Introduction to Probability : Exponential Distribution

www.Stats-Lab.com | www.bit.ly/IntroStats | Continuous Probability Distributions
A review of the exponential probability distribution

[@katecockerille8736]

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:)

[@famketheron7475]

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

[@nanabenz7970]

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

[@simranchhabra1722]

Thankyou,the explanation is very clear.

[@daleeps]

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

[@____________7035]

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

[@hakanchunton823]

Very helpful video. Thank you!

[@robertaglarsen]

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

[@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) ??

[@smokeyofficiial]

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

[@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.

[@reddotmobility]

Very Helpful ..Thank you so much for your upload

[@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

[@charvakpatel962]

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

[@fluffypanda3]

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

[@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

[@AkshaySahu]

Thanks for such an informative video.

[@codeguyross]

This was very helpful! Clear and easy to understand

[@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

[@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?

[@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.

[@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

[@ukidding]

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

[@lucretiastephenson3901]

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

[@utsavverma4595]

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

[@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.

[@abysswalkerx8434]

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

[@stloiyf]

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

[@mohammadpourheydarian5877]

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

[@harshitagarwal3557]

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

[@Deadburd55]

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

[@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

[@meghalbhansali5820]

Thank you, this was awesome! :)

[@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!

[@nimarzv]

THANK YOU!

[@ioannismarkoulakis4978]

finally the educational video I was searching

[@ojfbahf]

sir when do we use the compliment rule ?

[@alfredwhittingdale9192]

when wallahu fuckbar asks you to

[@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.

[@reddotmobility]

Can't find other videos of Probability .

[@joshuakoni5428]

Thank you! Was very helpful and clear to follow

[@I_neyoh]

Thank you, i understood it perfectly.

[@lesleymatsa2271]

Thank you so much

[@maribelbravo1464]

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

[@hannahburke6056]

Super super helpful. Thank you.

[@khaledalhorani7965]

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

[@murtazahussain6301]

thanks

[@libertarianPinoy]

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

[@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

[@SuperFerdie1965]

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

[@Ekjyot07]

oh my words! thanks so much!

[@gchoi0215]

Oh my god thank you so much

[@kumarprateek238]

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

[@sami-samim]

isn't it λe^(-λx)?

[@DavidMoscoeUni]

That's pdf, for the questions cdf is required

[@melquicarvalho]

muuuuuuuuuuuuuuuito bom!!! very good : )

[@leylasolmaz3978]

good job!

[@Ihatenicknames1]

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

[@tarikurrahmanlikhon5734]

Thanks bunch.

[@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...

[@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 :)

[@laiarturs1889]

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

[@tanyamusaidzi9911]

Thanks 😊

[@davidsosa2307]

chris o'Dowd teaches stastistics

[@evanjones2974]

HAND OVER YOUR GOLD LEPRECHAUN

[@dmccaulley9105]

THANK YOU!

[@ryanreal1783]

Can lambda be greater than 1?

[@ephraimspencer7059]

no

[@looploop6612]

Many So so so ...

[@markengelberg8079]

Thank you

[@ryanbee3886]

thanks

[@regularguyk6181]

why do you use the complement rule?

[@DragonflyStatistics]

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

[@AyodejiOyewole]

Really good presentation. Keep up the good job sir.

[@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

[@RashidByDay]

thaaaaaaaaaaaaaaank you

[@limjiu]

[@bguom4194]

wasting time too much

[@FuckingGolems]

How do you find the lambda of an exponential random variable?