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!
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.
thank you so much. I read many and many explaination but I cannot understand until saw yours
A vert beautiful explanation of inverse relationship between Poisson and exponential distribution. Thank you.
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!
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.
oh my god THANK YOU, this is exactly what I needed
This was exactly what i was looking for and in a very concise and precise way. Thank you!
Thanks! Great video
This was very helpful, thanks to you❤️🙏🏾
Thank you 🌟
Excellent
Thanks
🙏
Lamdha is not the probability, lamdha means events occurs in certain time
i think 200/40 is the mean
look at my comment if you want. I think mean is 40/200.