ROW-COLUMN DESIGNS: A NOVEL APPROACH FOR ANALYZING IMPRECISE AND UNCERTAIN OBSERVATIONS
Abdulrahman AlAita, Muhammad Aslam, Florentín Smarandache · Advances and Applications in Statistics · 2024
Classical row-column designs cannot be applied when the underlying data set contains some imprecise, uncertain, or undetermined observations. In this paper, we discuss row-column design under a neutrosophic statistical framework. A significant contribution of our study is to propose a novel approach to analyzing row-column designs using neutrosophic data. This approach involves calculating the neutrosophic analysis of variance (NANOVA) table for the proposed design and using it to derive the -test in an uncertain environment. Two numerical examples have been used to assess the proposed design’s performance. Results from the study indicated that a row-column design under neutrosophic statistics was more efficient than a row-column design under classical statistics in the presence of uncertainty. Received: January 1, 2024Accepted: March 28, 2024