Y1 - Quantitative Methods II

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• 9.1 Randomized, Comparative Experiments.
• 9.2 The Four Principles of Experimental Design.
• 9.3 Experimental Designs.
• 16.1.1 Interpret or analyze linear models or relationships
• 16.2.1 Interpret or analyze linear models or relationships
• 16.2.2 Use models to make predictions
• 16.3.3 Identify leveraged and/or influential points and determine if they affect the model.
• 16.3.4 Determine when linear models are appropriate and/or useful for predicting y-values
• 16.4.1 Interpret or analyze linear models or relationships.
• 16.5.4 Determine when linear models are appropriate and/or useful for predicting y-values.
• 16.6.6 Determine if a re-expression is appropriate.
• 16.7.6 Determine if a re-expression is appropriate.
• 17.1 Examining Residuals for Groups.
• 17.3 Unusual and Extraordinary Observations.
• 17.4 Working with Summary Values.
• 17.5 Autocorrelation.
• 17.7 The Ladder of Powers.
• 19.1 Indicator (or Dummy) Variables.
• 19.2 Adjusting for Different Slopes-Interaction Terms.
• 19.2 Adjusting for Different Slopes—Interaction Terms.
• 19.3 Multiple Regression Diagnostics.
• 19.4 Building Regression Models.
• 19.5 Collinearity
• 19.5 Collinearity.
• 20.10.3 Perform tests and state conclusions.
• 25.1 Analyzing a Design in One Factor—The One-Way Analysis of Variance.
• 25.2 Assumptions and Conditions for ANOVA.
• 25.3 Multiple Comparisons.
• 25.5 Analysis of Multifactor Designs.
• Chapter 4: Correlation and Linear Regression
• Chapter 14: Comparing Two Means – Quiz C
• Chapter 14: Comparing Two Means – Quiz D
• Chapter 15: Inference for Counts: Chi-Square Tests – Quiz C – Multiple Choice
• Chapter 15: Inference for Counts: Chi-Square Tests – Quiz D – Multiple Choice
• Chapter 16: Inference for Regression – Quiz C – Multiple Choice
• Chapter 16: Inference for Regression – Quiz D – Multiple Choice
• Chapter 18: Multiple Regression – Quiz C – Multiple Choice
• Chapter 18: Multiple Regression – Quiz D – Multiple Choice