Visual Statistics

Visual Statistics as a brief reminds us of how versatile statistics can be in such different contexts and how they can help us to make sense of what is around us. As Alan Smith states in his TED Talk, “(…) statistics are about us. If you look at the etymology of the word statistics, it’s the science of dealing with data about the state or the community that we live in. So, statistics are about us as a group, not us as individuals” (Smith, 2016)

On the 28th of September, both classes, Graphic Design and Design, Innovation and Brand Management joined to get the content for this assignment. The first part of the day we were asked to come up with questions that would give information about who we are as a group. At this point, we were not seeing the full picture so we just brainstormed about questions of every day that would suit the task.

Together, we created eighty-seven questions within six categories: food, body, values, relationships, habits and features. Next, the group of 42 students were asked to answer the questions by positioning themselves on one side of the room. For each question, there was one picture taken and finally, the content for this assignment was created.

Visual Statistics2


The objective was to create and present any kind of statistic information in order to produce knowledge about the cohort. As it is stated in the brief, “Your creative challenge is to analyse, present and conclude a range and/or sample of information based on the data collated”. Additionally, we were not allowed to use the pictures in the presentation, in other words, we should create our own visual content in order to communicate the output of the exercise.

This brief was open to any kind of solution. This time we were not asked to produce any kind of research. The task was only about finding patterns and connections in those pictures. Along with the brief, we were given examples of Visual Statistics from different authors and designers.

Visual Statistics . png

I chose to make “Do you work best: morning or evening?” the central question in my concept. Twelve students answered morning and thirty said they preferred to work during the evening. This question belongs to the habits category. Consequently, by following the morning individuals, I decided to investigate their habits.

Visual Statistics . png3

All Morning students prefer eating in yet, eighty per cent of them prefers going out to a pub than staying home or going to a club. Overall, at least fifty per cent of this students have the same answer to a question. Moreover, on average, the percentage of agreement is seventy-nine per cent.

The next step was to look at the bigger picture and compare the previous sample with the answers of the forty-two students. Then, in fact, the morning students agree most of the times with the majority, except for the question about the favourite time to work.

Finally, coming back to the sample of the students that prefer to work in the morning, I decided to analyse their behaviour individually. Accordingly to the pictures, I could identify four individuals that always answered the same. Their choice was always equivalent with the favourite answer of the morning students group.


The core of this project was to transform simple data and add meaning to it in order to produce information. I have chosen to limit my data to a specific category, once all the data share characteristics between each other. This makes the task of finding connections and relations between the answers of these students easier.

After the presentation, I was given feedback about the possibility to use storytelling into my communication. This idea of connections and relations within a category could be an advantage for the creation of a communication based on a storyline.

The visual communication I chose was to use circular graphs. This simple and direct data visualization only reveals one question at a time, however, it shows the proportion between the answers of the sample in comparison with the total. To conclude, this project allowed a variety of different approaches and my response was a clean and efficient way to communicate the results I have found.


Flight Patterns (s.d.) At: (Accessed on 11 January 2019)

Flourish | Data Visualisation & Storytelling (s.d.) At: (Accessed on 12 January 2019)

Information designer Nicholas Felton (s.d.) At: (Accessed on 11 January 2019)

Jordan, C. (2008) Turning powerful stats into art. [2008] At: (Accessed on 11 January 2019)

OECD Better Life Index (s.d.) At: (Accessed on 11 January 2019)

Peçanha, S. and Wallace, T. (2015) ‘The Flight of Refugees Around the Globe’ In: The New York Times 20 June 2015 [online] At: (Accessed on 11 January 2019)

Smith, A. (2016) Why you should love statistics. [2016] At: (Accessed on 11 January 2019)

The Data Visualisation Catalogue (s.d.) At: (Accessed on 12 January 2019)

The Guantánamo Docket (s.d.) In: The New York Times At: (Accessed on 11 January 2019)

The Water We Eat (s.d.) At: (Accessed on 11 January 2019)

United States gun death data visualization by Periscopic (s.d.) At: (Accessed on 11 January 2019)

What the World Eats (s.d.) At: (Accessed on 11 January 2019)

Wong, W. (2010) ‘The Universal Principles of Design: The Five Hat Racks’ At: (Accessed on 11 January 2019)

work — giorgialupi (s.d.) At: (Accessed on 11 January 2019)

Icons from from the Noun Project

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