Outliers are data points that stand out from the rest of a dataset. They are significantly higher or lower than the other values, which can indicate unusual behavior or errors in data collection. For example, if most students in a class score between 70 and 90 on a test, but one student scores 30, that score is an outlier. Identifying outliers is important because they can skew results and affect conclusions. In fields like statistics and data analysis, recognizing outliers helps researchers understand patterns and make better decisions. Sometimes, outliers can reveal interesting insights or trends that are worth exploring further.