Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…

Efron's Monte Carlo bootstrap algorithm is shown to cause degeneracies in Pearson's r for sufficiently small samples. Two ways of preventing this problem when programing the bootstrap of r are considered. (Author)

An algorithm and associated FORTRAN-77 computer subroutine are described for computing Goodman and Kruskal's tau-b statistic along with the associated nonasymptotic probability value under the null hypothesis tau=O. (Author)

Describes the algorithm used to select a simple random sample of certain size without having to list all possible samples and a justification based on Pascal's triangle. Provides testing results by various computers. (YP)