Something different: Outliers, Artifacts, and Anecdotes

Some data does not fit the pattern we identify or the narrative that guides us. How people approach a datum that does not stand in line can be ... fuzzy. Grabbing a couple of  commonly shared thoughts on the matter: 

• trimming
• winsorization
• "the plural of anecdote is not data"
• "the exception proves the rule"

"You don't count because you're different," is not usually phrased that bluntly, but I have read or heard:

Data Science versus Curation and Registration: A Year in Museums

March means I've been museum focused for a year. Visiting. Volunteering. Interacting with guests, helping collections management. Classes on the skills and technology applied.

I've learned a lot. The museum approach to helping people learn, and helping people desire to learn, is amazing and deep. Museums do not have captive audiences. They have to market learning, make it desirable. And they do. And I think that data scientists should do so too.

Small Team Designs versus Learning Access

Today, as a museum gallery host, I watched a design failure - I'm confident it was unintentional - unnecessarily block access to one of the exhibits. I think it was because of a certain way the design team was all alike.

It was a mock 1920's telegraph, attempting to highlight communications from a small town that did not yet have telephone service. It has a vigorously ruggedized mock telegraph key for the guests to try using morse code to spell out messages. When pressed firmly, it sounds a buzzer so the guest can hear the dit-dah patterns of morse code. It has the same functionality as Morse code trainers had in the era of morse-using telegraphs. The one at the link has a key, a copy of the Morse code version in use at that facility, a buzzer, and a light.