Probability: Binomial Distribution

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In essence, Binomial events are a sequence of identical Bernoulli events. Before we get into the difference and similarities between these two distributions, let us examine the proper notation for a Binomial Distribution. We use the letter “B” to express a Binomial distribution, followed by the number of trials and the probability of success in each one. Therefore, we read the following statement as “Variable “X” follows a Binomial distribution with 10 trials and a likelihood
of success of 0.6 on each individual trial”. Additionally, we can express a Bernoulli distribution
as a Binomial distribution with a single trial. Alright! To better understand the differences between
the two types of events, suppose the following scenario. You go to class and your professor gives the class a surprise pop-quiz, which you have not prepared for. Luckily for you, the quiz consists of 10 true or false problems. In this case, guessing a single true or false question is a Bernoulli event, but guessing the entire quiz is a Binomial Event.
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#probability #binomial #distribution

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[@nicorobin7666]

Thank you so much for these dense clear comprehensive short videos. These are more valuable than an hour long lecture of the same subject

[@365DataScience]

You are most welcome.

[@kartikbhargav6316]

True

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[@ebierealexandria]

Nice video but please where does the 10 come from?

[@gurkapraveen1728]

Same doubt

[@josepitinvikingo]

I did not understand how you got the 10 out of the C :(

[@allahsslave9609]

same but i figured it out using the combination formula. n/y= nCy= n!/(n-y)!y! if n=5, y=3 u plug in 5!/(5-3)!3! the answer comes out to 10

[@chawza8402]

this one is kinda hard but thank you! little question from me, do you use your animation using PowerPoint or pure in a video editor?

[@drbarbarossa8503]

What is 10 in GM example please

[@jajatrevis2910]

It's the answer you get when you solve 5 combination 3

[@ryanyeet7288]

Thank you, Mr. Data Science, very cool!

[@jawad_youtube]

Good presentation ❤️ Great visuals 💓 A perfect educative video 👍🏻

[@zenwoo7759]

More useful than my college lecturer lmao

[@nicorobin7666]

Where did the number 10 come from?

[@marciosp450]

It came from Combination formula: 5! / (3! * (5-3)!). kzbin.info/www/bejne/pmnZepajp8SDp9E

[@theboze838]

Very well done here. So much better understanding now. Thank you!

[@alexmattyou]

Clearly explanied 👍👍

[@BruceNJeffAreMyFlies]

The way he says 'Great! 😎' as soon as I said, out loud, "what the fuck?", was just too hilarious!

[@nicorobin7666]

Is there an intuitive way to understand the formula?

[@CesarSilva-j4x]

very good

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[@independent7212]

tq u for the video

[@angedieka3320]

Hello! kind help here: In batch of 100 screws, a maximum of 3 can be defective. A random sample of 20 screws are taken. How many defective parts are allowed in this sample considering all scenarios probabilities less than or equal to 90%?

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[@nazirsaleh9123]

Negative Binomial ?

[@mackscarey8602]

Is the graph that is shown at 2:02 a type of probability mass function?

[@KundanYadav-je4xf]

yes

[@techotech1252]

Very interesting and informative

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thanks for the great content

[@arnabhai3629]

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[@365DataScience]

Thank you!

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Excellent!