Joint Probability Density Function- Joint PDF/Properties of Joint PDF/Joint Probability Distribution

This video discusses Joint Probability Density Function- i.e. Joint PDF. Properties of Joint Probability Density Function are also covered here. The relationship between joint CDF and joint PDF is explained.
You will find here the definition of Joint Probability Density Function and its mathematical representation (joint PDF formula).
The video explains the Joint PDF for two independent random variables and also for dependent random variables.
Relation between probability and Joint PDF is given for dependent and statistically independent random variables X and Y.

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Random Variables and Probability Distribution

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[sanjanajain]

Thank you sir....very clear explaination and nice notes

[CHBSHUBHAMBAPUSHELKE]

In property one you should say that joint cdf is monotonous non-decreasing function hence the joint pdf is non-negative. As its not always true that if function is positive it means its derivative is positive.

[classmate]

Sir A lecture without examples is NO lecture!
Please provide the lectures with at least 4 eamples, don't think about the video lenght!

[SajanKumar-ecus]

Please also discuss numerical on each concept

[JeremiahMC]

At 3:26 "The derivative of a non-negative function will also be non-negative". This is false. The reason the pdf is non-negative is that the cdf is a monotonically increasing function. Then in the next property you say that the joint pdf is continuous because the joint cdf is continuous. This is also not true -- a continuous function does not always have a continuous derivative (consider y = abs(x)).

[nitishpandey]

Sir last mein statistically independent ke case mein dono function ke beech me multiply aana chahiye

[nandinikatigehallimath]

What if Z=X1+X2, where X1 is poisson and X2 is gaussian where X1 and X2 are independent. How to find the CDF and PDF for it

[nittyagopalbose]

Can I get the papers you use to teach anyhow?

[গোলামমোস্তফা-শ৮থ]

But p=p(x)+p(y)
What will happen if p(x)=1 and p(y)=1?
P=2
!
Relation between joint pdf and probability.

[rimzathzain]

Without example difficult to understand