Análisis y comunicación de datos cuantitativos

Esta es una de las preguntas más habituales de mis estudiantes -de métodos cuantitativos- cuando he alcanzado con ellos la confianza suficiente. Y lo peor de todo es que no les falta razón a juzgar por la opinión vertida en este post escrito a modo de reflexión ante la reciente publicación del libro de Ian Ayres de título Super Crunchers.

Me ha parecido especialmente interesante el siguiente comentario:

The nature of the analysis is such that neither side can convince the other that “their” analysis is reliable. That’s not always true. As I suggest in the podcast, Milton Friedman was able to convince the skeptics that inflation is everywhere and always a monetary phenomenon. Friedman won the debate. But how many other studies can you think of where someone staked out a controversial position and convinced the skeptics based on empirical analysis? I think it can be done, but it’s rare. And in today’s world, most of the interesting empirical claims are being made in cases where the data are too incomplete and the issue is so complex that we can’t move to a consensus. The empirical work doesn’t improve our understanding of what’s going on. It masks what’s going on. It gives a patina of science when in effect the numbers aren’t really informing the debate.