Posts with R code
In this post, we are going to replicate an analysis from the current issue of Scientific American about a common mathematical pitfall of Coronavirus antibody tests with R.
Many people think that when they get a positive result of such a test they are immune to the virus with high probability. If you want to find out why nothing could be further from the truth, read on!
Continue reading “COVID-19: False Positive Alarm”
Google does it! Facebook does it! Amazon does it for sure!
Especially in the areas of web design and online advertising, everybody is talking about A/B testing. If you quickly want to understand what it is and how you can do it with R, read on!
Continue reading “Learning Data Science: A/B Testing in Under One Minute”
It is not easy to create secure passwords. The best way is to let a computer do it by randomly combining lower- and upper-case letters, digits and other printable characters.
If you want to learn how to write a small function to achieve that read on!
Continue reading “Learning R: Build a Password Generator”
Our intuition concerning randomness is, strangely enough, quite limited. While we expect it to behave in certain ways (which it doesn’t) it shows some regularities that have unexpected consequences. In a series of seemingly random posts, I will highlight some of those regularities as well as consequences. If you want to learn something about randomness’ strange behaviour and gain some intuition read on!
Continue reading “Learning Statistics: Randomness is a Strange Beast”
About two years ago the renowned medical journal “The Lancet” came out with the rather sensational conclusion that there is no safe level of alcohol consumption, so every little hurts! For example, drinking a bottle of beer per day (half a litre) would increase your risk of developing a serious health problem within one year by a whopping 7%! When I read that I had to calm my nerves by having a drink!
Ok, kidding aside: in this post, you will learn how to lie with statistics by deviously mixing up relative and absolute changes in risks, so read on!
Continue reading “Lying with Statistics: One Beer a Day will Kill you!”
Star Wars is somewhat nerdy, R definitely is… what could be more worthwhile than combining both 😉
This Sunday was Star Wars Day (May the 4th be with you!) and suitable for the occasion we will do a little fun project and implement the following xkcd flowchart, which can give us more than 2 million different Star Wars plots.
Even if you are new to R, the used code should be comprehensible, so read on!
Continue reading “Learning R: Build xkcd’s Star Wars Spoiler Generator”
In one of my most popular posts So, what is AI really? I showed that Artificial Intelligence (AI) basically boils down to autonomously learned rules, i.e. conditional statements or simply, conditionals.
In this post, I create the simplest possible classifier, called ZeroR, to show that even this classifier can achieve surprisingly high values for accuracy (i.e. the ratio of correctly predicted instances)… and why this is not necessarily a good thing, so read on!
Continue reading “ZeroR: The Simplest Possible Classifier, or Why High Accuracy can be Misleading”
The global lockdown has slowed down mobility considerably. This can be seen in the data produced by our ubiquitous mobile phones.
Apple is kind enough to make those anonymized and aggregated data available to the public. If you want to learn how to get a handle on those data and analyze trends with R read on!
Continue reading “COVID-19: Analyze Mobility Trends with R”
One widely used graphical plot to assess the quality of a machine learning classifier or the accuracy of a medical test is the Receiver Operating Characteristic curve, or ROC curve. If you want to gain an intuition and see how they can be easily created with base R read on!
Continue reading “Learning Data Science: Understanding ROC Curves”
One of the biggest problems of the COVID-19 pandemic is that there are no reliable numbers of infections. This fact renders many model projections next to useless.
If you want to get to know a simple method how to roughly estimate the real number of infections and expected deaths in the US, read on!
Continue reading “COVID-19 in the US: Back-of-the-Envelope Calculation of Actual Infections and Future Deaths”
