What is the Difference Between Mean and Median?

The main difference between mean and median lies in the way they represent the central tendency of a dataset. Here are the key differences between the two:

• Mean: The mean is the average of a set of numbers, calculated by adding all the numbers together and dividing the sum by the total number of values. It is sensitive to outliers and can be affected by any single value being too high or too low compared to the rest of the dataset.
• Median: The median is the middle value in a list of given numbers numerically ordered from smallest to largest. It is not much sensitive to outlier data and defines the central value of the data set. In case of an odd number of observations, the median is the middle value, while for an even number of observations, it is the arithmetic mean of the two middle values.

In summary, the mean is the average of a dataset, while the median is the middle value of the dataset. The median is less sensitive to outliers compared to the mean, making it a useful measure when dealing with datasets that have extreme values.

Comparative Table: Mean vs Median

The difference between mean and median can be summarized as follows:

Both mean and median are measures of central tendency, but they are used in different scenarios. Mean is the average of a set of values, while median is the central value in a data set. Mean takes every value in the given data set for calculation, whereas the median is calculated using only the middle value(s).