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Wednesday, March 21, 2012. Bayesian Causal Analysis of Service Quality. And an exposure to. Generally, a causal model. Is an abstract model that uses cause and effect logic to describe the behavior of a system. A causal model is a specific type of model focusing on causal factors. The logic can be as simple as a Boolean, "if-then" model or as complicated as Bayesian. P (A B) = P (B A) P (A)/ P (B). This rule is at the very heart of Bayesian analysis. It allows information updating in response to new ...

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Working Analytics | scottradcliffe.com Reviews
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Wednesday, March 21, 2012. Bayesian Causal Analysis of Service Quality. And an exposure to. Generally, a causal model. Is an abstract model that uses cause and effect logic to describe the behavior of a system. A causal model is a specific type of model focusing on causal factors. The logic can be as simple as a Boolean, if-then model or as complicated as Bayesian. P (A B) = P (B A) P (A)/ P (B). This rule is at the very heart of Bayesian analysis. It allows information updating in response to new ...
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Working Analytics | scottradcliffe.com Reviews

https://scottradcliffe.com

Wednesday, March 21, 2012. Bayesian Causal Analysis of Service Quality. And an exposure to. Generally, a causal model. Is an abstract model that uses cause and effect logic to describe the behavior of a system. A causal model is a specific type of model focusing on causal factors. The logic can be as simple as a Boolean, "if-then" model or as complicated as Bayesian. P (A B) = P (B A) P (A)/ P (B). This rule is at the very heart of Bayesian analysis. It allows information updating in response to new ...

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Working Analytics: March 2012

http://www.scottradcliffe.com/2012_03_01_archive.html

Wednesday, March 21, 2012. Bayesian Causal Analysis of Service Quality. And an exposure to. Generally, a causal model. Is an abstract model that uses cause and effect logic to describe the behavior of a system. A causal model is a specific type of model focusing on causal factors. The logic can be as simple as a Boolean, "if-then" model or as complicated as Bayesian. P (A B) = P (B A) P (A)/ P (B). This rule is at the very heart of Bayesian analysis. It allows information updating in response to new ...

2

Working Analytics

http://www.scottradcliffe.com/2012/03/labyrinths-of-information-inspirations.html

Tuesday, March 6, 2012. The Labyrinths of Information – inspirations from the work of the late Claudio Ciborra. 1951 – 2005) was a professor of Information Systems and PWC Chair in Risk Management in the London School of Economics. And a leading researcher in the areas of information systems, management, and strategy. Ciborra was an original thinker in his field: the Social Study of Information Systems. Posted by Scott Radcliffe. Subscribe to: Post Comments (Atom). View my complete profile. Is used to de...

3

Working Analytics: Big Data: After the Hype, Then What?

http://www.scottradcliffe.com/2012/03/big-data-after-hype-then-what.html

Tuesday, March 20, 2012. Big Data: After the Hype, Then What? It was quite refreshing to read the recent piece on Seeking Alpha. Entitled " Beware the Hype Over Big Data Analytics. The author hit the nail on the head. With the conclusion that. In fact, the labor and technology barriers to enter. Have never been lower, and continue to drop rapidly. So once we get past the big data hype, how can we create competitive advantage out of the promise of big data? Enabled by distributed (web) services. From this...

4

Working Analytics: Oceans of Information - Making Sense with Ontological Mapping

http://www.scottradcliffe.com/2012/03/oceans-of-information-making-sense-with.html

Monday, March 12, 2012. Oceans of Information - Making Sense with Ontological Mapping. I was pleased to see this provocative post. From my friend and associate Bill Franks of Teradata. In it he points out the fact that virtually no analytical processing directly analyzes unstructured data. Simply put, this is due to the fact it is simply not possible to "discover" topics, sentiments, patterns or trends in text documents without the process of defining concepts, and determining correspondences between them.

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Working Analytics: Bayesian Causal Analysis of Service Quality

http://www.scottradcliffe.com/2012/03/bayesian-causal-analysis-of-service.html

Wednesday, March 21, 2012. Bayesian Causal Analysis of Service Quality. And an exposure to. Generally, a causal model. Is an abstract model that uses cause and effect logic to describe the behavior of a system. A causal model is a specific type of model focusing on causal factors. The logic can be as simple as a Boolean, "if-then" model or as complicated as Bayesian. P (A B) = P (B A) P (A)/ P (B). This rule is at the very heart of Bayesian analysis. It allows information updating in response to new ...

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Wednesday, March 21, 2012. Bayesian Causal Analysis of Service Quality. And an exposure to. Generally, a causal model. Is an abstract model that uses cause and effect logic to describe the behavior of a system. A causal model is a specific type of model focusing on causal factors. The logic can be as simple as a Boolean, "if-then" model or as complicated as Bayesian. P (A B) = P (B A) P (A)/ P (B). This rule is at the very heart of Bayesian analysis. It allows information updating in response to new ...

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