Iranian Statistical Society Journal of the Iranian Statistical Society 1726-4057 25 1 2026 06 01 A novel parametric correlation coefficient for intuitionistic fuzzy numbers 127 148 738152 10.22034/jirss.2026.2082115.1173 EN Zahra Behdani Department of Mathematics and Statistics, Faculty of Energy and Data Sciences, Behbahan Khatam Alanbia University of Technology, Khouzestan, Iran. Journal Article 2025 12 26 Correlation coefficients are widely used to measure the relationship between variables, but existing approaches for intuitionistic fuzzy numbers (IFNs) often fail to capture negative dependence and lack flexibility. In this paper, we propose a novel parametric correlation coefficient for IFNs based on a newly defined difference operator. The proposed method allows the correlation value to vary within the interval $[-1, 1]$, enabling the representation of both positive and negative relationships. Moreover, by introducing parameters $\alpha$ and $\beta$, the method provides flexibility for decision-makers to evaluate correlations at different levels. Numerical examples and applications in medical diagnosis and multi-criteria decision-making demonstrate the effectiveness, robustness, and practical applicability of the proposed approach. Correlation coefficients are widely used to measure the relationship between variables, but existing approaches for intuitionistic fuzzy numbers (IFNs) often fail to capture negative dependence and lack flexibility. https://jirss.irstat.ir/article_738152_dc3479382dd9378558991bc63f132b8f.pdf