Final answer:
When handling outliers in a data set, the median is the advised measure of central tendency because it is not influenced by extreme values, unlike the mean, which can be skewed. The correct answer is b) Use the median.
Step-by-step explanation:
When dealing with a measure of central tendency for a distribution with outliers or extreme high or low scores, it is advisable to use the median. The reason for this is because the median is the value that lies at the middle of a data set, dividing it into two equal parts, and is not affected by the precise numerical values of the outliers.
In contrast, the mean is sensitive to outliers as it is the arithmetic average of all data points and can be skewed by extreme values. While the mode indicates the most frequently occurring data value and could be considered as well, it may not represent the central tendency if the outliers do not recur.
Consequently, the mean can be significantly distorted in the presence of outliers, leading to a misleading representation of the data's center.
The median is generally a better measure of the center when there are extreme values or outliers. For example, if the data set is 3, 4, 5, 14, 14, considering 14 is an outlier, the median would be 5, which is a more accurate reflection of the center of the majority of the data than the mean, which would be higher due to the inclusion of the outlier.