<P> Some systematists prefer to exclude taxa based on the number of unknown character entries ("?") they exhibit, or because they tend to "jump around" the tree in analyses (i.e., they are "wildcards"). As noted below, theoretical and simulation work has demonstrated that this is likely to sacrifice accuracy rather than improve it . Although these taxa may generate more most - parsimonious trees (see below), methods such as agreement subtrees and reduced consensus can still extract information on the relationships of interest . </P> <P> It has been observed that inclusion of more taxa tends to lower overall support values (bootstrap percentages or decay indices, see below). The cause of this is clear: as additional taxa are added to a tree, they subdivide the branches to which they attach, and thus dilute the information that supports that branch . While support for individual branches is reduced, support for the overall relationships is actually increased . Consider analysis that produces the following tree: (fish, (lizard, (whale, (cat, monkey)))). Adding a rat and a walrus will probably reduce the support for the (whale, (cat, monkey)) clade, because the rat and the walrus may fall within this clade, or outside of the clade, and since these five animals are all relatively closely related, there should be more uncertainty about their relationships . Within error, it may be impossible to determine any of these animals' relationships relative to one another . However, the rat and the walrus will probably add character data that cements the grouping any two of these mammals exclusive of the fish or the lizard; where the initial analysis might have been misled, say, by the presence of fins in the fish and the whale, the presence of the walrus, with blubber and fins like a whale but whiskers like a cat and a rat, firmly ties the whale to the mammals . </P> <P> To cope with this problem, agreement subtrees, reduced consensus, and double - decay analysis seek to identify supported relationships (in the form of "n - taxon statements," such as the four - taxon statement "(fish, (lizard, (cat, whale)))") rather than whole trees . If the goal of an analysis is a resolved tree, as is the case for comparative phylogenetics, these methods cannot solve the problem . However, if the tree estimate is so poorly supported, the results of any analysis derived from the tree will probably be too suspect to use anyway . </P> <P> A maximum parsimony analysis runs in a very straightforward fashion . Trees are scored according to the degree to which they imply a parsimonious distribution of the character data . The most parsimonious tree for the dataset represents the preferred hypothesis of relationships among the taxa in the analysis . </P>

What is the principle of maximum parsimony and the principle of maximum likelihood