Michele Pasin / Quotes

Correlation and causation

Scientists are trained to recognize that correlation is not causation, that no conclusions should be drawn simply on the basis of correlation between X and Y (it could just be a coincidence). Instead, you must understand the underlying mechanisms that connect the two. Once you have a model, you can connect the data sets with confidence. Data without a model is just noise.

The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all.

Saved 9 September 2013 / www.wired.com ↗

#model #theory #noise #data-sets

Nanopublication support is not argumentative support

Nanopublications distill content as a graph of assertions associated with (a) provenance of the article or dataset from whence they came; and (b) a set of…

Micropublications: A Semantic Model For Claims, Evidence, Arguments And Annotations In Biomedical Communications #graph #set #data-sets

Protecting the team from business noise

There is often a lot of noise from within the business, and it's down to the product owner and the ScrumMaster to protect the team from that noise. Changes in…

A Scrum Master Is Not A Project Manager By Another Name #product-owners #owners #business #team #changes #noise

The Logical ½ behind computer glitches

function represented by the sloping line in the grey area very steep. Nevertheless, in practice the line between one and zero is actually rather fuzzy. This…

Beyond Zero and One (Andrew Smart) #computer #noise #bits #brain

Why scientists don't share their data

Open data-sharers are still in the minority in many fields. Although many researchers broadly agree that public access to raw data would accelerate science —…

Data-sharing: Everything On Display : Naturejobs #data-sets #researchers #information #set #contextual-information

Artificial neurons as activation units

The building blocks of neural networks are simplified versions of biological neurons called activation units. These units have a set of input connections and…

Introducing Artificial Intelligence (Henry Brighton and Howard Selina) #connectionism #brain #model

Beyond simple assertions and their provenance

The micropublication approach goes beyond statements and their provenance, proposing a richer model in order to account for a more complete and broadly useful…

Micropublications: A Semantic Model For Claims, Evidence, Arguments And Annotations In Biomedical Communications #assertion #statements #model #view