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While a two-dimensional ogive or a cross-section of a three-dimensional ogive may represent the shape of a given distribution, they are only good for representing higher-likelihood (one- and two-sigma) outcomes because ogives do not have characteristic low-likelihood tails tails.
For very well managed processes (better than four sigma accuracy), a custom ogive may provide a very good approximation of resulting distribution.
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