NOV 30, 2010 10:15am ET

Related Links

Microsoft CEO Nadella Unveils Data-Analysis Tools for Companies
April 17, 2014
Gartner: CEOs Focus on Tech-Related Business Growth in 2014
April 17, 2014
Analytics: Needing to Know or Wanting to Know?
April 9, 2014

Web Seminars

April 29: Create a data protection strategy with open, software-defined storage
April 29, 2014
New Best Practices To Manage Customer Information
May 7, 2014
May 13: Cost-effective, scale-out backup in 1 solution
May 13, 2014

Bayes and Risk Management – Part 1


A few years ago, after undergoing a routine physical, a friend of mine received some bad news. A test given to men his age came back positive, an indication of a pretty serious medical condition.  Worse, 99 percent of those with the disease test positive, while only 5 percent who don't have the condition get the bad news.  

Get access to this article and thousands more...

All Information Management articles are archived after 7 days. REGISTER NOW for unlimited access to all recently archived articles, as well as thousands of searchable stories. Registered Members also gain access to:

  • Full access to including all searchable archived content
  • Exclusive E-Newsletters delivering the latest headlines to your inbox
  • Access to White Papers, Web Seminars, and Blog Discussions
  • Discounts to upcoming conferences & events
  • Uninterrupted access to all sponsored content, and MORE!

Already Registered?


Comments (2)
Thanks Mr Miller, This was a nice overview of Bayesian fundamentals. Do you have any recommendations for books like "Bayesian Statistics for Dummies" or "Using Bayesian Probabilities in Business Risk Management"? Your substitution for P(D) was not entirely clear. It would seem that if 5% of folks who did not have the condition got a positive result, then the probability of not having the condition given a positive result would also be 5%. Thanks Shane
Posted by Shane P | Wednesday, December 01 2010 at 4:18PM ET
I was lucky enough to be lectured by a bayesian when I took my degree, but this is much clearer - thanks! What I like about the bayesian approach is the way it provides a framework for transparently and consistently updating estimated probabilities as new information becomes available, allowing forecasting systems to "learn". I've also used a bayesian belief network to combine subjective judgements about weak risk factors to identify the most likely cases to cause problems. I look forward to hearing more about business applications.
Posted by Colin E | Wednesday, December 01 2010 at 5:52PM ET
Add Your Comments:
You must be registered to post a comment.
Not Registered?
You must be registered to post a comment. Click here to register.
Already registered? Log in here
Please note you must now log in with your email address and password.

Are you actively evaluating master data management technologies and their ability to scale and support emerging trends around big data, social and mobile?

Yes 61%
No 23%
Don't Know 9%
Not Applicable 6%


Login  |  My Account  |  White Papers  |  Web Seminars  |  Events |  Newsletters |  eBooks
Please note you must now log in with your email address and password.