Not exactly since this generally is an analyst determination of whether or not extremes are viable but there are tests that can be run or distribution stats to help. There also are higher order stats like cluster analysis and/or association tests available.
My suggestion is to 1st plot the responses looking for outliers (generally defined as > +/-2 standard deviation but based on the type of data) and look at you skewness & kurtosis stats overall then by key demographics segments viewed side-by-side.
All this is preceded by an emphasis that the type of data (scaly, ordinal, nominal...) always affects what one accepts/looks for.
See the note below
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