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The residuals in regression estimation are estimates of error. Most commonly, the errors are assumed to be statistically independent, identically distributed and normally distributed, that is, to have a Gaussian distribution.

If these were the assumptions under which the regression was calculated then the residuals could (at least potentially) be examined for any departures from the assumptions. Usually they are plotted against the independent variable to see if there is any systematic relationship between the two sets of values. The residuals might also be tested for normality.

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Q: How do you interpret residual values?

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