The focus of this work is on generalizing the notion of variation in a
set of numbers to variation in a set of probability distributions. The
authors collect some known ways of comparing stochastic matrices in the
context of information theory, statistics, economics, and population
sciences. They then generalize these comparisons, introduce new
comparisons, and establish the relations of implication or equivalence
among sixteen of these comparisons. Some of the possible implications
among these comparisons remain open questions. The results in this book
establish a new field of investigation for both mathematicians and
scientific users interested in the variations among multiple probability
distributions. A great strength of this text is the resulting
connections among ideas from diverse fields - mathematics, statistics,
economics, and population biology. In providing this array of new tools
and concepts, the work will appeal to the practitioner. At the same
time, it will serve as an excellent resource for self-study or for a
graduate seminar course, as well as a stimulus to further research.