Introduction to Probability : Exponential Distribution

[@ihsanerady9403]

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

[@robertaglarsen]

"The CDF can be written as the probability of the lifetime being less than some value x" That helped me soooo much, thanks!

[@Caffeinegoesinface]

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!

[@androidcobra679]

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:)

[@____________7035]

5:46 E and Var 2:50 PDF 4:10 CDF

[@kelvinok2000]

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.

[@codeguyross]

This was very helpful! Clear and easy to understand

[@kumarprateek238]

Thank you so much man. This is the only video which helped me so far

[@nanabenz7970]

This is a very nice and explicit video... great help. Thanks

[@mohammadpourheydarian5877]

I like it for being neatly written making it easy to copy fr future use.

[@ioannismarkoulakis4978]

finally the educational video I was searching

[@smokeyofficiial]

lovely video but much easier on the question C by just integrating f(x) within that limit 5 and 10. Good job man

[@Deadburd55]

this video helped so much once i figured out the e is a set number. kinda like pi.

[@famketheron7475]

Should've explained how you derived the cumulative distribution function from probability density function. Also we can solve P(5

[@charvakpatel962]

Thank You So Much Sir. It really helped me a lot. Keep on doing this kind of videos

[@simranchhabra1722]

Thankyou,the explanation is very clear.

[@hakanchunton823]

Very helpful video. Thank you!

[@harshitagarwal3557]

Thanks a lot..Earlier i was very much confused in waiting line theory..

[@abysswalkerx8434]

Thanks so much! Loved it even more because of the Irish accent!

[@joshuakoni5428]

Thank you! Was very helpful and clear to follow

[@reddotmobility]

Very Helpful ..Thank you so much for your upload

[@daleeps]

Beautiful, thank you! I could not find a detailed explanation anywhere

[@hannahburke6056]

Super super helpful. Thank you.

[@youngzenizer]

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) ??

[@khaledalhorani7965]

You made my day :) I can't thank you enough...

[@meghalbhansali5820]

Thank you, this was awesome! :)

[@tana4497]

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

[@AkshaySahu]

Thanks for such an informative video.

[@krishammond8851]

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.

[@AyodejiOyewole]

Really good presentation. Keep up the good job sir.

[@I_neyoh]

Thank you, i understood it perfectly.

[@bhavoh]

For part c), I don't understand how the complement of P(5

[@DragonflyStatistics]

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.

[@DragonflyStatistics]

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

[@bhavoh]

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!

[@DragonflyStatistics]

Call it Learning. I am sort of build up the library bit by bit - Also can't cram everything into one video

[@lewisclothier5496]

Don't get why you wouldnt just do P(5

[@user-qf8ur9sp1b]

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?

[@reddotmobility]

Can't find other videos of Probability .

[@winnieng5303]

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

[@MrSazid1]

if you want to use the pdf you have to integrate .. which is the cdf.. less math to do

[@akashray6447]

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.

[@Ekjyot07]

oh my words! thanks so much!

[@ukidding]

are earthquakes in a region truly independent? one earthquake may give rise to tremors and affect the future

[@ojfbahf]

sir when do we use the compliment rule ?

[@alfredwhittingdale9192]

when wallahu fuckbar asks you to

[@murtazahussain6301]

thanks

[@Ihatenicknames1]

Thank you! This was really good :D keep making videos!

[@lucretiastephenson3901]

Thank you!!!!!!!!!!!!

[@leylasolmaz3978]

good job!

[@fluffypanda3]

For part B it should be P(x>10) not greater than equal to

[@lesleymatsa2271]

Thank you so much

[@tarikurrahmanlikhon5734]

Thanks bunch.

[@tanyamusaidzi9911]

Thanks 😊

[@mohammadal-sweity789]

For part a in your example you wrote the question asking for P(x

[@samyukthaponnamanda7145]

Mohammad Al-Sweity i think... Because probability of a continuous random variable at particular point is zero...

[@melquicarvalho]

muuuuuuuuuuuuuuuito bom!!! very good : )

[@GSBhargav94]

shouldnt P(X>=10) be 1-P(X

[@takudzwamukura7172]

I liked the video before I saw that part

[@kalaninalak]

For discrete variables this would be true, however `1-P(X

[@zamanraja9531]

Yh

[@idobooks909]

In continuous distributions P(X>=k) = P(X>k). Because doing Integral in a precise point is equal to 0.

[@jasmeet17mast]

am confused in part a you computed p(x

[@DragonflyStatistics]

+Jasmeet Singh for Continuous Distributions they are consider to be the exact same (P(X=k) is considered to be Zero)

[@jasmeet17mast]

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

[@SuperFerdie1965]

I thought v(x) was e(x squared) - the square of e(x) not just e(x squared)?

[@monsturyo9041]

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

[@regularguyk6181]

why do you use the complement rule?

[@DragonflyStatistics]

in general, it is always a useful thing to consider when tackling probability exercises. ...

[@libertarianPinoy]

How is P(X>=x)=1 ?

[@maribelbravo1464]

Thank you for the video! It is very helpful. (':

[@ryanreal1783]

Can lambda be greater than 1?

[@ephraimspencer7059]

no

[@georgetorru9834]

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

[@dmccaulley9105]

THANK YOU!

[@markengelberg8079]

Thank you

[@stloiyf]

1:30 that should be "inversely proportional"...and i think you mean "less than 0 seconds" at 2:48

[@gchoi0215]

Oh my god thank you so much

[@sami-samim]

isn't it λe^(-λx)?

[@DavidMoscoeUni]

That's pdf, for the questions cdf is required

[@ryanbee3886]

thanks

[@balasandeep63]

thank u so much

[@emperorofthegalaxy1]

2 AM in the morning, im now ready for my stats quiz. GG ENGR 371

[@kumarprateek238]

hahaha 1:57 AM here, ready for my internals tomorrow

[@emperorofthegalaxy1]

@@kumarprateek238 lmao 7 years ago. Dont remeber any of this shit. I prob failed that exam

[@kumarprateek238]

@@emperorofthegalaxy1 lol

[@kumarprateek238]

same I failed too

[@utsavverma4595]

Felt more like reading lines than explaining things , so If you explain more pictorially than it would help better

[@laiarturs1889]

You can't wait less than 5 seconds? 2:46

[@davidsosa2307]

chris o'Dowd teaches stastistics

[@RashidByDay]

thaaaaaaaaaaaaaaank you

[@evanjones2974]

HAND OVER YOUR GOLD LEPRECHAUN

[@looploop6612]

Many So so so ...

[@RuriRukawa]

why do you keep saying NOT? the answer is NOT point ....it's confusing. Other than that, good video.

[@jiggsaw25]

"naught" is simply another name for zero.

[@RuriRukawa]

oh okay. didn't know that. thanks :)

[@limjiu]

[@bguom4194]

wasting time too much

[@nimarzv]

THANK YOU!