Good models + Bad data = Bad analysis
Example showing how to diagnose bad data in data science models
Aggregation
The index of an index is confusion
The puzzle of negative numbers
How effective visualization brings data alive
Bringing data alive
An overused chart, why it fails, and how to fix it
A chart with conceptual appeal but fails the data
Reality check on the long tail
Another over-sold story?
Making charts beautiful without adding unneeded bits
What is the message?