Statistics with R Programming Part 4 | Continuous Random Variable | Data Science Tutorial

Statistics with R Programming Part 3 | Poisson Distribution Tutorial | Data Science Tutorial
Hello and welcome back to another session of statistics tutorial with R Programming Powered by Acadgild. In the previous video, you have learned Poisson distribution and in this Data Science tutorial, you will be able to learn, Continuous Random Variables, before that, if you have missed our previous tutorials of this series, kindly click the following links and watch the video for a better continuation.
Let’s go through the concept in-depth,
Continuous Random Variable: Almost every type of data which exist in today’s world can be modelled as continuous random variables. It is essential to understand the inherent uncertainties. This is basically done by evaluating the probability density functions as well as the cumulative density functions.
Continuous Random Variables can classified as
• Uniform distribution
• Normal/Gaussian distribution
• Lognormal distribution
• Exponential distribution
• Weibull distribution
• Gumbel Distribution
Kindly, go through the complete video to learn the implementation. Please like, share and subscribe to the channel for more tutorials.
#ContinuousRandomVariables, #Statistics, #R, #datascience
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[RanjibBanerjee]

Rubbish, Show in your tutorial how to integrate a PDF to get the expected value of the random variable