Descriptive Statistics Part 5
In this tutorial, we will discuss about percentiles , quantiles and quantiles in data .
So , In data how can we find where is 10 percentiles , where is 20 , 30 so on.
In section 1, will discuss about percentiles .
In section 2, will discuss about quantiles or quartiles in depth .
So, understand in depth let take a simple sample of height data -
Height distribution — 18 , 19 , 20, 55 , 48 , 46, 77, 15, 17, 66.
It’s height of sample . now visualize the quantiles and percentiles.
First of all, we do the height in sorted order .
After sorting distribution look like — 15, 17, 18, 19, 20, 46, 48, 55, 66.
Now calculate percentile , above diagram we take 20 is percentile 50% . It mean 50% height of the people below 20 or 50% people of height above 20.
55 take is on 90% percentile it mean 90% people of height is less than 55.
19 take is on 40% percentile it mean 40% height of people above 19.
Section 2-
Quantiles — quantiles mean quoters.
To understand about quantiles we are taking same dataset of heights.
It mean 50% data left side 50% to right side from the median so that it is called Q3.
How to find Q1, Q2, Q3, IQR ,Min, mAx read my box plot blog.
For calculating, quantiles entire sample data divided into 4 quoter.
If any doubt regarding it. please comment below and ask feel free.
If any doubt regarding this tutorial ask feel free on LinkedIn- http://linkedin.com/in/puneet166
GitHub workspace link- https://github.com/puneet166?tab=repositories
