Four short links: 26 September 2017

Metric Pitfalls, Big Data, Data Analysis, and Startup Advice

By Nat Torkington
September 26, 2017
  1. Twelve Common Metric Interpretation Pitfalls (Paper a Day) — from Microsoft experiences. This is solid gold for anyone doing online A/B testing. If you see an unexpected metric movement, positive or negative, it normally means there is an issue. For example, a too-good-to-be-true jump in number of clicks turned out to be because users were confused and clicking around trying to figure things out!
  2. Using Big Data to Solve Economic and Social ProblemsThis introductory course, taught by Raj Chetty, shows how “big data” can be used to understand and solve some of the most important social and economic problems of our time. The course gives students an introduction to frontier research in applied economics and social science that does not require prior coursework in Economics or Statistics. Topics include equality of opportunity, education, health, the environment, and criminal justice. In the context of these topics, the course provides an introduction to basic statistical methods and data analysis techniques, including regression analysis, causal inference, quasi-experimental methods, and machine learning.
  3. Learn faster. Dig deeper. See farther.

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  4. Apache Arrow — columnar in-memory data analysis; think R or Pandas, but as a C++ library with bindings to other languages.
  5. YC’s Essential Startup AdviceYour job as a founder will often seem to be continuously righting a capsized ship. This is normal.
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