The researchers compared different ways to estimate data without being thrown off by unusual values. They found that traditional methods can be easily influenced by these outliers, leading to inaccurate results. By using more robust estimators and nonparametric regression, which doesn't rely on specific assumptions, they were able to get more accurate conclusions about the data they were studying.