Four Mistakes To Avoid If You’re Analyzing Data
The post highlights four (4) common mistakes in analyzing data, with visualizations.
Four (4) seems like a low number, at least in my personal experience. 😉
Still, I am encouraged that the post concludes with:
Analyzing data is not easy. We hope this post helps. Has your team made or avoided any of these mistakes? Do you have suggestions for a future post? Let us know; we’re @plotlygraphs, or email us at feedback at plot dot ly.
I just thought of a common data analysis mistake, reliance on source or authority.
As we saw in Photoshopping Science? Where Was Peer Review?, apparently peer reviewers were too impressed by the author’s status to take a close look at photos submitted with his articles. On later and closer examination, those same photos, as published, revealed problems that should have been caught by the peer reviewers.
Do you spot check all your data sources?