Correlation evaluation with fuzzy data and its application in the management science. (English) Zbl 1407.62435
Huynh, Van-Nam (ed.) et al., Econometrics of risk. Cham: Springer. Stud. Comput. Intell. 583, 273-285 (2015).
Summary: How to evaluate an appropriate correlation with fuzzy data is an important topic in the educational and psychological measurement. Especially when the data illustrate uncertain, inconsistent and incomplete type, fuzzy statistical method has some promising features that help resolving the unclear thinking in human logic and recognition. Traditionally, we use Pearson’s Correlation Coefficient to measure the correlation between data with real value. However, when the data are composed of fuzzy numbers, it is not feasible to use such a traditional approach to determine the fuzzy correlation coefficient. This study proposes the calculation of fuzzy correlation with three types of fuzzy data: interval, triangular and trapezoidal. Empirical studies are used to illustrate the application for evaluating fuzzy correlations. More related practical phenomena can be explained by this appropriate definition of fuzzy correlation.
For the entire collection see [Zbl 1341.91005].
For the entire collection see [Zbl 1341.91005].
MSC:
| 62P25 | Applications of statistics to social sciences |
| 62M86 | Inference from stochastic processes and fuzziness |
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