Understanding Distributions with Extremes: Probability for Data Science Series (End)
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If you’ve been following my articles, you’ve probably noticed my recent emphasis on probability distributions. I’ve spent a lot of time talking about their importance, and for good reason. If you’ve already grasped why these distributions are crucial, this article will serve as a nice reinforcement. If not, I hope this article will provide some new insights for you!
Let me ask you a question
Why are probability distributions so important? Why do we spend so much time studying probability density functions (PDFs) and cumulative distribution functions (CDFs)? Hint: The answer depends on whom you ask.
However, you probably came here for a more direct answer. So… for me… I’ll answer that question by helping you understand extreme values like Xₘᵢₙ and Xₘₐₓ (If you just want the answer, please skip to the end of the article)!
Hopefully my explanations are intuitive and accessible, without unnecessary jargon.