robust statistics

Robust statistics are methods designed to analyze data accurately even when there are unusual or outlier values that don't follow the typical pattern. Traditional statistical techniques can be heavily influenced by these outliers, leading to misleading results. Robust methods aim to provide reliable summaries and conclusions by minimizing the impact of such atypical data points. This approach ensures more trustworthy insights, especially in real-world situations where data often contains errors, anomalies, or rare events. Overall, robust statistics help researchers and analysts make better decisions when dealing with imperfect or messy data.