The last variable ("Survived") is finally applied, this time along the left edge with the result highlighted by shade: dark grey rectangles represent people that did not survive the disaster, light grey ones people that did. Women in the first class are immediately seen to have had the highest survival probability. The survival probability for females is seen to have been higher than that for men (marginalised over all classes). Similarly, a marginalization over gender identifies first-class passengers as most probable to survive. Overall, about 1/3 of all people survived (proportion of light gray areas). Properties The displayed variables are categorical or ordinal scales. The plot is of at least two variables. There is no upper limit, but too many variables may be confusing in graphic form. The number of observations is not limited, but not read in the image. The areas of the rectangular tiles that are available for a combination of features are proportional to the number of observations that have this combination of features. Unlike, for example, the boxplot or QQ plot, it is not possible for the mosaic plot to plot a confidence interval. However, the tiles can be colored according to the standardized residual from a model of independence, so that cells with excessively large or small deviations are shaded to show those that are 'significant' and the pattern of association can be discerned. Criticism The mosaic plot has been criticised for making the data hard to perceive and to compare visually, because the values correspond to areas. See also Heat map Treemap Contingency table References Further reading John Hartigan, Beat Kleiner: Mosaics for contingency tables. In: Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface. 1981, S. 268–273. Michael Friendly: A Brief History of the Mosaic Display In: Journal of Computational and Graphical Statistics, 2002, 11, 89-107. [The earliest known mosaic display goes back to Georg von Mayr (1877).] Statistical charts and diagrams