This paper addresses the problem of estimating fault tolerance coverage thr
ough statistical processing of observations collected in fault-injection ex
periments. In an earlier paper, various estimators based on simple sampling
in the complete fault/activity input space and stratified sampling in a pa
rtitioned space were studied; frequentist confidence limits were derived ba
sed on a normal approximation. In this paper, the validity of this approxim
ation is analyzed. The theory of confidence regions is introduced to estima
te coverage without approximation when stratification is used. Three statis
tics are considered for defining confidence regions. It is shown that one-a
vectorial statistic-is often more conservative than the other two. However
, only the vectorial statistic is computationally tractable. We then consid
er Bayesian estimation methods for stratified sampling. Two methods are pre
sented to obtain an approximation of the posterior distribution of the cove
rage by calculating its moments. The moments are then used to identify the
type of the distribution in the Pearson distribution system, to estimate it
s parameters, and to obtain the coverage confidence limit. Three hypothetic
al example systems are used to compare the validity and the conservatism of
the frequentist and Bayesian estimations.