I have watched tons of videos and never understand it , untill I watched yours . You have no idea how much it helps. Your steps are very simple, clear and really easy to understand. Thank you sooooo much
Ok this is fantastic. My prof has the most round about ways of explaining probability densities. This really underlines the basic concepts and makes it much easier to tackle tougher problems, that included exponential distribution as a part of them. Thanks!
For my high school math class, I am supposed to be teaching exponential distribution to my fellow peers. This video was very helpful! Thank you so much:)
Thank you so much Stats. your video has just save me time,unnecessary stress and perfect understanding. God bless you. i enjoyed and learnt from your video.
I thought because exponential distribution deals with continuous data, that you could not use less/more than or equal to, rather just less than or more than. Because with continuous data the probability of you being exactly on the point of a discrete number such as having exactly 5 litres of fuel in ur tank, would be 0? correct me if I'm wrong
Ive done all the workings using .10 as Lambda and having the value being in brackets after the lambda, still same result just slightly different method.
Good question - Remember that the exponential is a continuous distribution. P(X =k) is considered 0. If the distribution was *discrete* - then the problem you mentioned would arise.
As regards the Interval 1. P(Inside Interval) = 1-P(outside Interval) 2. P(Outside Interval) = P(Too High) + P(Too Low) It is common to all continuous distributions so not discussed here in detail
Stats-Lab Dublin I see! It is important to be aware of those minor things when working with continuous distributions vs. discrete. Thank you for your explanation!
I'm confused.. at 10:00 you say "and that minus there, and that minus there gives a plus".. where are you getting the other minus? I can only see a 1 - (1-e^(-lambda x)) which should give -e^(-lambda x) ??
because pdf of a function is the probability per unit if you use it then it will not give you the probability ,instead if one uses the integration of pdf wrt "the unit" then you will get{(probability/unit)xunit} which will give you the probability also known as the cdf.
The failure rate of an electronic component is 2 per 300 hours on average. a) Find the probability that the component will fail before 200 hours of operation? b) Find the probability that the component is still working after 500 hours of operation. i need help with that anyone with an idea pls
I have watched tons of videos and never understand it , untill I watched yours . You have no idea how much it helps. Your steps are very simple, clear and really easy to understand. Thank you sooooo much
"The CDF can be written as the probability of the lifetime being less than some value x"
That helped me soooo much, thanks!
Ok this is fantastic. My prof has the most round about ways of explaining probability densities. This really underlines the basic concepts and makes it much easier to tackle tougher problems, that included exponential distribution as a part of them. Thanks!
For my high school math class, I am supposed to be teaching exponential distribution to my fellow peers. This video was very helpful! Thank you so much:)
5:46 E and Var
2:50 PDF
4:10 CDF
Thank you so much Stats. your video has just save me time,unnecessary stress and perfect understanding. God bless you. i enjoyed and learnt from your video.
Should've explained how you derived the cumulative distribution function from probability density function. Also we can solve P(5
This was very helpful! Clear and easy to understand
This is a very nice and explicit video... great help. Thanks
Thank you so much man. This is the only video which helped me so far
lovely video but much easier on the question C by just integrating f(x) within that limit 5 and 10. Good job man
I like it for being neatly written making it easy to copy fr future use.
Thank You So Much Sir. It really helped me a lot. Keep on doing this kind of videos
finally the educational video I was searching
this video helped so much once i figured out the e is a set number. kinda like pi.
Thankyou,the explanation is very clear.
Very helpful video. Thank you!
Very Helpful ..Thank you so much for your upload
Thanks a lot..Earlier i was very much confused in waiting line theory..
Thank you! Was very helpful and clear to follow
Beautiful, thank you! I could not find a detailed explanation anywhere
Thanks so much! Loved it even more because of the Irish accent!
Super super helpful. Thank you.
I thought because exponential distribution deals with continuous data, that you could not use less/more than or equal to, rather just less than or more than. Because with continuous data the probability of you being exactly on the point of a discrete number such as having exactly 5 litres of fuel in ur tank, would be 0? correct me if I'm wrong
Thanks for such an informative video.
Really good presentation. Keep up the good job sir.
Ive done all the workings using .10 as Lambda and having the value being in brackets after the lambda, still same result just slightly different method.
