The technique minimizes the sum of the squared residuals. However, the Ordinary Least Square ( OLS ) regression technique can help us to speculate on an efficient model. The calculation of the real values of intercept, slope, and residual terms can be a complicated task. A residual gives an insight into how good our model is against the actual value but there are no real-life representations of residual values. They are also referred to as error or noise terms. Residuals identify the deviation of observed values from the expected values.
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