Sean Owen created this handy cheat sheet that shows the most common probability distributions mapped by their underlying relationships.

Probability distributions are fundamental to statistics, just like data structures are to computer science. They’re the place to start studying if you mean to talk like a data scientist.

Owen argues that the probability distributions relate to each other in intuitive and interesting ways that makes it easier for you to recall them. For instance, several follow naturally from the Bernoulli distribution. Having this map by hand should thus help you really understand what these distributions imply.

On top of that, it’s just a nice geeky network poster!

Now, Sean didn’t just make a fancy map. In the original blog he also explains each of the distributions and how it relates to the others. Having this knowledge is vital to being a good data scientist / analyst.

You can sometimes get away with simple analysis using R or scikit-learn without quite understanding distributions, just like you can manage a Java program without understanding hash functions. But it would soon end in tears, bugs, bogus results, or worse: sighs and eye-rolling from stats majors.

For instance, here’s Sean explaining the Binomial distribution:

The binomial distribution may be thought of as the sum of outcomes of things that follow a Bernoulli distribution. Toss a fair coin 20 times; how many times does it come up heads? This count is an outcome that follows the binomial distribution. Its parameters are n, the number of trials, and p, the probability of a “success” (here: heads, or 1). Each flip is a Bernoulli-distributed outcome, or trial. Reach for the binomial distribution when counting the number of successes in things that act like a coin flip, where each flip is independent and has the same probability of success.

Typography plays a crucial role in design and finding the right font can take a few minutes or a few days. According to Vijay Verma, every font has specific design intent, communicates certain attributes. Fortunately, there are many (free) online libraries to help you these days, such as Google Fonts, MyFonts, Lineto, TypeAtelier, or TypeMates.

Geometric fonts

Geometric fonts are sans-serif typefaces building on geometric shapes like near-perfect circles and squares.

Today many technology brands currently deploy geometric fonts that represent minimalism, simplicity, and cleanliness, like — Product Sans by Google, Cereal by Airbnb etc.

Design experts argue (here, here) that the geometric fonts below will work very well in modern user interfaces. These fonts are used among others by IKEA, Spotify, NASA, AirBnB, Volkswagen, Apple, Marvel, and Snapchat. Can you guess which is which?

You can click the images to visit the source pages.

Futura

Gilroy

Brown

Circular

Gordita

Cera PRO

Sailec

Avenir Next

GT Walsheim

TT Commons

Free Geometric Fonts

Although very aesthetically pleasing, some of these fonts can be pretty expensive if you’re just hobbying. While there are many more fonts out there that may be perfectly free.

Do have a look atGoogle Fonts, as they provide nearly a 1000 pretty interesting typefaces, all for free!

Moreover, if you’re specifically looking for a geometric font, have a look at these 18 free geometric typefaces!

Saskia Freeke (twitter) is a Dutch artist, creative coder, interaction designer, visual designer, and educator working from Amsterdam. She has been creating an awesome digital art piece for every day since January 1st 2015. Her ever-growing collection includes some animated, visual masterpieces.

My personal favorites are Saskia’s moving works, her GIFs:

Saskia uses Processing to create her art. Processing is a Java-based language, also used often by Daniel Shiffmann whom we know from the Coding Train.