What type of data is affected most significantly by extreme values?

The mean is the measure of central tendency most significantly affected by extreme values, also known as outliers. This is because the mean is calculated by summing all values in the data set and then dividing by the number of observations. When an extreme value, whether very high or very low, is included in this calculation, it can dramatically change the sum and, consequently, the resulting mean.

For instance, if a set of test scores is composed primarily of scores in the 70s and 80s, a single score of 0 or 100 will pull the mean down or push it up, respectively, creating a misrepresentation of the typical score. This sensitivity to extreme values means that the mean can provide a skewed view of the data's central tendency, particularly in datasets with outliers.

In contrast, the median, which is the middle value when all observations are sorted, is not affected by extreme values since it depends solely on the rank order of values, not their specific magnitudes. Similarly, the mode, being the most frequently occurring value, is not influenced by extreme values either. The weighted mean, depending on its construction, can be comparatively less influenced than the simple mean but can still reflect the impact of outliers if extreme