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For two qualitative variables (nominal or ordinal in level of measurement), a contingency table can be used to view the data, and a measure of association or a test of independence could be used. [3] If the variables are quantitative, the pairs of values of these two variables are often represented as individual points in a plane using a ...
The first scatterplot is formed from the points (d 1 α u 1i, d 2 α u 2i), for i = 1,...,n. The second plot is formed from the points (d 1 1−α v 1j, d 2 1−α v 2j), for j = 1,...,p. This is the biplot formed by the dominant two terms of the SVD, which can then be represented in a two-dimensional display.
Other correlation coefficients or analyses are used when variables are not interval or ratio, or when they are not normally distributed. Examples are Spearman’s correlation coefficient, Kendall’s tau, Biserial correlation, and Chi-square analysis. Pearson correlation coefficient
The points inside a curve labelled S represent elements of the set S, while points outside the boundary represent elements not in the set S. This lends itself to intuitive visualizations; for example, the set of all elements that are members of both sets S and T , denoted S ∩ T and read "the intersection of S and T ", is represented visually ...
Statistical graphics have been central to the development of science and date to the earliest attempts to analyse data. Many familiar forms, including bivariate plots, statistical maps, bar charts, and coordinate paper were used in the 18th century.
When modelling relations between two different classes of objects, bipartite graphs very often arise naturally. For instance, a graph of football players and clubs, with an edge between a player and a club if the player has played for that club, is a natural example of an affiliation network, a type of bipartite graph used in social network analysis.
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The key fact is that a nonroot vertex v is a cut vertex (or articulation point) separating two biconnected components if and only if there is a child y of v such that lowpoint(y) ≥ depth(v). This property can be tested once the depth-first search returned from every child of v (i.e., just before v gets popped off the depth-first-search stack ...