Scientists use big data to understand what separates winners from losers
scientificamerican.com
Scientists use big data to understand what separates winners from losers
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Re: Scientists use big data to understand what separates winners from losers
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#5Re: Scientists use big data to understand what separates winners from losers
#6Regarding counter-terrorism, that would suggest that rather than more surveillance we instead need better reporting of and responding to failed terrorist incidents/attacks.
Re: Scientists use big data to understand what separates winners from losers
#7This is confounded by the fact that the closer one is to success the more frequent their attempts tend to be. The article doesn't indicate the research took this into consideration.
e.g. Golfers takes shots more frequently the closer they are to a hole. But telling a golfer from the start to take a series of frequent short shots is bad advice.
Re: Scientists use big data to understand what separates winners from losers
#8So did the scientists succeed or fail ? I couldn't really tell from the article and the paper, albeit I just skimmed it.
I guess we can only wait for the title "Here is 10 reasons why you are a loser, Harry..."..
Re: Scientists use big data to understand what separates winners from losers
#9Re: Scientists use big data to understand what separates winners from losers
#10>the faster you fail, the better your chances of success, and the more time between attempts, the more likely you are to fail again This is confounded by the fact that the closer one is to success the more frequent their attempts tend to be. The article doesn't indicate the research took this into consideration. e.g. Golfers takes shots more frequently the closer they are to a hole. But telling a golfer from the star…
But yes, it is not defined what they took into account. e.g. