Probability density and mass functions

We introduce the basics of probability density and mass functions and how they let us handle different kinds of random variables. Video by Ari Seff ( / ariseffai )
Princeton COS 302 Lecture 15, Part 2

[@annapieroni1865]

Thank you for the very clear explanation! I never took a stats class, so online resources like this help me survive upper division CS and ME classes. Much needed for fluids labs and speech processing!

[@parmisbathaeiyan9955]

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[@bryan6aero]

Thanks. This explanation was very clear, concise, and helpful.

[@intelligentsystemslab907]

Glad it was helpful!

[@mr.p2665]

Underrated channel

[@mohammadpourheydarian5877]

Very beautiful. Thank you.

[@melontusk7358]

Just brilliant.

[@raideryvs5595]

Great explanation !

[@Anandhu-X]

Thank you

[@mandelbro777]

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[@Anandhu-X]

4:37
Say if the p(X=4)=0.5
What is the interpretation of this exact statement?
Could it be that the probability of x occurring arbitrarily close to 4 is 50%?

[@kvs123100]

One query! When we have countable infinite values, would that be considered as continuous distribution/setting?

[@intelligentsystemslab907]

No, that's still a discrete distribution. It has a probability mass function rather than a density function. The Poisson and geometric distributions are both examples of discrete distributions over a countable set.

[@kvs123100]

@@intelligentsystemslab907 thanks for the great explanation!

[@iTzTomy04]

You’re my guardian angel