Random Variable, Probability Mass function, Cumulative distribution function|PMF and CDF

Random Variable, Probability Mass function, Cumulative distribution function|PMF and CDF
#RandomVariable #probabiltiymassfunction #unfolddatascience

Hi, my name is Aman and I am a data scientist.

In this video, I discuss about random variable, probability mass function and probability distribution function. I talk with example what is PDF, PMF and CDF. Below questions are answered in this video:
1. What is a random variable
2. What is Continuous and discrete random variable
3. What is Probability mass function
4. What is Probability distribution function
5. What is Cumulative distribution function

About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.

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[Ramesh-rpjq]

Your teaching style is unique which anyone can easily understand the concepts. Now I am clear on pmf with cdf as part of Probability distribution. Looking for same concept on real time scenario where it can be useful in DS

[haweyorashid]

I would have considered myself a smart person if you were my teacher b/c I am understanding everything so easily while I am loss in stupid lectures thank you so much for sharing your beautiful knowledge

[mosama]

Really, thank you for the BEAUTIFUL explanation man, really appreciate :-)

[joylethabo]

10/10!! where has this channel been hiding this whole time 😭

[xoda]

i did not understand how in the coin tossing case, for a random variable it is 0 if the outcome is head and 1 if the outcome is tail? Should not it be 1/2 in both case?

[krittikamaheshbabu]

in cumulative distribution function, p(x greater than or equal to 1 ) is also 3/4 right?

[farhadkhan]

very easy method.. I got it, , love from Pakistan

[YashpalNSharma]

Hi Aman - In real time Machine Learning, how often do we find data which does NOT follow a normal distribution (bell curve - right or left skewed)?
Just trying to understand how data distributions are in general practical use cases. Thank you!

[ajaynimmala]

P(x=1) is 3/4 as we have three cases where we can have atleast one Head in our random experiment as per our X in discussion. Please clarify?

[ashokthulluri]

sir, how it's take p(x<=1) cumulative distribution function could you explain step by step pls.

[jaxayprajapati]

your content is very helpful but i can not use this concept with real dataset so plz can you take real dataset

[jaxayprajapati]

and what is random variable for dataset

[jaxayprajapati]

plz aap real dataset leke ye concept samajaye