factorial Design.
Lecture 38 - Multiple response Optimization and RSM
Lecture 39 - Fractional Factorial Design
Lecture 40 - Taguchi Method
