Anscombe's quartet (Anscombe, 1973) are a set of four two-variable datasets that have several common summary statistics but which have very different joint distributions. This becomes apparent when the data are plotted, which illustrates the importance of using graphical displays in Statistics. This package enables the creation of datasets that have identical marginal sample means and sample variances, sample correlation, least squares regression coefficients and coefficient of determination. The user supplies an initial dataset, which is shifted, scaled and rotated in order to achieve target summary statistics. The general shape of the initial dataset is retained. The target statistics can be supplied directly or calculated based on a user-supplied dataset.


The main functions in anscombiser are

  • anscombise, which modifies a user-supplied dataset so that it shares sample summary statistics with Anscombe's quartet.

  • mimic, which modified a user-supplied dataset so that is shares sample summary statistics with another user-supplied dataset.

See vignette("intro-to-anscombiser", package = "anscombiser") for an overview of the package.


Anscombe, F. J. (1973). Graphs in Statistical Analysis. The American Statistician 27 (1): 17–21.

See also