Mean vs Median
Mean (or average) and median are statistical terms that have a somewhat similar role in terms of understanding the central tendency of a set of statistical scores. While an average has traditionally been a popular measure of a mid-point in a sample, it has the disadvantage of being affected by any single value being too high or too low compared to the rest of the sample. This is why a median is sometimes taken as a better measure of a mid point.
|Improve this chart||Mean||Median|
|Definition:||The mean is the arithmetic average of a set of numbers, or distribution.||The median is described as the numeric value separating the higher half of a sample, a population, or a probability distribution, from the lower half.|
|Applicability:||The mean is used for normal distributions.||The median is generally used for skewed distributions.|
|Robustness:||The mean is not a robust tool since it is largely influenced by outliers.||The median is better suited for skewed distributions to derive at central tendency since it is much more robust and sensible.|
|Expression:||The mean of a set of numbers x1, x2, ..., xn is usually denoted by x̅.||There is usually no accepted standard symbol for Median. It is popularly denoted by the letter ‘m’.|
edit Definitions of mean and median
In mathematics and statistics, the mean or the arithmetic mean of a list of numbers is the sum of the entire list divided by the number of items in the list. When it comes to symmetric distributions, the mean is probably the best measure to arrive at central tendency. In probability theory and statistics, a median is that number separating the higher half of a sample, a population, or a probability distribution, from the lower half.
edit How to calculate
The Mean or average is probably the most commonly used method of describing central tendency. A mean is computed by adding up all the values and dividing that score by the number of values. The Median is the number found at the exact middle of the set of values. A median can be computed by listing all numbers in ascending order and then locating the number in the centre of that distribution. This is applicable to an odd number list; in case of an even number of observations, there is no single middle value, so it is a usual practice to take the mean of the two middle values.
Let us say that there are nine students in a class with the following scores on a test: 2, 4, 5, 7, 8, 10, 12, 13, 83. In this case the average score (or the mean) is the sum of all the scores divided by nine. This works out to 144/9 = 16. Note that even though 16 is the arithmetic average, it is distorted by the unusually high score of 83 compared to other scores. Almost all of the students' scores are below the average. Therefore, in this case the mean is not a good representative of the central tendency of this sample.
The median, on the other hand, is the value which is such that half the scores are above it and half the scores below. So in this example, the median is 8. There are four scores below and four above the value 8. So 8 represents the mid point or the central tendency of the sample.
edit Disadvantages of Arithmetic Means and Medians
Mean is not a robust statistic tool since it cannot be applied to all distributions but is easily the most widely used statistic tool to derive the central tendency. The reason that mean cannot be applied to all distributions is because it gets unduly impacted by values in the sample that are too small to too large.
The disadvantage of median is that it is difficult to handle theoretically. There is no easy mathematical formula to calculate the median.
edit Other meanings of the words
Mean can be used as a figure of speech and holds a literary reference. It is also used to imply poor or not being great. Median, in a geometric reference, is a straight line passing from a point in the triangle to the centre of the opposite side.