Bernoulli Distribution

In this tutorial we are going to discuss another type of probability distributions- the Bernoulli distribution. Bernoulli events are the simplest we can have, since they consist of a single trial and only 2 possible outcomes. Examining them will provide us with the fundamental properties necessary to build more complex scenarios as we dive deeper into the field of probability.

365 Data Science is an online educational career website that offers the incredible opportunity to find your way into the data science world no matter your previous knowledge and experience. We have prepared numerous courses that suit the needs of aspiring BI analysts, Data analysts and Data scientists.

We at 365 Data Science are committed educators who believe that curiosity should not be hindered by inability to access good learning resources. This is why we focus all our efforts on creating high-quality educational content which anyone can access online.

#BernoulliDistribution #Statistics #DataScience

[DargiShameer]

Short and informative. Channel subscribed

[beefandpotatoes]

by far this video is the best I have seen on Brn (P). I am going to check his other videos. Thank you very much.

[faiqarif]

So basically, its an elementary case of a binomial distribution?

[nicorobin]

Who is the evil soul that disliked such an excellent video

[unknownshadow]

Very good illustration....!
The examples are easy yet do not loose the essence of the topic

[bluecup]

I think the order in the "Probability Distributions" is reversed, this should come before the Binomial, right? Thanks, loving these, extremely helpful and concise.

[sajidbhai]

Can you tell in which of the branches of engineering probability and binomial distribution used

[tinyasira]

in 2:22 how to get the second line? like the values of x0- miu and then (0-p)^2 I didn't get that

[shafiqshams]

Why variance is not equal to p . (1 - p)^2 ??

[roopinm.p]

How to calculate mode and median for this distribution?

[smbdcry]

2:15 I have seeking the steps before variance standard formula jumping into p(1-p) … does anyone know the missing parts. Really wanna know what’s the middle steps.. otherwise I had to hard code in my memory

[archanalawande]

For a Bernoulli r.v.x, μ3=0.7 what is Var( X) ?