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We give a geometrically motivated measure of skewness, define a mean valuetriangle number, and dispersion (in that order) of a fuzzy number withoutreference or seeking analogy to the namesake but parallel concepts inprobability theory. These measures come about by way of a new representation offuzzy numbers as parameterized curves respectively their associated tangentbundle. Importantly skewness and dispersion are given as functions of $\alpha$(the degree of membership) and such may be given separately and pointwise ateach $\alpha$-level, as well as overall. This allows for e.g., when amathematical model is formulated in fuzzy numbers, to run optimization programslevel-wise thereby encapsuling with deliberate accuracy the involved membershipfunctions' characteristics while increasing the computational complexity byonly a multiplicative factor compared to the same program formulated in realvariables and parameters. As an example the work offers a contribution to therecently very popular fuzzy mean-variance-skewness portfolio optimization.

New definitions (measures) of skewness, mean and dispersion of fuzzy numbers -- by way of a new representation as parameterized curves