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The trimmed mean is a statistical measure that reduces the influence of outliers by removing a specified percentage of the lowest and highest values from a data set before calculating the mean. For example, in a 10% trimmed mean, the lowest 10% and highest 10% of data points are discarded, allowing for a more robust average that better represents the central tendency of the remaining data.

Measures of central tendency are statistical metrics that summarize a set of data by identifying the center point or typical value. The most common measures include the mean (average), median (middle value), mode (most frequent value), and midrange (average of the highest and lowest values). Each measure provides different insights, especially in the presence of skewed data or outliers.

The midrange is a simple measure of central tendency calculated by taking the average of the maximum and minimum values in a data set. It is defined as (max + min) / 2. While easy to compute, the midrange can be heavily influenced by outliers, making it less reliable than other measures like the mean or median in skewed distributions.