From the course: Statistics and Python for Telecommunication: Using Data Analytics for Decision-Making in Modern Telecommunications
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Telecom applications of dispersion metrics - Python Tutorial
From the course: Statistics and Python for Telecommunication: Using Data Analytics for Decision-Making in Modern Telecommunications
Telecom applications of dispersion metrics
(bright music) - [Instructor] So from the perspective of telecom networks and telecom ecosystem where all we can use these different techniques, we have a data with us we would like to get into more details about the data sets and database. We can calculate the range to understand and get a quick comparison on the extreme values. What are the extremities? What is the minimum? What is the maximum value? As we said in a network, we may would like to understand what is the user data speeds or user throughput days. How my competition is doing, are they doing good or bad? How do we come to know? We need to compare these different values as compared to their dataset or our dataset. And that's where the benchmark also comes in the picture. We would like to see what is the average throughput. Okay, we calculated it, it's an essential tendency. Now we would like to understand what is the range, what is the minimum and the maximum data speeds a customer is getting in Operator A, Operator B…
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