M estimation is a robust regression technique that assigns a weight to each observation based on the magnitude of the residual for that observation. Large residuals are downweighted (assigned weights less than 1) whereas observations with small residuals are given weights close to 1. By iterating the reweighting and fitting
Building a data and analytics culture in higher education means equipping key stakeholders with the skills necessary to analyze and leverage insights extracted from data. Doing so can drive faster, more accurate decision-making. When I hear “data and analytics culture,” I immediately think of the work Jason Simon and his team
An early method for robust regression was iteratively reweighted least-squares regression (Huber, 1964). This is an iterative procedure in which each observation is assigned a weight. Initially, all weights are 1. The method fits a least-squares model to the weighted data and uses the size of the residuals to determine
