The concept of normality generalizes to orthogonality. There are statistical methods to empirically test that assumption, see the above Normality tests section. ANOVA is a relatively robust procedure with respect to violations of the normality assumption. One application of normality tests is to the residuals from a linear regression model. Deviations from a straight line suggest departures from normality. The F statistic is distributed F under assumption of null hypothesis and normality assumption. Residuals are examined or analyzed to confirm homoscedasticity and gross normality. This gives rise to the normality assumption of Tukey's test. The F statistic is distributed F under assuming of null hypothesis and normality assumption. Bootstrapping does not rely on the assumption of normality. Slowly, her daily life returns to some sense of normality. Grubbs's test is based on the assumption of normality. Normality, and abnormality, can be characterized statistically. Attempts to define the boundaries of normality are controversial. Relations between the two states assumed a veneer of normality.