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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Additional Reading

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• How to detect spurious correlations, and how to find the real ones
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• 66 job interview questions for data scientists

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