A value that falls outside the expected range of data can best be described as what?

A value that falls outside the expected range of data is best described as an outlier. Outliers are defined as observations that deviate significantly from the rest of the data, making them stand out due to their distance from the central tendency of the dataset. Identifying outliers is crucial in data analysis, as they can affect the results of statistical tests and can provide insights into variability, data quality, or unique phenomena within the data.

While the term anomaly can also indicate a deviation from the norm, it is often used in specific contexts such as fraud detection or network security, where the focus is on unexpected patterns. Variance refers to a statistical measure of the dispersion of data points, but it does not specifically denote individual data points that lie outside a typical range. A statistical error usually refers to the incorrect calculation or inference resulting from data analysis, rather than the characterization of a singular value within the data set.

In summary, outliers are specifically identified values in a dataset that do not conform to the expected range, making them the most fitting term for the scenario described.