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    <title>Sensitivity-Analysis on Pi Stack</title>
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      <title>Uncertainty Quantification in Python in 2026: SALib vs Chaospy vs EasyVVUQ</title>
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      <description>&lt;p&gt;Your model has eleven input parameters, four of which are measured with 15 per cent error, and you have been reporting a single deterministic number — a mean from one run at nominal values — as if it were a prediction. That is the most common methodological failure in computational engineering, and it is a statistics problem, not a modelling problem. Uncertainty quantification (UQ) is the discipline of propagating input uncertainty to output uncertainty, and decomposing which inputs actually drive the spread.&lt;/p&gt;</description>
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