Francis Galton's invention of correlation dates from late in the year 1888, and it arose when he recognized a common thread in three different scientific problems he was studying. Galton's own 1890 account of the moment of discovery is discussed and contrasted with Karl Pearson's widely known association of correlation with a retreat into a recess at Naworth Castle. The circumstances that led Galton to write the account are reviewed.

This is a review of the current state of the "theory of shape" introduced by the author in 1977. It starts with a definition of "shape" for a set of $k$ points in $m$ dimensions. The first task is to identify the shape spaces in which such objects naturally live, and then to examine the probability structures induced on such a shape space by corresponding structures in $\mathbf{R}^m$. Against this theoretical background one formulates and solves statistical problems concerned with shape characteristics of empirical sets of points. Some applications (briefly sketched here) are to archeology, astronomy, geography and physical chemistry. We also outline more recent work on "size-and-shape," on shapes of sets of points in riemannian spaces, and on shape-theoretic aspects of random Delaunay tessellations.

In applying for a research grant, a young statistician or probabilist faces keen competition for limited funds. The quality of the research proposed and the qualifications of the researcher are major criteria in evaluating a project for funding. However, chances for funding can be improved if the application is carefully written, based upon an understanding of how it will be evaluated. In applying for support, the young researcher should consider the advantages and disadvantages of the various opportunities for funding. Specifics of the discussion center upon the National Science Foundation of the United States government.

"Grouped" data are defined to be the result of observing continuous variables only up to the nearest interval, rectangle or triangle. This paper traces the development of statistical methods for grouped data, focusing on the major results and their interpretations. It emphasizes the impact of likelihood and Bayesian ideas on the analysis of grouped data, particularly as they influence current work.