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Longest Running Thread EVER


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Re: Longest Running Thread EVER

 

. . . Why is it that the US gets all the fun politics? Share' date=' damn you![/quote']

 

Actually, wasn't Belgian politics riotously funny about a decade back? To the point that "Belgium" was a one-word joke post on some chats and BBSs?

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Re: Longest Running Thread EVER

 

I encountered a relatively new father the other day who has taken to describing diaper-changing episodes as DEFCON ratings. He has the sign wrong (in his scale a pee-only diaper is a 1) but in terms of contractions it's plausible.

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Re: Longest Running Thread EVER

 

Obviously some new threat has appeared in the cyberworld, because Java and Firefox and every other damned piece of software an this pathetic box is grabbing for the update connection and insisting it must download a patch ***NOW***, which triggers the antivirus to grab what little available memory it has not already arrogated to itself, and bring the box to utter catatonia. Not even the 3-finger salute gets a prompt response, and I'm this close to grabbing the 60VAC to remind it who is the boss here.

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Re: Longest Running Thread EVER

 

By waiting five minutes for the antivirus to back off, rebooting the box (another five-minute process), and firing up the newly-patched browser. Other unknown anomalies were going on as well, which is why I ultimately did the power-cycle. I'd never had Vim crash before.

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Re: Longest Running Thread EVER

 

Mortality is usually defined in terms of a hypothetical cohort of 100,000 people of mixed age, sex, race, etc. That's fine, but when you're modeling a population that starts at age 50, some portion of that cohort has already died, so you're constructing a population of people who are still alive at that age, and the age structure of the population depends in a complicated way on the data. And exactly how to construct a model population of a particular size isn't immediately obvious when you're interested in the operation of a particular cause of mortality. Disease incidence is specified in the same way, but it gets messier still because the model population you're trying to construct has to exclude people who already have been diagnosed with the disease, whether they've died or not. So by definition you are constructing something that is different from the standard population for which you have statistics, and statistical tests to compare your model population with the real population must fail at some level because of that.

 

Some of the goofy numbers the model has been kicking out I think are caused by some of these subtle issues, and that most statistical products are not really defined in a way that's helpful to someone doing this kind of numerical model. That's not surprising ... the statistical products were defined long before this type of modeling was possible ... but it is annoying, especially when you've got no formal training in statistics and you suffer from the "that word ... I do not think it means what you think it means" syndrome.

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