Giulio D'agostini – författare

This book provides a multi-level introduction to Bayesian reasoning (as opposed to “conventional statistics”) and its applications to data analysis. The basic ideas of this “new” approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide — under well-defined assumptions! — with “standard” methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework.

This workshop is the fourth of a series initiated in Durham (March 93), followed by Eilat (February 94) and Paris (April 95). The large interest and the great inflow of experimental data, coming mainly from HERA, are some of the reasons behind the decision to have this annual meeting, presently the most important one for this area of research. During the workshop, experimental results and theoretical aspects have been reported on subjects, which have been organised by working groups on: 1) hadron structure functions; 2) photoproduction and photon structure; 3) diffractive interactions; 4) hadronic final states; 5) spin effects in lepton nucleon scattering; 6) special session on theoretical advances. While the contributions to the working groups offer hot material for specialists, the reports by the conveners, as well as other contributions to the plenary sessions, offer to nonspecialists a complete overview of this research field.