Finding a CDF from a pdf
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- Опубликовано: 11 сен 2024
- How to find a cumulative distribution function from a probability density function, examples where there is only one function for the pdf and where there is more than one function of the pdf.
I'm trying to brush up on my stats for a course on Bayesian Machine Learning, and this is the clearest example I found. I thought this is how the cumulative distribution function worked, but the other sources I encountered were less approachable for someone who hasn't taken stats in awhile. This used basic integral calculus and confirmed that my intuition was correct. Thanks!
Hey from the future 👋. How is your machine learning journey so far? 😅
@@hk254lyt8 Hey. It's good! I have been working as a data scientist for a year and a half, and have a modeling pipeline I built for personal projects.
This was so simple, concise and clear to understand! Thank you!!
Can't tell you how much I needed this. Many thanks from myself and my grade!
Crisp, clear and very concise. Thanks mate!
5 years later still helps me greatly thank you!!!
I really have to watch this like more than 10 times because of the graph, it’s not clear 🙁. But this was all the eplanation I needed. Thank you.
you're THE MAN, thanks so much, got theory of information exam in less than two days, you saved me
Can't tell you how much this one has assisted me, thank you
Thank you for explaining through these easy examples .
Great job explaining. Very clear and to the point. Thank you. The way you write the x tho really bothers me hahah
I'd also like to thank you for very effective teaching in this video! It's great!
Just one minor thing that I nevertheless think could increase its quality is if the writing could have been less hard to interpret :) It's a bit like Doctors handwriting ;). I know, there may be technical aspects at play, but still, it's just my well-meaning suggestion.
Thank you. This was a super, super clear explanation.
Thank you, bless you Sir. no time wasted straight knowledge straight facts, you're a beast.
Finally I found the best explanation video❤
Thanks very much.
It saved the day.
Sarcastic part was 8:20, the background looked like a truck was coming.
Thank you for your clear explanation. It's super helpful!
Thnx for explaining...ND no problem with handwriting, Its better than mine
greaaat explanation i finally could understand the concept thanks to ur video, please just consider improving the way u write, other than that, just continue adding some of these awesomeee videos. danke schÖn
Thank you for the clear explanation! It was very helpful
And.. I understand your handwriting and don't understand people who don't :D
Many many thanks to you bro .. I need the most... honestly
The variable under integration should be something different from x, say 1/4tdt. Very well explained
well explained.Thankyou
That was the first question of the midterm of the Modeling and Discrete Simulation course at Marmara University.
Sir, when you are using "x" as a limit how can you integrate the PDF using "dx". Shouldn't you use a dummy variable?
X is a variable value between 1to3 for finding the probality at any point
Yes. Bad form not to.
why in 1st example the probability is 1 after 3 ..Reason ?? the graph is still touching zero as in case of x less than 1
Awesome video my man! Just a quick question, at 5:00 why do you put 1, x>3 instead of 0, x>3? Doesn't it say 0 for all other values outside of the range of f(x)?
A CDF is the cumulative probability. So, the sum of the probabilities up to that point: P(X>3)=1. The graphs of the pdf and cdf are different. He did not graph the latter.
Yes, but this now a is a cumulative function, which is different to the probability density function. It means that the area under the curve will be 1 for any point where x>3, because we are counting all of the area up to that point.
thank you for this.
Thank you so much, you really saved my life on understanding the concept!
Good work, my g.
Better than my lecture can I pay you the tuition instead
bohat papi samjhaya re, love from Pakistan
Thanks!! Keep posting more...I will tell my friends of your channel
perfect..never found something simpler!
Great Explanation😌
Thanks mate.Keep up.You're the man.
Why does x stay the same instead of being multiplied with the xˆ2 inside the bracket and hence becoming xˆ3? Pleaseee anyone answerrrr
great explanation
Help me please, is there any difference between corresponding distribution function and cumulative distribution function?
You are totally amazing
Well explained 🙏
Incredibly, thank you so much!!
Very helpful! Thank you!
is it okay if we dont subtitute values and just get the function
for example without substituting the value in second part function we get is 7+2x3/21
You're incredible! Thanks you so much!
good explanation sir.u have done a great job.
Very nice! It really helped me.
Really helpful, thanks!
if question is P(X+Y>3)..........what should i do?
Why do you get a probability that is greater than 1? For instance with the second example f(x)= 2/7*(2^2) >1 ... surely it doesn't work?
why would you add area of A i. e. 1/3*1...??? There is an integration that will add the area already..
Really nice 👍
you saved my life ...
You are awesome man
I have a question (in the 1st problem).
I understand why the cdf becomes 0 when x < 1. But...
The cdf is (x^2 - 1)/8 if 1 ≤ x < 3; and the cdf is 1 if x ≥ 3, aren't they?
I think you’re referring to the inequality signs relating to 3. When x is 3, F(x) = 1 either way. Whether you say F(x) = 1 when x ≥ 3 or F(x) = (x^2 - 1)/8 when 1≤ x ≤ 3. Substitute 3 into this and you still get 1. So doesn’t matter whether you include 3 in the second or last statement.
This is because the probability of an exact number = 0. So the inclusive inequality signs are pretty much irrelevant.
Hate to be nitpicky, but why do you draw your x's like that...
Thanks, helped me a ton.
Could you please explain why you have X^2 / 2? Is f(x) by definition x^2?
thanks man
great video, thank you!
Awesome Vid! Much appreciated!
why is it 1 for x>3? shouldn't it be 0?
for the f(x) then , then yes x>3 is 0. but since its F(x) which is the CUMULATIVE distribution function, the value is for x>3 is 1 since the total area for overall is 1. the total area is 1 when the range is between 1-3. anything above 3, is considered more than 1.
very helpful, thank you
Great!!!!! Thank you so much for this
Great video. Thanks :)
Thank you so much
Thankyou !!!!! It is very helpful
I love you thank you
awesome explanation thank you ^^
wonderful thank you man
awesome video bro thank yu verymuch
I understood everything, thank you! In part 2, F(x) is x/3 when 0
Because its continuous, it doesn't really make a difference because the probability of x=1 is 0
thanks chief
the second part answer should have been
7x+2x3 /21
no?
Excellent!
welldone man
How we get 7??
Thank you!
Thank you :)
Your voice sounds nice.
thank you!!
Thanx sir
why is the probability 1 at x > 3
It's because we are looking at a cumulative function. The limits of the pdf is between 1 and 3, so anything before 1 the probability is 0. Anything above 3 the probability is 1, because the cumulative function encompasses everything up to the number inputted, if you choose a number 3 or greater, it will have given the area of the entire function, which is 1.
Hope that helps.
Thanks a lot
thank you.
Keep it up
Error in the final F(x)
In the cdf while writing the function for 1
Ok, I see what is happening... duh! As the name suggests it is cumulative. Similarly p(x)=0 for x>2 but P(x)=1 for x>2! Got it. Thanks.
Brilliant
thank you bruv
Thanks :)
how to find cdf from pmf
Thanks sir.
tnx sir
ty :D
thankyou
thats wassup dawg on god
the video gives useful information, thank you very much
better handwriting next time XD
you sound like you could be a harry potter character
hye sir
Sorry i didn't understand the drawing. :(
this is unclear put the camera closer to the paper next time I cannot see anything
I didn't understand anything 😭😭😭