UsefulLinks
1. Introduction to Design of Experiments
2. Fundamental Principles of Experimental Design
3. Planning and Conducting Experiments
4. Simple Comparative Experiments
5. Analysis of Variance (ANOVA)
6. Factorial Designs
7. Fractional Factorial Designs
8. Response Surface Methodology
9. Robust Design and Taguchi Methods
10. Advanced and Specialized Designs
11. Statistical Analysis and Model Building
12. Software Tools and Implementation
13. Quality Control and Best Practices
14. Applications and Case Studies
  1. Statistics

Design of Experiments

1. Introduction to Design of Experiments
2. Fundamental Principles of Experimental Design
3. Planning and Conducting Experiments
4. Simple Comparative Experiments
5. Analysis of Variance (ANOVA)
6. Factorial Designs
7. Fractional Factorial Designs
8. Response Surface Methodology
9. Robust Design and Taguchi Methods
10. Advanced and Specialized Designs
11. Statistical Analysis and Model Building
12. Software Tools and Implementation
13. Quality Control and Best Practices
14. Applications and Case Studies
12.
Software Tools and Implementation
12.1.
Statistical Software Overview
12.1.1.
R and R Packages
12.1.2.
SAS JMP
12.1.3.
Minitab
12.1.4.
Design-Expert
12.1.5.
Python Libraries
12.2.
Design Generation
12.2.1.
Creating Experimental Designs
12.2.2.
Randomization Procedures
12.2.3.
Design Evaluation
12.2.4.
Design Modification
12.3.
Data Analysis Implementation
12.3.1.
Data Import and Management
12.3.2.
Statistical Analysis Procedures
12.3.3.
Model Fitting and Selection
12.3.4.
Diagnostic Procedures
12.4.
Visualization and Reporting
12.4.1.
Statistical Graphics
12.4.2.
Response Surface Plots
12.4.3.
Interaction Plots
12.4.4.
Report Generation
12.4.5.
Results Export

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13. Quality Control and Best Practices

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