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Statistics 101: A Deep Dive into Percentiles and Box Plots

Two people analyzing graphs
Understanding Data Distribution

Percentile and box plots are excellent tools for better understanding your data distribution.

Knowing these concepts is one thing, but having a deep understanding of them and their meaning in real-world examples is imperative.

I will break down these concepts not from the mathematical or book definitions but from the perspective of simple real-world examples to help you remember them forever.

First, let us understand what data distribution

What is Data distribution?

Imagine you have 30 students in a class and measure everyone’s height. The way these heights are distributed — some students being tall, some short, and many in between — is data distribution.

The Scenario

A few students might be pretty short (around 157 cm)

Most students cluster around an average height (say 168 cm to 173 cm)

A few students might be very tall (around 183 cm)

This natural spread or “distribution” of heights reveals key information about our data:

What is the most common height?

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Data Science Club
Data Science Club

Published in Data Science Club

This publication focuses on good quality articles on data science, data engineering, machine learning and deep learning.

Jainam Nimish Shroff
Jainam Nimish Shroff

Written by Jainam Nimish Shroff

CTO at a Tech Startup. I write about Productivity, Data Engineering, and Data Science. Reach out to me to get added to my publications.

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