I’m doing some form of data visualization learning for 180 days because I need to #JFDI. See post explaining how and why I’m doing this.
1/3 of the way through! So much learned about working, devoting self to doing a bit everyday, deciding how to narrow in focus, and the like. Will likely reflect on this more tomorrow, but it was soccer night tonight, just posting my learning summary for today.
Reading and Learning Data Visualization Theoretically/Critically:
Reading Nathan Yau’s book Data Points – Visualization that Means Something
p. 31-45 Uncertainty and Context Sections
- In context of people misinterpreting estimates and uncertainty – really “consider what your data truly represents. Always take uncertainty and variability into account” p. 35
- “You have to know the who, what, when, where, why, and how-the metadata or the data bout the data- before you can know what the numbers are truly about.” p. 37
- “Things can change across cities, states, and countries just as they do over time. For example, it’s best to avoid global generalizations when the data comes from only a few countries. The same logic applies to digital locations. Data from websites, such as Twitter or Facebook, encapsulates the behavior of its users and doesn’t necessarily translate to the physical world.” p.38