1. Correlation and causality
Understanding why correlation does not imply causality (even though many in the press and some researchers often imply otherwise)
2. Fitting a line to data
Sal creates a scatter plot and then fits a line to data on the median California family income.
3. Estimating the line of best fit exercise
Sal solves a problem where he has to estimate the line of best fit for a scatter plot.
4. Eyeballing the line of best fit
Given a random assortment of points, draw a line of best fit through them.
5. Estimating slope of line of best fit
Given a scatter plot, can you estimate the slope of the line of best fit that goes through the data points?
6. Squared error of regression line
Introduction to the idea that one can find a line that minimizes the squared distances to the points
7. Proof (part 1) minimizing squared error to regression line
Proof (Part 1) Minimizing Squared Error to Regression Line
8. Proof (part 2) minimizing squared error to regression line
Proof Part 2 Minimizing Squared Error to Line
9. Proof (part 3) minimizing squared error to regression line
Proof (Part 3) Minimizing Squared Error to Regression Line
10. Proof (part 4) minimizing squared error to regression line
Proof (Part 4) Minimizing Squared Error to Regression Line
14. Example: Correlation coefficient intuition
Sal explains the intuition behind correlation coefficients and does a problem where he matches correlation coefficients to scatter plots.
15. Correlation coefficient intuition
Match correlation coefficients to scatterplots to build a deeper intuition behind correlation coefficients.