  This paper offers examples of concrete numerical applications of Bayesian
quantum-state assignment methods to a three-level quantum system. The
statistical operator assigned on the evidence of various measurement data and
kinds of prior knowledge is computed partly analytically, partly through
numerical integration (in eight dimensions) on a computer. The measurement data
consist in the average of outcome values of N identical von Neumann projective
measurements performed on N identically prepared three-level systems. In
particular the large-N limit will be considered. Three kinds of prior knowledge
are used: one represented by a plausibility distribution constant in respect of
the convex structure of the set of statistical operators; another one
represented by a prior studied by Slater, which has been proposed as the
natural measure on the set of statistical operators; the last prior is
represented by a Gaussian-like distribution centred on a pure statistical
operator, and thus reflecting a situation in which one has useful prior
knowledge about the likely preparation of the system. The assigned statistical
operators obtained with the first two kinds of priors are compared with the one
obtained by Jaynes' maximum entropy method for the same measurement situation.
In the companion paper the case of measurement data consisting in absolute
frequencies is considered.
