Not only is it not right, it’s not even wrong!
Wolfgang Pauli (http://en.wikipedia.org/wiki/Wolfgang_Pauli#Personality_and_reputation)
Categories
Category: Uncategorized
The whole experience makes me want to pull aside politicians and business leaders and maybe everyone else and offer some pious advice: Don’t try to be everyman. Don’t pretend you’re a member of every community you visit. Don’t try to be citizens of some artificial globalized community. Go deeper into your own tradition. Call more upon the geography of your own past. Be distinct and credible. People will come.
David Brooks (http://nyti.ms/NudBX9)
Darwin and Turing had both discovered, in their different ways, the existence of competence without comprehension.
http://www.theatlantic.com/technology/archive/2012/06/a-perfect-and-beautiful-machine-what-darwins-theory-of-evolution-reveals-about-artificial-intelligence/258829/
The simplistic interpretation of this theorem which many people jump to is “machine learning is dead” since there can be no single learning algorithm which can solve all learning problems. This is the wrong way to think about it. In the real world, we do not care about the expectation over all possible sequences, but perhaps instead about some (weighted) expectation over the set of problems we actually encounter. It is entirely possible that we can form a prediction algorithm with good performance over this set of problems.
John Langford (http://hunch.net/?p=111)
Causation vs Association…
When to manage and when to coach
http://www.forbes.com/sites/work-in-progress/2012/05/01/know-when-to-manage-and-when-to-coach/
Statistical significance
http://learnandteachstatistics.wordpress.com/2012/05/22/significance/
Making a singular matrix non-singular
Recall first that in statistics, we distinguish between descriptive statistics and statistical inference. Descriptive statistics, as the name suggests, is that part of statistics concerned with defining and studying descriptors of data. It involves no probability theory and aims simply to offer tools for describing, summarizing, and visualizing data. Statistical inference, on the other hand, concerns the more sophisticated enterprise of estimating descriptors of an unknown probability distribution from random samples of the distribution. The theory and methods of statistical inference are built on the tools of descriptive statistics: The estimators considered in statistical inference are of course, when stripped of their inferential interpretation, merely descriptors of data
Michael Phillip Lesnick (from http://bit.ly/K0E8dt)
List of good statistics books
http://stats.stackexchange.com/a/7477/7603