Counselor Education Comprehensive Exam (CECE) Practice Exam

An outlier affects which measure of central tendency the most?

1. Mean

2. Median

3. Mode

4. Skewness

The correct answer is: Mean

The mean is significantly influenced by outliers because it is calculated by summing all the values in a dataset and then dividing by the total number of values. When an outlier exists, especially a value that is much higher or lower than the rest of the data points, it can disproportionately distort the mean. For example, in a dataset where most numbers are clustered around a certain range, adding an extremely high or low number can pull the mean in the direction of that outlier, leading to a misleading representation of the dataset's central tendency. In contrast, the median, which is the middle value when data points are arranged in order, is much more resistant to outliers because it only considers the middle value and not the extreme values in the dataset. The mode, which identifies the most frequently occurring value, is entirely unaffected by outliers, as it relies solely on frequency rather than value. Skewness, while related to the distribution of data and can be affected by outliers, is not a measure of central tendency in the same way the mean, median, or mode are. Consequently, when considering which measure of central tendency is most affected by outliers, it is clear that the mean takes precedence due to its sensitivity to extreme values.