Estimating the Linear Equation Using the Method of Least Squares
1. Looks at differences between actual values (Y) & predicted values (Y). ‘Best fit’ tries to make these small
- But positive differences offset negative
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2. MLS minimizes the sum of the squared differences (or errors)