Associations between two variables, for instance between brain and behavioral measurements, are often studied using correlations, and in particular Pearson correlation. However, Pearson correlation is not robust: outliers can introduce false correlations or mask existing ones. These problems are exacerbated in brain imaging by a widespread lack of control for multiple comparisons, and several i...

The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlate...

This paper adds one more contribution to the large literature on binomial confidence intervals for small samples (e.g., Clopper and Pearson 1934; Pearson and Hartley 1954; Sterne 1954; Crow 1956; Blyth and Still 1983; Blyth 1986; Santner and Duffy 1989; Agresti and Coull 1998; Henderson and Meyer 2001). Clopper and Peason (1934) gave the first two-sided binomial confidence intervals, in graphic...