# What is the sensitivity and how does it contribute to design robusteness?

Every contributor of the dependency graph has a nominal value and a sigma value, and the Solver computes the first partial differential of the mathematical equation to determine sensitivity values for each contributor (s = d(contributor)/d(analyzed dimension). Sensitivity actually represents the amplification effect of one specific contributor relative to the analysed dimension. In the following example, if the first contributor (FreeL) is changed by a value of 1, the analyzed variable (Ftot) will change by a value of 1.205.

Sensitivity can also be used to understand the relative importance of the tolerance interval versus the nominal value of a contributor. In the previous example, the second contributor (d) has a very high sensitivity (278). That means that its impact on the output dimension comes mainly from its nominal value (0.5) and not from its tolerance interval (+/- 0.0025). Remember that the % of Contribution is the combined effect of both the tolerance interval and the sensitivity.

Note that the worst case analysis also uses sensitivity values to provide a linear estimate of the outcome based on contributor values being at maximum and minimum tolerance limits.

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