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Sensitivity analysis has several limitations, including its dependence on the assumptions made in the model; if the model is flawed, the results can be misleading. It typically examines one variable at a time while holding others constant, which may not reflect real-world interactions or correlations among variables. Additionally, it can oversimplify complex systems by failing to account for non-linear relationships and may not capture the full range of uncertainty inherent in the inputs. Lastly, sensitivity analysis does not provide information on the probability of outcomes, limiting its usefulness in decision-making under uncertainty.

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