A tool designed for statistical analysis, this utility calculates the average of a dataset after removing the highest and lowest 10% of the values. For instance, with a dataset of 100 numbers arranged from smallest to largest, the top 10 and bottom 10 values would be excluded, and the mean calculated from the remaining 80. This method helps mitigate the impact of outliers on the average, providing a more robust measure of central tendency than a standard arithmetic mean.
Offering a more stable representation of the typical value in a dataset, this analytical method is particularly useful when data may be skewed by extreme values. Its development stems from the need to address the limitations of traditional averaging in the presence of outliers, leading to wider adoption across various fields, from scientific research to financial analysis, where accuracy and reliability are paramount. By reducing the influence of anomalies, this technique offers a clearer view of the true central tendency.
