Why do we square the residuals when using the least-squares line method to find the line of best fit?

1 answer:

4 0

We square the residuals when using the least-squares line method to find the line of best fit because we believe that huge negative residuals (i.e., points well below the line) are just as harmful as large positive residuals (i.e., points that are high above the line).

<h3>What do you mean by Residuals?</h3>

We treat both positive and negative disparities equally by squaring the residual values. We cannot discover a single straight line that concurrently minimizes all residuals. The average (squared) residual value is instead minimized.

We might also take the absolute values of the residuals rather than squaring them. Positive disparities are viewed as just as harmful as negative ones under both strategies.

To know more about the Least-Squares Line method, visit:

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fenix001 [56]

Answer:

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$\huge{\boxed{\frac{1}{4}}}\ \ \huge{\boxed{\frac{1}{4}}}$

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