A statistical outlier is a data point that significantly differs from other observations in a dataset. It is often identified using methods such as the IQR (Interquartile Range) or Z-scores, which help determine how far a value deviates from the mean or median. Outliers can indicate variability in the data, measurement errors, or unique phenomena. Identifying outliers is important in data analysis because they can skew results and affect statistical conclusions. In fields like finance, healthcare, and social sciences, recognizing outliers helps researchers and analysts make more accurate interpretations and decisions based on the data.