UsefulLinks
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
11.
Statistical Analysis and Model Building
11.1.
Data Preparation and Exploration
11.1.1.
Data Cleaning Procedures
11.1.2.
Missing Data Handling
11.1.3.
Outlier Detection and Treatment
11.1.4.
Exploratory Data Analysis
11.1.5.
Graphical Methods
11.2.
Model Specification and Fitting
11.2.1.
Linear Models
11.2.2.
Generalized Linear Models
11.2.3.
Nonlinear Models
11.2.4.
Parameter Estimation Methods
11.2.5.
Maximum Likelihood Estimation
11.3.
Model Selection and Validation
11.3.1.
Model Selection Criteria
11.3.1.1.
AIC and BIC
11.3.1.2.
Cross-Validation
11.3.1.3.
Prediction Error
11.3.2.
Variable Selection Methods
11.3.2.1.
Forward Selection
11.3.2.2.
Backward Elimination
11.3.2.3.
Stepwise Selection
11.3.3.
Model Validation Techniques
11.3.4.
Overfitting Prevention
11.4.
Assumption Checking and Diagnostics
11.4.1.
Residual Analysis
11.4.2.
Influence Diagnostics
11.4.3.
Leverage and Cook's Distance
11.4.4.
Normality Assessment
11.4.5.
Homoscedasticity Testing
11.4.6.
Independence Verification
11.5.
Interpretation and Communication
11.5.1.
Effect Size Interpretation
11.5.2.
Practical vs. Statistical Significance
11.5.3.
Confidence Intervals
11.5.4.
Prediction Intervals
11.5.5.
Graphical Presentation
11.5.6.
Report Writing
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10. Advanced and Specialized Designs
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12. Software Tools and Implementation