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!
oh my god THANK YOU, this is exactly what I needed
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.
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❤️🙏🏾
Excellent
Thanks
Thank you 🌟
🙏
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.