Often multivariable observations may not be detected as outliers when each variable is considered independently. In such situations outlier detection can only be successfully done when multivariate analysis is performed, and the interactions among different variables examined. With the aid of a diagrammatic illustration, given an example of how an outlier in a bivariate distribution may be confused as an inlier if each dimension of the bivariate distribution is treated as a distinct univariate distribution.