In statistical inference hypotheses related to different kinds of phenomena are formulated,
and then data are collected and analyzed, which either confirm or falsify these hypotheses …

Empirical trimmed means have been studied in general spaces and, in particular, they have
been applied to the one-dimensional fuzzy case. They provide a competing robust …

In previous papers, it has been empirically proved that descriptive (summary measures) and
inferential conclusions (in particular, tests about means p-values) with imprecise-valued …

In analyzing fuzzy-valued imprecise data statistically, scale measures/estimates play an
important role. Scale measures/estimates of data sets are often considered, among others …

In this article, we propose the generalized one-tailed hypergeometric test with fuzzy
hypotheses for both test methods: significance testing (by controlling the type I error) and …

With the rapid development of the shipping transportation, the comfort of the cabin
environment is becoming increasingly critical. This paper presents a comprehensive comfort …

Measuring psychological variables (attitudes, opinions, perceptions, feelings, etc.) there is a
need for rating scales coping with both the natural imprecision and individual differences. In …

Computer simulations are a powerful tool in many fields of research. This also applies to the
broadly understood analysis of experimental data, which are frequently burdened with …

Different approaches to robustly measure the location of data associated with a random
experiment have been proposed in the literature, with the aim of avoiding the high sensitivity …

A typical two-sample problem we deal with in statistical reasoning is to conclude whether the
distributions of these samples differ significantly. In other words, we want to know if the given …