Outliers are data points that significantly deviate from the rest of the observations in a dataset, and their significance in frequency distribution lies in their potential to skew statistical analyses. They can arise from various sources, including measurement errors or genuine novel phenomena. The presence of outliers can distort key statistical measures such as the mean, which is sensitive to extreme values, leading to misleading interpretations of central tendency. For instance, while the mean may be heavily influenced by an outlier, the median remains more stable and often provides a better representation of the typical value in skewed distributions.