When the mean and median of a data set are close to each other, it indicates that the distribution of the data is relatively symmetrical. This means that the values are fairly evenly distributed around the center of the data set, without extreme outliers skewing the results.
The mean is calculated by adding up all the values in the data set and dividing by the number of values, while the median is the middle value when the data set is arranged in order. If there are no significant outliers that drastically affect the mean, both the mean and median will be similar, reflecting a balanced data distribution.
In contrast, if there are outliers—extremely high or low values—the mean can be significantly affected, while the median remains stable, which can show a skewed distribution. Therefore, when you observe that the mean and median are close together, it suggests that the data set does not have large outliers and is likely to be more normally distributed.