Intro Stats, Lec 5B, Correlation & Regression (& application to Joe Mauer's Baseball Statistics)

(0:00) Will be quickly going over a lot of material.
(0:43) Scatterplots for Joe Mauer, his Home Run totals and Batting Averages per season. Either could be the explanatory variable and either could be the response variable. The correlation is the same either way.
(1:44) Summary of correlation facts.
(2:33) Mathematica demonstration of how changing the viewing window might seem to change the correlation, but it doesn't.
(4:55) More properties about correlation.
(6:09) Formulas for finding the slope and intercept of a regression line. Keep track of order of operations.
(8:14) Facts about least squares regression lines. Include discussion of general linear equations and how to find the change in y ("delta y") when you know the slope and the change in x ("delta x"). This is key to interpreting the slope as a rate of change. Include a discussion of the coefficient of determination and how it measures the strength of the linear relationship.
(13:50) What's the regression line used for?
(16:01) Regression lines on a spreadsheet for Joe Mauer's data about home runs and batting averages. Use the equations for estimation/prediction. Interpret the slope.
(22:41) Warning: swapping the variables and finding the new regression line is NOT the same as finding the inverse function of the original.
(23:50) Residuals and residual plots.
(26:24) Cautions about correlation and regression.
(27:18) Read about sampling techniques, especially simple random sampling. Will be using a table of random digits.

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[achmeineye]

This is an awesome example but it depresses me.