## Cat and whisker plots – sampling from the Quick, Draw! dataset

Last night, I saw a tweet announcing that Google had made data available on over 50 million drawings from the game Quick, Draw! I had never played the game before, but it is pretty cool. The idea behind the game is whether a neural network can learn to recognize doodling – watch the video below for more about this (with an example about cats of course!)

For each game, you are challenged to draw a certain object within 20 secs, and you get to see if the algorithm can classify your drawing correctly or not. See my attempt below to draw a trumpet, and the neural network correctly identifying that I was drawing a trumpet.

Since I am clearly obsessed with cats at the moment, I went straight to the drawings of cats. You can see ALL the drawings made for cats (hundred of thousands) and can see variation in particular features of these drawings. I thought it would be cool to be able to take a random sample from all the drawings for a particular category, so after some coding I set up this page: learning.statistics-is-awesome.org/draw/. I’ve included below each drawing the other data provided in the following order:

• the word the user was told to draw
• the two letter country code
• the timestamp
• whether the drawing was correctly classified
• number of individual strokes made for the drawing

[Update: There are now more variables available – see this post for more details]

So, on average, how many whiskers do Quick, Draw! players draw on their cats?

I took a random sample of 50 drawings from those under the cat category using the sampling tool on learning.statistics-is-awesome.org/draw/. Below are the drawings selected 🙂

Counting how many individual whiskers were drawn was not super easy but, according to my interpretation of the drawings, here is my sample data (csv file). Using the awesome iNZight VIT bootstrapping module (and the handy option to add the csv file directly to the URL e.g. https://www.stat.auckland.ac.nz/~wild/VITonline/bootstrap/bootstrap.html?file=http://learning.statistics-is-awesome.org/draw/cat-and-whisker-plots.csv), I constructed a bootstrap confidence interval for the mean number of whiskers on cat drawings made by Quick, Draw! players.

So, turns out it’s a fairly safe bet that the mean number of whiskers per cat drawing made by Quick, Draw! players is somewhere between 2.2 and 3.5 whiskers. Of course, these are the drawings that have been moderated (I’m assuming for appropriateness/decency). When you look at the drawings, with that 20 second limit on drawing time, you can see that many players went for other features of cats like their ears, possibly running out of time to draw the whiskers. In that respect, it would be interesting to see if there is something going on with whether the drawing was correctly classified as being a cat or not – are whiskers a defining feature of cat drawings?

I reckon there are a tonne of cool things to explore with this dataset, and with the ability to randomly sample from the hundreds and hundreds of thousands of drawings available under each category, a good reason to use statistical inference 🙂 I like that students can develop their own measures based on features of the drawings, based on what they are interested in exploring.

After I published this post, I took a look at the drawings for octopus and then for octagon, a fascinating comparison.

I wonder if players of Quick, Draw! are more likely to draw eight sides for an octagon or eight legs for an octopus? I wonder if the mean number of sides drawn for an octagon is higher than the mean number of legs draw for an octopus?

## It’s raining cats and dogs (hopefully)

In April 2017, I presented an ASA K-12 statistics education webinar: Statistical reasoning with data cards (webinar). Towards the end of the webinar, I encouraged teachers to get students to make their own data cards about their cats. A few days later, I then thought that this could be something to get NZ teachers and students involved with. Imagine a huge collection of real data cards about dogs and cats? Real data that comes from NZ teachers and students? Like Census At School but for pets 🙂 I persuaded a few of my teacher friends to create data cards for their pets (dogs or cats) and to get their students involved, to see whether this project could work. Below is a small selection of the data cards that were initially created (beware of potential cuteness overload!)

The project then expanded to include more teachers and students across NZ, and even the US, and I’ve now decided to keep the data card generator (and collection) page open so that the set of data cards can grow over time. Please use the steps below to get students creating and sharing data cards about their pets.

Creating and sharing data cards about dogs and cats

Inevitably, there will be submissions made that are “fake”, silly or offensive (see below).

Data cards submitted to the project won’t automatically be added to any public sets of data cards, and will be checked first. Just like with any surveying process that is based on self-selection, is internet based and relies on humans to give honest and accurate answers, there is the potential for non-sampling errors. To help reduce the quantify of “fake” data cards, if you are keen to have your students involved with this project it would be great if you could do the following:

1. Talk to your students about the project and explain that the data cards will be shared with other students. They will be sharing information about their pet and need to be OK with this (and don’t have to!). The data will be displayed with a picture of their pet, so participation is not strictly anonymous. All of this is important to discuss with students as we need to educate students about data privacy 🙂

2. When students submit their data, they are given the finished data card which they can save. Set up a system where students need to share the data card they have created with you e.g. by saving into a shared Google drive or Dropbox, or by emailing the data card to you. The advantage for you of setting up this system is that you get your class/school set of data cards to use however you want. The advantage for me is that this level of “watching” might discourage silly data cards being created.

Pet data cards

The data collection period for this set of data cards was 1 May 17 to 19 May 17.

The diagram below shows the data included on each data card:

Additional data that could be used from each data card includes:

• Whether the pet photo was taken inside or outside
• Whether the pet photo is rotated (and the angle of rotation)
• The number of letters in the pet name
• The number of syllables in the pet name