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Edlintics

Standard error of the estimate

The standard error of the estimate measures how far actual data points typically fall from a fitted regression line, computed from the error sum of squares and used to build prediction intervals and test the slope's significance.

ByHoang TruongUpdated

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Five months of machine hours and maintenance cost produce residuals of €4, −€3, €0, −€7 and €6, squaring and summing to an error sum of squares of 110. With n − 2 = 3 degrees of freedom, the standard error of the estimate is √(110 ÷ 3) = €6.06 — the typical distance between actual cost and the fitted line.

Where it fits
SubjectData Analysis & StatisticsAdvancedTopicSimple Linear Regression & OLSAdvanced

The formula

LaTeX
SEE=SSEn−2SEE = \sqrt{\dfrac{SSE}{n-2}}

Variables

Error sum of squares (squared units of y)
Number of observations

Estimates the typical distance between actual values and the fitted regression line, using n − 2 degrees of freedom for a simple regression.

Standard error of the estimate — Edlintics Glossary