Error tolerance refers to the capacity of a system or method to withstand errors or inaccuracies in data and still produce acceptable outcomes. It is essential in ensuring the reliability of computer-generated results, especially when models are complex and subject to uncertainties. By defining acceptable levels of error, engineers and analysts can better validate and interpret results, ensuring that decisions made based on these outputs are sound and trustworthy.
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