Guiding principles of the DTR

1. Data doesn’t say anything.

2. We say things about data that we decided was worth collecting and how to collect.

3. There is no such thing as “actionable, data-driven insights”.

4. Down with the tyranny of means!

5. If there is no documentation, we throw the data away.

6. Theories tell us where to look.

7. Data science is a science and an art.

8. Data science is much more than programming.

9. Data science is for everyone.

10. Statistical significance is overrated.

11. Don’t get us started on pie charts.

12. Data dashboards are not as useful as they seem.

13. We begin from our expertise and instincts, and we are prepared to be wrong.

14. We ask: “What am I missing?”

15. We ask: “How was this measured?”

16. We ask: “How might my data be wrong, and in what way might this bias my results?”

17. The causal mechanism is our holy grail.

18. We operate at the intersection of imagination, critical thinking, and quantitative skills (in that order).

19. The intersection of data science and subject matter expertise represents the lowest hanging fruit for discovery.

20. We begin from a place of curiosity.

21. We are humble but not afraid.

Honorable mentions from experts that I am borrowing from other contexts

1. “Whose mind am I going to change about what?” (Gary King)

2. We are making “a commitment to precision.” (Arthur Lupia)

3. “Let go of perfectionism.” (Alice Zhao)