From the course: Statistics and Python for Telecommunication: Using Data Analytics for Decision-Making in Modern Telecommunications
Join today to access over 24,900 courses taught by industry experts.
Use cases in telecom: Poisson distribution - Python Tutorial
From the course: Statistics and Python for Telecommunication: Using Data Analytics for Decision-Making in Modern Telecommunications
Use cases in telecom: Poisson distribution
(upbeat music) - [Instructor] Now what are the different use cases of the poisson distribution? Again, we can look into the network reliability in this case, and we would like to see that how often a call drop may happen across different sites, across different time domains. Maybe a busy hour, we would like to calculate it, a network reliability for that particular timestamp. So that is possible. If you would like to validate the service level agreement, that is also possible with your vendor, whatever the agreement you have, or even if you are doing it in-house, the kind of quality analysis you can do. You can see that either the call drops are exceeding the particular threshold or not. If it is set to a certain level by poisson distribution, you can see that what is the probability that there would be a more number of cold drops beyond that particular threshold. So it gives you a fair idea, like how much you're going beyond particular threshold. Because sometimes, in SLA, you have a…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.