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Starts Today: BayesiaLab Course in Houston

Our first BayesiaLab course of 2015 started this morning in Houston, Texas. It looks like we'll have three fun days ahead of us. Only 30 minutes into the course, we have a lively debate about Frequentist vs. Bayesian Statistics.


The BayesiaLab Digest - January 6, 2015

There is a large body of literature about applied research with Bayesian networks. With this digest, we intend to highlight a selection of recent articles in this domain on a regular basis.

Vlek, Charlotte S., Henry Prakken, Silja Renooij, and Bart Verheij

Extracting Scenarios from a Bayesian Network as Explanations for Legal Evidence 


Happy Holidays from Bayesia USA!


BayesiaLab Course in Paris

Our last BayesiaLab course of the year concluded yesterday in Paris. These eight researchers can now call themselves "BayesiaLab-Certified," which has become a highly sought-after credential among applied scientists. We hope to seem them all again in 2015 for our BayesiaLab Conference in Washington, D.C.

Our training program will continue in the new year with a 3-Day Introductory BayesiaLab Course in Houston, TX, January 14-16.


"Data-Driven Decisions" - Good Alliteration, Bad Motto.

Whoever cites "data-driven decisions" probably has good intentions but implicitly commits a fallacy of omission! The problem is that the motto, "data-driven decisions", fails to state what is really required to make data useful for decision making.



Get your calendars ready...

Tomorrow we'll announce the dates of 38 BayesiaLab events across Europe, North America, Asia, and Australia in 2015. Stay tuned!


Confusing Statistical and Causal Concepts - A 21st-Century Fallacy

It was exciting to see the launch of the beta version of IBM's Watson Analytics. The interface is highly intuitive, and the visualization of the results is brilliant.

However, I must point out a fundamental flaw in the modeling approach presented in Watson Analytics. Throughout the entire site and all its video tutorials, there is a consistent conflation of statistical and causal concepts. For example, prediction, explanation, association, and impact are all presented indistinguishably. There are countless instances in Watson where measures of association are falsely labeled with causal descriptions.


A Successful BayesiaLab Course in Washington, D.C.

Many thanks to our course participants in Washington, D.C., who persevered last week through three intense days of instruction on Bayesian networks and BayesiaLab.


BayesiaLab Course Starts Today in Washington, D.C.

Our last BayesiaLab course of the year started this morning in Washington, D.C. Researchers from industry, government, and academia have joined this program to learn all about Bayesian networks and BayesiaLab. Once again, Dr. Lionel Jouffe flew in from France to teach this highly popular seminar.

The next BayesiaLab course in the U.S. is scheduled for January 14-16, 2015, in Houston, Texas.


BayesiaLab Course in Paris, October 2014

No rest for the weary! After last month's mega training program in Los Angeles, we are back to our regular course schedule. This week, a group of researchers from France and Switzerland completed the 3-day introductory BayesiaLab course in Paris. Coming up in November: BayesiaLab Course in Washington, D.C.