A trimmed mean is a statistical measure that calculates the average of a dataset after removing a certain percentage of the highest and lowest values. This process helps reduce the impact of outliers, which can skew the results. For example, if you have a set of test scores, trimming the top and bottom 10% can provide a more accurate representation of the central tendency. This method is particularly useful in fields like economics and psychology, where extreme values may distort the overall analysis. By focusing on the middle portion of the data, trimmed means offer a more robust understanding of trends and patterns.