How One Unverified Claim Of A $7,500 'Loss' From Cybercrime Translates To $1.5 Billion In Losses In The Press
from the lies,-damned-lies dept
I think we should just admit that there's a "cyber-" inflation factor. That is, for anything in which someone puts a prefix of "cyber-" before a word, we can assume that reports of the "impact" are going to be massively inflated. Cyberwar? Totally overhyped. Cyberbullying? Not nearly as crazy as you hear. And now we've got a new report saying that reports of "losses" from "cybercrime" appears to be greatly overestimated as well.First, losses are extremely concentrated, so that representative sampling of the population does not give representative sampling of the losses. Second, losses are based on unverified self-reported numbers. Not only is it possible for a single outlier to distort the result, we find evidence that most surveys are dominated by a minority of responses in the upper tail (i.e., a majority of the estimate is coming from as few as one or two responses). Finally, the fact that losses are confined to a small segment of the population magnifies the difficulties of refusal rate and small sample sizes. Far from being broadly-based estimates of losses across the population, the cyber-crime estimates that we have appear to be largely the answers of a handful of people extrapolated to the whole population. A single individual who claims $50,000 losses, in an N = 1000 person survey, is all it takes to generate a $10 billion loss over the population. One unverified claim of $7,500 in phishing losses translates into $1.5 billionAnd yet, of course, such claims of massive losses will still be regularly repeated in the press and by politicians. I've always said that it would be great if we could force feed politicians and journalists economics lessons, but I'd like to propose adding statistics to the required curriculum as well.
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Filed Under: cybercrime, statistics
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Stats?
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Re: Stats?
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That's why I never believe whatever claims unless I see how it was sampled, what statistic methods were applied, how much of an err was admitted (confidence interval and the likes) and so on. Unfortunately, I'm the minority that has at least a tiny bit of knowledge about statistics. (No statistics used here but empirically almost no1 around me has any clue how to deal with statistic data or judge if a statistic study has been conducted in a proper manner).
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1: The members of these groups would be better positioned to do their respective jobs.
2: The number of people in each group would be drastically reduced.
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This is why anyone running for an elected office...
(Yes, I'm well aware that this is not a panacea, but wouldn't it be nice to actually have a senator who could multiply? Or a DA who knew what the bell curve is? And how refreshing would it be to have ANY elected official who understood the proper way to extrapolate an exponential?
"The greatest shortcoming of the human race is man's inability to understand the exponential function."--- Albert A. Bartlett
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Neither economics nor statistics are hard sciences.
Therefore, your "forced feeding" seems similar to commie "re-education": you just intend to stifle other /views/ not /facts/.
By the way, Marx was an economist.
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Re: Neither economics nor statistics are hard sciences.
Talk about making stuff up. Statistics is a field of mathematics. I suppose you've never studied it? Of course, I can see how when someone doesn't like how the numbers add up they might in response just want to just declare mathematics to be unscientific. What a load.
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A couple of friendly tips -
1. Reply to the dumbest people, but don't worry about the ones with good points. If their whole point boils down to 'I know you are but what am I?' then thrash them handily without touching the guys that have well reasoned arguments.
2. Use the word FREETARD. People get all up in arms when you use that word. No matter what your point is, using that word is guaranteed to elicit a few nerd rage responses.
Happy trolling!
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This isn't a statistics issue
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