This statistic is used to evaluate the statistical significance of parameter estimates computed via maximum likelihood methods. It is also sometimes called the efficient score statistic. The test is based on the behavior of the log-likelihood function at the point where the respective parameter estimate is equal to 0.0 (zero); specifically, it uses the derivative (slope) of the log-likelihood function evaluated at the null hypothesis value of the parameter (parameter = 0.0). While this test is not as accurate as explicit likelihood-ratio test statistics based on the ratio of the likelihoods of the model that includes the parameter of interest, over the likelihood of the model that does not, its computation is usually much faster. It is therefore the preferred method for evaluating the statistical significance of parameter estimates in stepwise or best-subset model building methods.

In Statistica, the score statistic is, for example, computed in the Generalized Linear Models module. An alternative statistic is the Wald statistic.