Robust regression refers to a set of statistical techniques designed to provide reliable estimates in the presence of outliers or violations of assumptions that typically underlie ordinary least squares regression. These techniques aim to minimize the influence of atypical observations, leading to more accurate and stable parameter estimates. Robust regression is particularly useful in real-world data analysis where data may not conform strictly to model assumptions, ensuring that conclusions drawn from the data are more trustworthy.
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