The book provides a generalization of Gaussian error intervals to
situations where the data follow non-Gaussian distributions. This
usually occurs in frontier science, where the observed parameter is
just above background or the histogram of multiparametric data
contains empty bins. Then the validity of a theory
cannot be decided by the chi-squared-criterion, but this long-standing
problem is solved here. The book is based on Bayes' theorem, symmetry and
differential geometry. In addition to solutions of practical problems, the text
provides an epistemic insight: The logic of quantum mechanics is
obtained as the logic of unbiased inference from counting data.
However, no knowledge of quantum mechanics is required. The text,
examples and exercises are written at an introductory level.
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