The Robust Fit option attempts to reduce the influence of outliers in your data set. In this instance, outliers are an observation that does not come from the “true” underlying distribution of the data. For example, if weight measurements were being taken in pounds for a sample of individuals, but one of the individuals accidentally recorded their weight in kilograms instead of pounds, this would be a deviation from the true distribution of the data. Outliers such as this could lead you into making incorrect decisions because of their influence on the data. The Robust Fit option reduces the influence of these types of outliers.