most recent 30 from http://www.or-exchange.com 2010-07-31T00:37:33Z http://www.or-exchange.com/feeds/tag/analytics http://www.creativecommons.org/licenses/by-nc/2.5/rdf http://www.or-exchange.com/questions/131/how-to-determine-useful-signals-for-prediction-models Mark 2010-01-06T08:14:46Z 2010-06-16T17:17:25Z

<p>With regards to <a href="http://mat.tepper.cmu.edu/blog/?p=1024" rel="nofollow">this blog post</a>. I have collected a number of datasets for different contributing variables to homicide incidents. I would like to know which of these variables is significantly contributing to the number of homicide in the area. I was planning to use our archaic friend, ANOVA, to see if there is any significant effect from each of these variables and then include the dominating ones in my model.</p> <p>I just want to know if there is any better (or perhaps more modern) tool to find good signals. perhaps Bayesian Inference? :)</p>

http://www.or-exchange.com/questions/138/how-do-you-deal-emotionally-with-macabre-data-sources Isaac Moses 2010-01-18T14:48:30Z 2010-03-02T18:15:24Z

<p>I've been working on the <a href="http://analyticsx.com/" rel="nofollow">Analytics X Prize</a>, which deals with predicting homicide rates. I find that I naturally look forward to new datapoints that to validate my model. Unfortunately, these anticipated "new datapoints" are new criminal homicides.</p> <p>When you're working with datasets that record human tragedies, how do you deal emotionally with the fact that more data would make your job easier, validate your work, etc., but that more data also means more tragedy?</p> <p>I imagine this would apply similarly to people who study disaster response. When something like the Haiti earthquake hits, the human in them must be horrified, but doesn't the researcher in them also naturally look forward to the research opportunities this sort of event creates?</p> <p>How do you keep your analysis work from making you callous?</p>