Branch Mathematics and Statistics Faculty and Staff Publications
Document Type
Article
Publication Date
2024
Abstract
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 FN -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.
Publication Title
Advances and Applications in Statistics
Volume
91
Issue
5
First Page
657
Last Page
671
DOI
http://dx.doi.org/10.17654/0972361724035
Language (ISO)
English
Keywords
neutrosophic statistics, row-column design, neutrosophic data, neutrosophic analysis of variance
Recommended Citation
AlAita, Abdulrahman; Muhammad Aslam; and Florentin Smarandache.
"Row-column designs: a novel approach for analyzing imprecise and uncertain observations."
Advances and Applications in Statistics
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
