What is the term for the average that is most sensitive to extreme values in a data set?

The mean, often referred to as the average, is calculated by summing all the values in a dataset and then dividing by the number of values. This calculation makes it particularly sensitive to extreme values, also known as outliers. When a dataset contains extremely high or low values, the mean can be significantly affected, resulting in a value that may not accurately represent the central tendency of the majority of the data points.

For example, if you have the data set {1, 2, 3, 4, 100}, the mean would be (1 + 2 + 3 + 4 + 100) / 5 = 22. However, the majority of the data points are much lower, and the mean does not reflect the typical values in the dataset. In contrast, the median is the middle value when the data is ordered, and is not influenced by extremes, making it a better measure of central tendency in skewed distributions. The mode, being the most frequently occurring value, is also unaffected by extreme values. The inclusive range simply gives an idea of how spread out the data is but does not provide a measure of central tendency.

Therefore, the mean is the term that identifies the average highly sensitive to extreme