Abstract
Ranked set sampling is a sampling design that allows the experimenter to span the full range values in the population and it can be used widely in industrial, environmental and ecological studies. In this paper, we consider the information content of ranked set sampling in terms of extropy measure. It is shown that the ranked set sampling performs better than its simple random sample counterpart of the same size. Monotone properties and stochastic orders are investigated. Sharp bounds on the extropy of RSS data based on the projection method in the non-parametric set-up as well as Steffensen inequalities in the parametric context are established. The extropy measure can also be used as a discrimination tool between RSS and SRS data.