Sums of squares are commonly used in statistics to partition the variability in a measurement, allowing us to attribute how much of the variability can be explained by another variable or variables, and how much is unexplained. In regression, the proportion of variability in the dependent variable that is explained by its linear relationship with the independent variable is known as R2, or the “coefficient of determination.” Although R2 is a commonly used statistic to measure how well a regression line fits the data, it doesn’t tell the whole story.
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Notes on the video: R2, The Coefficient of Determination