Matthew Norton

Visualizing Uncertainty


Visualizing Uncertainty

Graduate Work, Fall 2017

This work was a project based off a graduate's thesis work regarding ways to visualize uncertainty when displaying data. We were assigned to re-visualize the data from a given newspaper article. My data is from a poll regarding how likely Americans are to change their minds about Donald Trump.



I first explored different ways to visualize a comparison between two wholes. I had ideas like using shapes, such as rectangles or circles, and then dividing them into their given parts. I played around with using two sets of 100 squares in various formations. I found that the 100 squares was the easiest to quickly compare one with another.


Final work

I organized the 100 squares into a 10x10 grid and then shaded each square for it's respected placeholder using the data given. The interactive graphic allows you to see the uncertainty of each "stance." For this data, the margin of error was +/- 3.5%; so the blinking squares are showing the range between the lowest (-3.5%) and highest (+3.5%) margin of error. Users can switch between "stances" to see how the uncertainty affects the data.


This specific graphic compares how many Republicans and Democrats responded with "Approve - Won't Change". You can see on the left that 53% of Republicans and 5% of Democrats gave this response. With that, you can obviously see that there are way more dark red squares than dark blue squares. Finally, the flashing squares are showing the possible range with the margin of error applied. Since the margin of error for this information is +/- 3.5%, each "amount" is going up and down 3.5%. This motion graphic is intended to quickly translate the margin of error to the reader. They should quickly realized that, for example, even though it says 53%, with the MoE at +/- 3.5%, it can be anywhere from 49.5% to 57.5%.