I think Sir Ronald Fisher is the statistics equivalent to Leibniz in my mind. Check it:

…this paper laid the foundation for what came to be known as biometrical genetics, and introduced the very important methodology of the analysis of variance, which was a considerable advance over the correlation methods used previously.

The freaking ANOVA, people.

In addition to “analysis of variance”, Fisher invented the technique of maximum likelihood and originated the concepts of sufficiency, ancillarity, Fisher’s linear discriminator and Fisher information. His 1924 article “On a distribution yielding the error functions of several well known statistics” presented Karl Pearson’s chi-squared and Student’s t in the same framework as the Gaussian distribution, and his own “analysis of variance” distribution Z (more commonly used today in the form of the F distribution). These contributions easily made him a major figure in 20th century statistics.

Do you know what the Z distribution is? It’s used for setting confidence intervals around correlation estimates. Since a correlation is bound by -1 and 1, any sampling distribution with a mean correlation other than zero has a skewed distribution, and thus requires unsymmetrical confidence intervals to be set. Fisher’s Z distribution is a non-linear transformation of correlations that FORCES THEM INTO A NORMAL DISTRIBUTION in which you can set symmetrical confidence intervals, and then you can TRANSFORM THOSE LIMITS BACK and get confidence intervals in the original sampling distribution of correlations.

Seriously, that’s pretty freaking amazing. This guy rocked. Go search him in Wikipedia and see the  massive list of “see also” pages.