1. Regression Analysis Jared Dean as quoted in Big Data, Data Mining, and Machine Learning – From my experience, regression is the most dominant force in driving business decisions today. Regression analysis has many useful characteristics; one is the easy interpretation of results. Regression concepts are widely understood, and the methodology is well developed such that a well-tuned regression model by a skilled practitioner can outperform many algorithms that are gaining popularity from the machine learning discipline.

2. Simple Linear Regression

3. Khan Academy Videos Formula Derivation (4 parts) Examples (2 parts) R-squared or coefficient of determination (2 parts)Formula Derivation (4 parts)Examples (2 parts)R-squared or coefficient of determination (2 parts) Linear regression calculator Compute the equation for the least - squares, best-fit line through the 5 points {(2,2), (0,0), (-2,-2), (-1,1), (1,-1)}

4. General Regression – not just straight line Least Squares Approximation Introduction to Algorithms, Cormen, et al., MIT Press

11. Least Squares Approximation Pseudoinverse of Matrix A - Linear Example On Whiteboard Compute the equation for the least - squares, best-fit line through the 5 points {(2,2), (0,0), (-2,-2), (-1,1), (1,-1)}

12. Linear Regression versus Principal Component Analysis Linear RegressionPrincipal Component Analysis Reference

13. Linear Regression versus Reverse Linear Regression Linear RegressionReverse Linear Regression Reference