A Standard Problem: Determining Sample Size Recently, I was tasked with a straightforward question: "In an A/B test setting, how many samples do I have to collect in order to obtain significant results?" As ususal in statistics, the answer is not quite as straightforward as the question, and it depends quite a bit on the framework. In this case, the A/B test was supposed to test whether the effect of a treatment on the success rate p had the assumed size e.
I have a personal Google account, complete with gmail, gdrive and everything else. I first opened it up as a sort of spam email for all kinds of logins, but started to it use more and more due to its convenience. I was always slightly worried about the magnitude of data collected by Google on me, yet I never found a way to pinpoint exactly the extent of my slight worrying.
Hello world! My name is Sebastian Schweer, and I am a Data Scientist. This job description is increasingly popular, but it is notoriously difficult to describe precisely, what that entails. Let me show you one of my favourite definitions: Source. My job requires me to spend a lot of time each day writing code in varying languages, mostly R but also Python and SAS. This inevitably leads me to spend a lot of time thinking about both code as well as the process of programming itself.