What characteristic of the mean can be a disadvantage when calculating it as a measure of central tendency?

The characteristic that can be a disadvantage when calculating the mean as a measure of central tendency is its susceptibility to extreme scores, also known as outliers. When calculating the mean, all values in the dataset are considered equally, which means that a single very high or very low value can significantly skew the result. This means that the mean may not accurately represent the typical value of the data, particularly in datasets that contain outliers.

By contrast, median and mode, other measures of central tendency, are less affected by extreme values. The median, for example, represents the middle value of a dataset when ordered and thus provides a better indication of a “typical” value in skewed distributions. Understanding this limitation of the mean is essential for interpreting data correctly and choosing the appropriate measure of central tendency based on the dataset's characteristics.

The other answer choices do not correctly identify disadvantages of the mean. The mean does not always result in a whole number, nor does it specifically measure the middle value as the median does. Additionally, it does not use only the most frequent score, which is characteristic of the mode.