Regression Analysis

  1. Practical Applications and Implementation
    1. Data Preparation for Regression
      1. Data Cleaning and Preprocessing
        1. Missing Data Handling
          1. Listwise Deletion
            1. Pairwise Deletion
              1. Imputation Methods
              2. Variable Transformation
                1. Outlier Treatment
                  1. Feature Engineering
                  2. Model Building Process
                    1. Exploratory Data Analysis
                      1. Variable Selection Strategies
                        1. Model Specification Testing
                          1. Diagnostic Checking
                            1. Model Refinement
                              1. Final Model Selection
                              2. Interpretation and Communication
                                1. Coefficient Interpretation
                                  1. Statistical vs Practical Significance
                                    1. Confidence Intervals and Uncertainty
                                      1. Presenting Results
                                        1. Limitations and Assumptions
                                        2. Software Implementation
                                          1. Statistical Software Packages
                                            1. Programming Considerations
                                              1. Reproducible Research Practices
                                                1. Documentation and Reporting

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                                              7. Specialized Regression Techniques

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                                              1. Foundations of Regression Analysis