Medians & Percentiles
There are many different measures used in statistics that help in determining the situation, standing or position of one element of a population with respect to the entire population. A little bit of knowledge of histograms and column charts will probably help more in understanding these measures like medians, deciles and percentiles.
Median is described as the numerical value separating the higher half of a sample, a population, or a probability distribution, from the lower half.
A percentile (or centile) is the value of a variable below which a certain percent of observations fall. For example, the 30th percentile is the value (or score) below which 30 percent of the observations may be found.
It is also to be understood that the 50th percentile is the median itself. There are also terms/measures called quartiles. The 1st quartile is identical to the 25th percentile, the 2nd quartile with the median and the 3rd quartile with the 75th percentile.
Such measures like medians, quartiles and percentiles help in identifying certain classes of data or in categorizing the observations. These have a great role in data analysis and data interpretation in all statistical matters including samplings/surveys. Therefore they find lot of importance in program/project management, MIS (Management Information System) and M&E.
Median is described as the numerical value separating the higher half of a sample, a population, or a probability distribution, from the lower half.
A percentile (or centile) is the value of a variable below which a certain percent of observations fall. For example, the 30th percentile is the value (or score) below which 30 percent of the observations may be found.
It is also to be understood that the 50th percentile is the median itself. There are also terms/measures called quartiles. The 1st quartile is identical to the 25th percentile, the 2nd quartile with the median and the 3rd quartile with the 75th percentile.
Such measures like medians, quartiles and percentiles help in identifying certain classes of data or in categorizing the observations. These have a great role in data analysis and data interpretation in all statistical matters including samplings/surveys. Therefore they find lot of importance in program/project management, MIS (Management Information System) and M&E.