Difference Between Mean and Median

Mean vs Median

The mean and median are measures of a collection of data related to any single source information. We use mean and median to check the location of the data because they give an indication of a central value around which a set of values tends to cluster. Mean is the sum of total values in a data divided by number of values, while median is the middle value of a data. The selection of either mean or median for examining the data depends upon the type of data and requirement of result, as in some cases mean gives better results than median and vice versa.

Mean

The concept of mean is same as calculating the average value of a data set. In simple words, mean is the sum of total numeric values present in a data set divided by number of values present in that data set. This type of mean is called Arithmetic mean. There are other three classes of mean: Geometric mean, Harmonic mean and Population mean. Geometric mean is used for those positive numbers, which are interpreted in a data set as a product rather than sum. Harmonic mean is useful for those numbers, which have some relation with the term having units like data of velocity or acceleration collected in different time intervals. Both velocity and acceleration have units like m/s and m/sq.sec. The population mean is different from all these means as it is the expected value of a random variable, calculated from average weight of all possible values.

Median

Median of data set is that middle numeric value, which separate the lower half data from upper half data. The method of finding median is very easy; just arrange all the values of a given data in ascending order, that is start from minimum value and end at maximum value. Now the middle value is your median. If you have data in such condition, that number of values is even number, then the mean of two middle values will be your median. When there is a possibility of asymmetry in distribution or end values are not given, median is helpful for measuring the location. Therefore, median is better source of measuring central tendencies, if few values are clearly separated from the main body of the data (called outliers).

Comparison

• To clear the difference between mean and median, here is an example:

We have a data set comprises of values such as 5, 10, 15, 20 and 25, now we calculate mean and median for this data set.

Mean = 60+80+85+90+100= 415/5 = 83

Median = 85 because it is the middle number of this data set.

• Mean and median are measures that are used to interpret a collection of data from a single source.

• The mean is usually the most appropriate measure of location, because it takes into account every value in the data set.

• If there are outliers in the set of data, then the mean may be affected by these extreme scores and will not accurately represent all of the scores. In this case, the median is a better measure, because it is not affected by outliers..

• Median is not influenced by repeating numbers in a data set while mean value vary by increasing the same value in a data set, which is already exist in that data set.

• To calculate mean, you have to do some calculation for every type of data. On the other hand, to find the value of median, you do not require any calculation for all type of data.

Conclusion

Many people remain confused about the concept of mean and median. However, there is a clear difference between these two terms. Mean is average value of a data set, while median is the central numeric value of a data set.