A measure of agreement between the observed values of a random variable and corresponding values derived according to a theoretical model, or an hypothesis under test.

A measure of how well observed data conform to a specified, expected, or theoretical probability distribution.

The statistical resemblance of real data to a model, expressed as a strength or degree of fit of the model (statistics). [8

tests are statistical tests (like Chi-square test, ANOVA, Kolmogorov-Smirnov test, etc.) that determine fit of empirical distribution to a tested distribution. [pg 129-135, 3

How well the regression line "fits" the data, i.e., the amount of variation in the dependent variable that is accounted for by variation in the independent variable.

In general terms, a quantitative measure of the ability of an assumed functional form to fit a given set of data. In meteorology, "goodness of fit" usually refers to the size of the residual variance for a regression function used to fit a set of data. See regression.

Goodness of fit means how well a statistical model 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-square test).