This book investigates the challenges and methodologies for computing statistical measures when data is characterized by interval and fuzzy uncertainty. It addresses the need for robust statistical analysis in fields where precise numerical data is unavailable or inherently imprecise. The work presents theoretical frameworks and practical algorithms for handling such uncertainties, drawing upon concepts from interval analysis and fuzzy set theory to provide a comprehensive approach to statistical computation.

The subject matter points to a dense, specialist text aimed at researchers and advanced students in statistics, mathematics, and related fields. The focus on interval and fuzzy uncertainty suggests a rigorous theoretical treatment rather than an introductory overview. The book likely offers novel approaches to handling data imprecision, appealing to those working with complex or ill-defined datasets.