Glad it helped! Perhaps you might like the other videos on the channel too (if you haven't already seen them). A full categorised listing can be found here: iaincollings.com
Excellent explanation and great art of moving two pages over the main page to make the exact explanation 👍 Most important factor is the clear difference between the lambda values in the two distributions. Most needed explanation. Thanks for your Excellent explanation 👍
What is the resolution of this exercise: Consider a queuing model with two attendants and a waiting position operating under steady-state conditions. Suppose that if a customer arrives and finds both agents busy and the waiting position unoccupied, then the customer will wait as long as necessary for service. If the customer finds both attendants busy and the waiting position also occupied, he leaves immediately. Customers access the system according to a Poisson process with a rate of 2 customers per hour and that service follows an exponential distribution with a mean of 1 hour. The proportion of customers who arrive at the system and will not be served is: a)2/5 b)1/8 c)2/3 d)2/7 e)1/6
A question: In the exponentional distribution showing the distribution of time between events, by increasing \lambda the variance of exponential distribution decreases, while we expect the variance increases, since for large value of \lambda the Poisson distribution become more scattered. right?
I think you may have missed the point I made about the fact that lambda represents a different thing in the two equations (ie. for each Random variable). At the 3:30 min mark I explain what lambda is for the Poisson distribution, and a the 6:30 min mark I explain it for the exponential distribution. They are different things. Really, it would be better if a different symbol was used in one of the cases (eg. a different Greek letter), but that's not what happened over time when these distributions were being formulated and conventions were setting in.
Hi, found this explanation very helpful and interested to learn more about the Homogeneous Poisson process, Heterogeneous Poisson process, and heterogeneous Thomson process. Let me know where can I find this? Thank you!
I took a EE class that was in my opinion a total waste of time, a stats class called Random Signals Analysis that talks all about these random processes and other things. However as I get into my senior year of EE, I realize how important that class was, I feel bad for writing a class survey that said that class was ridiculous and a waste for us lol.
I've been looking for a quick, clean and simple explanation for a while and your content was what I was looking for. Thanks for content!
Glad it helped! Perhaps you might like the other videos on the channel too (if you haven't already seen them). A full categorised listing can be found here: iaincollings.com
Highlighting the different interpretations of lambda for Poisson and exponential distributions has saved me a lot of headache. Cheers!
I'm so glad it helped. I know that issue confuses lots of people.
@@iain_explainsstochastic process
Your teaching method is so minimalistic and to the point. cheer
Glad you like it.
Poisson distribution just come in time for preparing an exam in wireless. Thanks a lot, professor.
That's great timing. Good luck on your exam.
studying for my qualifying exam.... thank you for using pen and paper! so helpful just to go step by step
I'm so glad it was helpful - and that you liked the pen and paper approach!
Professor Iain explains very well because he understands it very well, great video thank you!
Glad you think so!
Excellent explanation and great art of moving two pages over the main page to make the exact explanation 👍
Most important factor is the clear difference between the lambda values in the two distributions. Most needed explanation. Thanks for your Excellent explanation 👍
Thanks for your nice comment. I'm glad it was helpful!
When I was sunk in a problem, your videos always inspire me. Thank you for the wonderful explain!
I'm so glad my videos are inspiring you! It's great to hear.
What is the resolution of this exercise:
Consider a queuing model with two attendants and a waiting position operating under steady-state conditions. Suppose that if a customer arrives and finds both agents busy and the waiting position unoccupied, then the customer will wait as long as necessary for service. If the customer finds both attendants busy and the waiting position also occupied, he leaves immediately.
Customers access the system according to a Poisson process with a rate of 2 customers per hour and that service follows an exponential distribution with a mean of 1 hour. The proportion of customers who arrive at the system and will not be served is:
a)2/5 b)1/8 c)2/3 d)2/7 e)1/6
i like your work very much .. your explanation is very clear and organized..and its done in the best way ..with a paper and a pen only.😍😊
Thank you so much 😀 I'm glad you like the videos.
thank you for clarifying the difference between the two lambdas!
Glad you found it helpful.
Thanks for this amazing video, it really helped in understanding the core concepts. Also very helpful the explanation about the lambdas!
I'm so glad it was helpful!
One of the best explanations. Thank you for the content. Keep them coming.
Thanks. I'm glad you like the videos.
Such a passion to teach to the world. So much of hard work. great. Keep going. :)
Thanks for your nice comment. I'm glad you like the videos.
I'm confused by 3Gpp FTP traffic model about why there is a expotional inter arrival time. Your video helped me out. Thank you professor!
Glad it helped!
Concise and precise! Thank you for such a beautifully detailed explanation!
Glad it was helpful!
thank you for explaining it clearly
Glad it was helpful!
Thanks! Now I get it!
I'm glad you found it helpful!
Very helpful.
Glad to hear!
Thanks sir , very helpful indeed
Glad you found it useful.
Good explanation!
Glad it was helpful!
🌟🌟🌟🌟Magnificent Explanation 🌟🌟🌟🌟 Really ! Statistics is mind blowing ! Needs more thoughtfulness to understand it.
I'm so glad yo like the video.
There is no scope of statistics in India professor but thank you so much for the best explanation......
It's my pleasure
so is the primary defining quality of a Poisson Process that the Time between events is Exponentially distributed?
Very nice video
Thanks. I'm glad you liked it.
awesome content dude, you have earnt a like and subscribe! thanks for the clear and thorough explanation :D
That's great to hear. I'm glad you liked it.
A question: In the exponentional distribution showing the distribution of time between events, by increasing \lambda the variance of exponential distribution decreases, while we expect the variance increases, since for large value of \lambda the Poisson distribution become more scattered. right?
I think you may have missed the point I made about the fact that lambda represents a different thing in the two equations (ie. for each Random variable). At the 3:30 min mark I explain what lambda is for the Poisson distribution, and a the 6:30 min mark I explain it for the exponential distribution. They are different things. Really, it would be better if a different symbol was used in one of the cases (eg. a different Greek letter), but that's not what happened over time when these distributions were being formulated and conventions were setting in.
Excellent
Thank you so much.
Hi, found this explanation very helpful and interested to learn more about the Homogeneous Poisson process, Heterogeneous Poisson process, and heterogeneous Thomson process. Let me know where can I find this? Thank you!
Thanks for the suggestions. I've put them on my "to do" list for a future video.
Appreciated your time and good work to help curious students to learn statistics in an easy and effective way! @@iain_explains
amazing
Glad you think so!
Thank you!
You're welcome!
Excellen max point!
Thanks. Glad you liked it.
More concrete sample would be nice
I Didn't understand what is the difference between lambadas in exponential and poisson 🤔
Lambda in exponential is only the rate
He loss me after the graphs
I took a EE class that was in my opinion a total waste of time, a stats class called Random Signals Analysis that talks all about these random processes and other things. However as I get into my senior year of EE, I realize how important that class was, I feel bad for writing a class survey that said that class was ridiculous and a waste for us lol.
I'm glad you've seen the light! 😁