Explain the term "outlier."

The term "outlier" refers to a data point that significantly differs from other observations in the dataset. This could mean that its value is much higher or much lower than most of the data points, which can affect statistical analyses and interpretations. Outliers can arise due to variability in the data or may indicate that there are measurement errors or special conditions affecting those data points.

Identifying outliers is crucial in statistics because they can skew results, impact the mean and standard deviation, and influence the conclusions drawn from the data analysis. For example, if an outlier is present in a dataset of heights, it could represent an exceptionally tall or short individual, which would not reflect the central tendency of the group.

While the other options provide different statistical concepts, they do not accurately capture the definition of an outlier. Concepts such as averages, repeated values, or strategies to eliminate variations focus on different aspects of data analysis rather than identifying points that stand out significantly from a dataset.