Thank you, this was awesome! :)
For part c), I don't understand how the complement of P(5
Good question - Remember that the exponential is a continuous distribution. P(X =k) is considered 0. If the distribution was *discrete* - then the problem you mentioned would arise.
As regards the Interval
1. P(Inside Interval) = 1-P(outside Interval)
2. P(Outside Interval) = P(Too High) + P(Too Low)
It is common to all continuous distributions so not discussed here in detail
Stats-Lab Dublin I see! It is important to be aware of those minor things when working with continuous distributions vs. discrete. Thank you for your explanation!
Call it Learning. I am sort of build up the library bit by bit - Also can't cram everything into one video
Don't get why you wouldnt just do P(5
Thank you, i understood it perfectly.
You made my day :)
I can't thank you enough...
For part B it should be P(x>10) not greater than equal to
I'm confused.. at 10:00 you say "and that minus there, and that minus there gives a plus".. where are you getting the other minus? I can only see a 1 - (1-e^(-lambda x))
which should give -e^(-lambda x) ??
are earthquakes in a region truly independent? one earthquake may give rise to tremors and affect the future
good job!
In part A why did you use the CDF instead of the PDF? You pretty much used the CDF in all parts instead of PDF why?
thanks
Sorry sir. I am not sure why we should use the CDF of exponential distribution in part a and b but not PDF of exponential distribution? Thanks
if you want to use the pdf you have to integrate .. which is the cdf.. less math to do
because pdf of a function is the probability per unit if you use it then it will not give you the probability ,instead if one uses the integration of pdf wrt "the unit" then you will get{(probability/unit)xunit} which will give you the probability also known as the cdf.
The failure rate of an electronic component is 2 per 300 hours on average.
a) Find the probability that the component will fail before 200 hours of operation?
b) Find the probability that the component is still working after 500 hours of operation. i need help with that anyone with an idea pls
oh my words! thanks so much!
Thank you so much
Thank you!!!!!!!!!!!!
THANK YOU!
Thank you! This was really good :D keep making videos!
Thanks bunch.
For part a in your example you wrote the question asking for P(x
Mohammad Al-Sweity i think... Because probability of a continuous random variable at particular point is zero...
sir when do we use the compliment rule ?
when wallahu fuckbar asks you to
Thanks 😊
shouldnt P(X>=10) be 1-P(X
I liked the video before I saw that part
For discrete variables this would be true, however `1-P(X
Yh
In continuous distributions P(X>=k) = P(X>k). Because doing Integral in a precise point is equal to 0.
1:30 that should be "inversely proportional"...and i think you mean "less than 0 seconds" at 2:48
Can't find other videos of Probability .
I thought v(x) was e(x squared) - the square of e(x) not just e(x squared)?
am confused in part a
you computed p(x
+Jasmeet Singh for Continuous Distributions they are consider to be the exact same (P(X=k) is considered to be Zero)
Thanks, I looked at the graph again and yes P(X=k) is always zero, Because in Continous random Vars we look for intervals. Thanks
Thank you
Thank you for the video! It is very helpful. (':
muuuuuuuuuuuuuuuito bom!!!
very good : )
How is P(X>=x)=1 ?
Thanks a lot this really help. BTW sorry i cant help but kind of laughed at 8:27 "Change it a BI*CH, sorry" haha
Oh my god thank you so much
why do you use the complement rule?
in general, it is always a useful thing to consider when tackling probability exercises. ...
Felt more like reading lines than explaining things , so If you explain more pictorially than it would help better
Can lambda be greater than 1?
no
isn't it λe^(-λx)?
That's pdf, for the questions cdf is required
thanks
thank u so much
2 AM in the morning, im now ready for my stats quiz. GG ENGR 371
hahaha 1:57 AM here, ready for my internals tomorrow
@@kumarprateek238 lmao 7 years ago. Dont remeber any of this shit. I prob failed that exam
@@emperorofthegalaxy1 lol
same I failed too
You can't wait less than 5 seconds? 2:46
thaaaaaaaaaaaaaaank you
chris o'Dowd teaches stastistics
HAND OVER YOUR GOLD LEPRECHAUN
Many So so so ...
why do you keep saying NOT? the answer is NOT point ....it's confusing. Other than that, good video.
"naught" is simply another name for zero.
oh okay. didn't know that. thanks :)
wasting time too much
THANK YOU!