Data from: Graphs in phylogenetic comparative analysis: Anscombe’s quartet revisited

1. In 1973 the statistician Francis Anscombe used a clever set of
bivariate datasets (now known as Anscombe’s quartet) to illustrate the
importance of graphing data as a component of statistical analyses. In his
example, each of the four datasets yielded identical regression
coefficients and model fits, and yet when visualized revealed strikingly
different patterns of covariation between x and y. 2. Phylogenetic
comparative methods are statistical methods too, yet visualizing the data
and phylogeny in a sensible way that would permit us to detect unexpected
patterns or unanticipated deviations from model assumptions is not a
routine component of phylogenetic comparative analyses. 3. Here, we use a
quartet of phylogenetic datasets to illustrate that the same estimated
parameters and model fits can be obtained from data that were generated
using markedly different procedures – including pure Brownian motion
evolution and randomly selected data uncorrelated with the tree. Just as
in the case of Anscombe’s quartet, when graphed the differences between
the four datasets are quickly revealed. 4. The intent of this article is
to help build the general case that phylogenetic comparative methods are
statistical methods and consequently that graphing or visualization should
invariably be included as an essential step in our standard data
analytical pipelines. 5. Phylogenies are complex data structures and thus
visualizing data on trees in a meaningful and useful way is a challenging
endeavor. We recommend that the development of graphical methods for
simultaneously visualizing data and tree should continue to be an
important goal in phylogenetic comparative biology.