Well, the normal distribution is the probability distribution without any skewness. Now, you might be thinking – why am I talking about normal distribution here? In simple words, skewness is the measure of how much the probability distribution of a random variable deviates from the normal distribution. If that sounds way too complex, don’t worry! Let me break it down for you. Skewness is the measure of the asymmetry of an ideally symmetric probability distribution and is given by the third standardized moment. Understanding Negatively Skewed Distribution.Understanding Positively Skewed Distribution.Analytics Vidhya’s statistics tutorials.Perfect introduction course for data science with a comprehensive statistics module.Note: Here are a couple of resources to help you dive deeper into the world of statistics for data science: So buckle up because you’ll learn a concept that you’ll value during your entire data science career. You’ll learn about skewness, its types, and its importance in the field of data science. Here, we’ll be discussing the concept of skewness in the easiest way possible. And I’m sure you’ll understand this by the end of this article. It is something that we simply can’t run away from. Skewness is a fundamental statistics concept that everyone in data science and analytics needs to know. And it’s actually a pretty easy topic in statistics – and yet a lot of folks skim through it in their haste of learning other seemingly complex data science concepts. So even if you haven’t read up on skewness as a data science or analytics professional, you have definitely interacted with the concept on an informal note. In other words, we can say that there’s a skew towards the end, right? If you’ll plot the distribution of the age of the population of India, you will find that there is a hump on the left side of distribution and the right side is comparatively planar. When we look at a visualization, our minds intuitively discern the pattern in that chart.Īs you might already know, India has more than 50% of its population below the age of 25 and more than 65% below the age of 35. The concept of skewness is baked into our way of thinking.

Learn what is skewness, and why it’s important for you as a data science professional.

Skewness is a key statistics concept you must know in the data science and analytics fields.

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