# 20 Statistical Concepts Every Data Scientist/Analyst Should Know

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Ever wondered how numbers can tell stories? That’s what statistics is all about — making sense of numbers to understand things better.

Think of statistics as learning the ABCs of data science. You start with the basics and soon you’re reading and writing stories, or in our case, analyzing data and making cool predictions!

In this easy-to-follow guide, we’re going to look at 20 key statistics concepts. Imagine these concepts as the building blocks of understanding data. They’re like Lego bricks — simple by themselves but can create something amazing when you put them together.

So, let’s start our journey into the fascinating world of statistics, where numbers tell tales and we’re here to listen and understand.

## 1. Population and Sample

A population is the entire set of individuals or objects under study. A sample is a subset of the population used to make inferences about the entire population.

Example: Consider a university with 10,000 students. The entire 10,000 students represent the population. If we select 500 students from this university and analyze their study habits, those 500 students constitute the sample.

## 2. Descriptive Statistics

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