The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis testing, e.g. to test for normality of residuals, to test whether two samples are drawn from identical distributions (see Kolmogorov–Smirnov test), or whether outcome frequencies follow a specified distribution (see Pearson's chi-squared test). In the analysis of variance, one of the components into which the variance is partitioned may be a lack-of-fit sum of squares.
Read more about Goodness Of Fit: Fit of Distributions, Regression Analysis, Other Measures of Fit
Famous quotes containing the words goodness of, goodness and/or fit:
“Thank God, I never was cheerful. I come from the happy stock of the Mathers, who, as you remember, passed sweet mornings reflecting on the goodness of God and the damnation of infants.”
—Henry Brooks Adams (1838–1918)
“Great is your faithfulness, O God, Creator,
with you no shadow of turning we see.
You do not change, your compassions they fail not;
all of your goodness forever will be.”
—Thomas O. Chisholm (1866–1960)
“If you want a golden rule that will fit everything, this is it: Have nothing in your houses that you do not know to be useful or believe to be beautiful.”
—William Morris (1834–1896)