Danilo Freire

Master of Arts in Political Science at the University of São Paulo. [More info]

[daniloamfreire]

Best World Cup-related video ever.

[daniloamfreire]

Um hangout muito interessante sobre economia do crime

[daniloamfreire]

Death is a natural part of life. And that's it.

[atlasofprejudice]

20 ways to slice the European continent from Atlas of Prejudice 2 by Yanko Tsvetkov.

[daniloamfreire]

Great video on how p-values are unreliable measures.

[daniloamfreire]

via Flowing Data:

Statistical concepts explained through dance

MARCH 7, 2014  |  STATISTICS

Forget bell curves, jellybeans, and coin flips to explain statistical concepts. Dancing Statisticsis a video series that demonstrates variance, correlation, and sampling through coreographed movements. The dance below explains variance.

[daniloamfreire]

Wonderful, truly wonderful.

[daniloamfreire]

Build interactive math equations and diagrams online using LaTeX and PSTricks

[thedeathdefyingunicorn]

[daniloamfreire]

I love this record :-)

[daniloamfreire]

rMaps is an R package for creating interactive maps. It builds off rCharts, but is focused exclusively on mapping libraries. The map shown in this video makes use of the crosslet library that integrates leaflet and crossfilter.

[daniloamfreire]

Games - a new package for estimating strategic interactions in R.

[daniloamfreire]

Mia principessa, why don't you say you love me and save me from this darkness?

[daniloamfreire]

Forecasting By Combining Expert Opinion

Michael is member of Revolution Analytics Sales Support team. In the following post, he shows how to synthesize a probability distribution from the opinion of multiple experts.

An excellent way to construct a Bayesian prior.

[daniloamfreire]

The Bryan Ferry Orchestra - Love Is Τhe Drug 

[daniloamfreire]

[googlepoet]

www.googlepoetics.com

[dartthrowingchimp]

Wowzers, this new tool looks like it could be super-useful for people (like me) studying and forecasting rare political events. H/t to Daniel Bilar.

BayesDB, a Bayesian database table, lets users query the probable implications of their tabular data as easily as an SQL database lets them query the data itself. Using the built-in Bayesian Query Language (BQL), users with no statistics training can solve basic data science problems, such as detecting predictive relationships between variables, inferring missing values, simulating probable observations, and identifying statistically similar database entries.

BayesDB is suitable for analyzing complex, heterogeneous data tables with up to tens of thousands of rows and hundreds of variables. No preprocessing or parameter adjustment is required, though experts can override BayesDB’s default assumptions when appropriate.

BayesDB assumes that each row of your table is a sample from some fixed population or generative process, and estimates the joint distribution over the columns. BQL then allows you to draw Bayesian inferences about individuals and about the overall population or process.