As part of our VisiMetrix roadmap, we’ve been researching how to predict Radio Access Network (RAN) congestion. In this post, Farooq explains how our data science team built a model that can effectively predict RAN congestion up to 7 days into the future and, in doing so, provide an early warning system for our customers’ network operations teams.
In part three of Introduction to Hypothesis Testing series we outlined some code samples for how to perform t-tests on mean-based samples. This post will now go into more detail for frequency-based samples.
The recent DataVizLive was held entirely online, due to COVID and like the rest of the world, they had to quickly learn to do things remotely-first. Although it wasn't faultless, it was still very engaging and filled with experienced speakers, who delivered practical visualisations. In this post, I will share my key takeaways from the event!
In part two of Introduction to Hypothesis Testing series we outlined some code samples for how to perform z-tests on proportion-based samples. This post will now go into more detail for mean-based samples.
When you analyse data you’re making lots of choices about what tools to use, and what the results mean. The aim of this post is to make clear the nature of the kinds of choices an analyst will make when examining data, and what responsibility is on you - the reader - to understand these choices before accepting the results of someone else’s analysis.
Knowing where the problem lies is only a half-success. The other half is having the knowledge to fix it. Recently our colleague Adam was tasked with getting to the bottom of an issue in one part of a system we were developing for a client. It required quite a bit of detective work, some experimentation, and ultimately learning. Here's the story of his journey.
In part one of this series we introduced the concept of hypothesis testing, and described the different elements that go into using the various tests. It ended with a cheat-sheet to help you choose which test to use based on the kind of data you’re testing. In this second post we will go into more detail on proportion-based samples.