each students preferred caffeine source is shown, but the visualization may not capture the full complexity of their choices. why someone may choose a hot drink over an energy drink can be influenced by various factors such as taste preferences, cultural influences, or even the social aspect of drinking hot beverages.
a major fault in data visualization is reducing lived experiences into simplified metrics. click on each dot to see their circumstances and how data visualisation can never fully capture the complexities of lived experiences.
data collection can lead to oversimplified representations of complex realities. each person's caffeine consumption is reduced to a number based on the ranges provided, and this demonstrates the importance of thoughtful data collection and the limitations of data visualisation in capturing the nuances of human experiences.