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Bivariate Data: Each data point has two values. The form is $(x,y)$ .
Line of Best Fit or Least Squares Line (LSL): $\hat{y}=a+\text{bx}$
$x$ = independent variable; $y$ = dependent variable
Residual: $\text{Actual y value}-\text{predicted y value}=y-\hat{y}$
Sum of Squared Errors (SSE): The smaller the SSE , the better the original set of points fits the line of best fit.
Outlier: A point that does not seem to fit the rest of the data.
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