Class notes

All files in PDF format

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• Syllabus
• SAS Introduction
• 1. Course Overview and Introduction to Design of Experiments
• 2. Review of Statistical Concepts
• 3. Simple Comparative Experiments
• 4. Single Factor Experiments
• 5. Checking Model Conditions
• 6. Linear Combinations and Multiple Comparisons
• 7. Random Factor in Single Factor Experiment
• 8. Power Calculation for Single Factor Experiment
• 9. ANOVA in terms of a linear regression model
• 10. Analysis of Covariance
• 11. Randomized Complete Block Design
• 12. Latin Square Design and Introduction to Repeated Measures
• 13. Replicated Latin Square and Crossover Design
• 14. Balanced Incomplete Block Design and Intrablock Analysis
• 15. Factorial Treatment Structure (focus on 2 x 2 factorial)
• 16. Factorial Analysis
• 17. General Factorial Model
• 18. Mixed Factorial Models I
• 19. Mixed Factorial Models II
• 20. Nested versus Crossed Factors
• 21. Split plot Design
• 22. Computing Standard Errors
• 23. Repeated Measures Analysis
• 24. 2^k Factorial Designs
• 25. Blocking and Confounding in 2^k
• 26. Fractional Factorials
• 27. Introduction to Response Surface Methodology

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