The study looked at a method to find unusual data points in time series data. The method was designed to find outliers by assuming the data had a certain pattern. The researchers found that the method worked well when looking for one outlier, but when used to find multiple outliers, it often found too many. They discovered that the method was flawed when used iteratively and figured out the correct way to analyze the data at each step of the search.