Standard Error of Estimate
Calculate Standard Error of Estimate instantly with the exact formula and a worked example.
Standard Error of Estimate
Sum of squared residuals (SSR)
Number of observations n
Number of predictors k
SEE
2.0702
Degrees of freedom
28
Mean squared error (MSE)
4.2857
More about: Standard Error of Estimate
What it calculates
The “Standard Error of Estimate” calculator computes SEE from 3 parameters: sum of squared residuals (ssr), number of observations n, number of predictors k.
A core calculation for studying, engineering tasks, and checking solutions.
Example calculation
With parameters Sum of squared residuals (SSR) = 120, Number of observations n = 30, Number of predictors k = 1 the result is 2.07.
How to use
- Enter sum of squared residuals (ssr), number of observations n and number of predictors k — each field above is adjustable with a slider.
- SEE is calculated automatically as you type.
- Check the worked example below to see the formula applied to real numbers.
- Copy the result or bookmark this calculator.
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FAQ
How is Standard Error of Estimate calculated?
The Standard Error of Estimate calculator computes SEE from sum of squared residuals (ssr), number of observations n, number of predictors k. Enter your values above and the exact formula is applied instantly; a worked example with real numbers is shown below.
Is the Standard Error of Estimate calculator free?
Yes. It is completely free, needs no signup, runs entirely in your browser, and sends no data to any server.
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