| A | Nonlinear Growth Modeling | Intro to Collection |
| B | Nonlinear Growth Modeling | Need for Nonlinear Growth Models |
| C | Nonlinear Growth Modeling | Basic Linear Growth Model |
| D | Nonlinear Growth Modeling | Quadratic Growth Model |
| E | Nonlinear Growth Modeling | Spline Growth Model |
| F | Nonlinear Growth Modeling | Special Shapes & Time Transforms |
| G | Nonlinear Growth Modeling | Latent Basis Growth Model |
| H | Nonlinear Growth Modeling | Inherently Nonlinear Models (Exponential Growth Model) |
| I | Nonlinear Growth Modeling | Sigmoid Growth Model |
| J | Nonlinear Growth Modeling | Sinusoidal “Growth” Model |
| K | Nonlinear Growth Modeling | A Few Recommendations |
| A | Time | Theoretical Meanings |
| B | Time | Aligning Data and Aligning Life |
| C | Time | Conceptual and Pragmatic Decisions |
| D | Time | Implications for Study Design |
| I | Two Occasion Change Models | Overview |
| II | Two Occasion Change Models | Auto-Regressive and Difference Score Models of Change |
| III | Two Occasion Change Models | Critique, Resolution, Equivalence & Summary |
| 1 | Data Mining | Regression as a Statistical Learning Tool + Cross-Validation |
| 2 | Data Mining | Cross-Validation Tutorial |
| 3 | Data Mining | Supervised Machine Learning: The Caret Package |
| 4 | Data Mining | Introduction to Classification & Regression Trees |
| 5 | Data Mining | Ensemble Methods - Bagging, Random Forests, Boosting |
| 6 | Data Mining | k Nearest Neighbors: An Introductory Example |
| 7 | Data Mining | Unsupervised Machine Learning: The hclust, pvclust, cluster, mclust, and more |
