Describe how data outliers might be revealed in histograms and stem-and-leaf plots. A. Any large values might indicate potential outliers. B. Any small values might indicate potential outliers. C. Any large gaps between bars or stems might indicate potential outliers. D. Large concentrations of data values might indicate potential outliers.

C - Any large gaps between bars or stems might indicate potential outliers.

Step-by-step explanation:

An outlier can be observed from histogram when such value (s) stands at distance to others. In this sense, the bar will be distinct from other bars. Similarly in stem and leaf, such value (s) will distinctly far from other distributed values. We must also say that, outlier (s) can be lower outlier (s). That is, when such value (s) is extremely smaller compare to majority and even far from actual minimum. We also have higher outlier (s), when the value is far higher compare to other distributed values and far from the actual maximum.