Three thoughts this time, for our first edition of Thoughts of the Week.

Thought #1

An estimate that is slightly biased but robust, model-independent, easy to compute, and easy to interpret, is better than one that is a non-biased, difficult to compute, mysterious, or not robust. That's one of the differences between data science and statistics.

Thought #2

Learning how to code, especially SQL, should be the last step in becoming a data scientist, because it creates highly rigid thinking, while data science is about ideas, problem solving, vision, initiative and flexibility (the opposite of coding).

Thought #3

Data science is not built on stats taught in traditional stats programs. It is based on modern stats that are not found in stats textbooks, though quite a bit can be found in modern machine learning books.

Source for this sarcastic picture: timoelioot.com

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Comment by Christian Cantos on November 23, 2014 at 7:39am

Dear Dr granville,

I would like to agree with thought nbr 2, but do you think that lower priority to coding skill is the current trend ?

From the beginning big data is a computer oriented technique, and most of the people using hadoop that I know are without stats knowledge, but with strong development skills, which makes them more employable than statisticians for instance.

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