The Exponential Distribution

Organized by textbook: learncheme.com/ Made by faculty at the University of Colorado Boulder, Department of Chemical & Biological Engineering.

[@beefandpotatoes6525]

A vert beautiful explanation of inverse relationship between Poisson and exponential distribution. Thank you.

[@themovingmachine7321]

thank you so much. I read many and many explaination but I cannot understand until saw yours

[@jarik2510]

Might need the community help: In the last example (earthquakes), why do we choose lambda to be events/time and not time/events if we are looking for the probability of a time interval?
Thanks in advance!

[@beefandpotatoes6525]

I think mean is 40/200. Our x is time and not number of events. Yes it would have been mean in case of Poisson which is number of events per time period.

[@leokeatonn]

oh my god THANK YOU, this is exactly what I needed

[@IgorKuts]

This was exactly what i was looking for and in a very concise and precise way. Thank you!

[@Rule-hf7nz]

Thanks! Great video

[@marwa_elnaggar]

Thank you 🌟

[@ghady31]

Excellent
Thanks

[@fendibasrifendi4229]

Lamdha is not the probability, lamdha means events occurs in certain time

[@user-fi9bm2ic5n]

🙏

[@heezyyyy]

i think 200/40 is the mean

[@beefandpotatoes6525]

look at my comment if you want. I think mean is 40/200.