An introduction to (refresher on) linear regression. The emphasis here is on SSR + SSE = SST. The coefficient of determination = SSR/SST = [correlation coefficient]^2. Further, I emphasize the standard error of the estimate (SEE). This is analogous to the standard deviation; it captures the dispersion of actual observations from the "predicted Y" line.

(20 min.)

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