Introduction to R: Probability Distributions

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DataDaft

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Published on November 25, 2019 7:54:06 PM ● Video Link: https://www.youtube.com/watch?v=Rxe086csxTU

Duration: 24:00

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Understanding the processes that generate the data we see is at the heart of data science. Much of the data we observe is generated by processes with an element of chance or randomness. Sometimes it rains, sometimes it doesn't. Probability is a statistical concept that describes the chances that some event will occur. Probability distributions are mathematically defined functions that model the chances of seeing the different potential outcomes of a random event. There are many different probability distributions that can be used to model different types of random events and processes. In this lesson, we focus on learning the basics of probability and take a look at a few common probability distributions in the context of learning the R programming language.


This is lesson 22 of a 30-part introduction to the R programming language for data analysis and predictive modeling. Link to the code notebook below:

Intro to R: Probability Distributions
https://www.kaggle.com/hamelg/intro-to-r-part-22-probability-distributions

** Note: It seems I used my code clip banner overlay at the bottom of the video by mistake! It should have the Introduction to R banner. **

This guide does not assume any prior exposure to R, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn R.

I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can fork and edit each lesson so that you can follow along and run code yourself.

Introduction to R Playlist:
https://www.youtube.com/playlist?list=PLiC1doDIe9rDjk9tSOIUZJU4s5NpEyYtE