From the course: Python Functions for Data Science

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Statistical functions with SciPy

Statistical functions with SciPy - Python Tutorial

From the course: Python Functions for Data Science

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Statistical functions with SciPy

- [Instructor] As a reminder, the SciPy library is foundational for scientific computing, an important toolbox for data scientists and composed of task-specific sub-modules built on top of the numpy library. The stats sub-module is particularly crucial to data science, as it supports many different types of probability distributions and contains several statistical tools. I'll be going over some examples to demonstrate how statistical functions from SciPy stats-module are used. First, I'll import the numpy library and give it the alias np, then I'll import the stats sub-module from the SciPy library. Let's say I want to create a variable that represents a binomial discrete random variable, I will declare B to be a binomial discrete random variable with parameters 10 and 0.4. It will look like this. Now, say I want to compute the value of this variables probability mass function at two I can use the pmf functions…

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