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Top 10 Statistics Mistakes Every Data Scientist Should Avoid
Latest   Machine Learning

Top 10 Statistics Mistakes Every Data Scientist Should Avoid

Last Updated on July 17, 2023 by Editorial Team

Author(s): Anmol Tomar

Originally published on Towards AI.

1. Selection Bias

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Image Credit: Unsplash

Statistics plays a crucial role in data science, helping us draw meaningful insights from data and make informed decisions. However, even the most experienced data scientists can make mistakes when dealing with statistical concepts and methods. These mistakes can lead to flawed analyses, misinterpretations, and inaccurate conclusions.

In this blog, we will explore the top 10 statistics mistakes commonly made by data scientists. By highlighting these mistakes and providing examples, we aim to increase awareness and help data scientists avoid these pitfalls. Whether you’re a beginner or a seasoned professional, understanding these common statistical errors will empower you… Read the full blog for free on Medium.

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Published via Towards AI

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