This is widely used in calculating the positions of students participated in entrance exams, though the calculations vary slightly.

The p^{th} percentile of a data set is a value such that at least p % of the items in

the dataset have a value equal to or less than the value of the data item. It also means that

(100 – p) % of the items have a value more than the value of the data item.

Calculating Percentile

Percentile can be calculated using the following approach:

Arrange the data in ascending order.

The position of the p^{th } percentile item, i = (p/100) * n where n is the total numbers in the data sample.

If i is not an integer, round up. The p^{th} percentile is the value in the i^{th} position.

If i is an integer, the p^{th} percentile is the average of the values in positions ‘i’ and ‘i +1’.

Calculating 90th Percentile

Consider the below sample of data.

5,6,2,3,4,4,4,5,8,9

Arrange the data in ascending order

2,3,4,4,4,5,5,6,8,9

i = (p/100) * n = (90/100) x 10 = 9

Averaging the 9th and 10th data value you get 90th percentile = (8 +9)/2 = 8.5

{ 4 comments… read them below or add one }

WHAT IS THE PRACTICAL UTILITY OF PERCENTILE AND QURTILE CALCULATIONS

Hi John,

Percentiles were explained to give an understanding of quartiles. In practice, quartiles are used by analysts. Quartiles are basically to understand the ranking of a fund based on its performance compared to other funds in the same category. For example, if a fund’s rank is 20 out of 100 funds used for comparison by Morningstar and for another fund it is 500 out of 600 funds. Instead of looking at the rank and total funds considered for comparison, if the data is given in quartiles it’s readily understood that the funds are in top category/moderate/worst etc. In the above example the first fund is in the first quartile so we can conclude that it’s a top performing fund whereas the second fund’s quartile is 4 we can say that it’s performance is detracting.

Thanks satyam

can you just explain the importance of moving averages in stock market

One of the applications of moving averages is calculating value at risk. And it is used in technical analysis. Please have a look at this.

http://lastbull.com/nse-quotes-%E2%80%93-value-at-risk-var/