EstimatedVariance

As of Version 7.0, EstimatedVariance has become a property of LinearModelFit and NonlinearModelFit.

EstimatedVariance

is a possible value for the RegressionReport option which represents the estimated error variance.

Details and Options

To use EstimatedVariance, you first need to load the Regression Common Functions Package. You can do this by using Needs["LinearRegression`"] or Needs["NonlinearRegression`"], which will automatically load the Regression Common Functions Package, or you can load the package directly by using Needs["RegressionCommon`"].
EstimatedVariance is equivalent to the squared sum of FitResiduals divided by the degrees of freedom n-p where n is the length of the dataset and p is the number of parameters.

Wolfram Language code: Needs["LinearRegression`"]

Sample data:

Wolfram Language code:

data = {{0.05, 90}, {0.09, 95}, {0.14, 110}, 
{0.17, 125}, {0.2, 140}, {0.21, 150}, 
{0.23, 175}, {0.25, 190}, {0.3, 210}, 
{0.35, 255}};

EstimatedVariance for a linear regression:

Wolfram Language code: Regress[data, {1, x ^ 2}, x, RegressionReport -> {EstimatedVariance}]

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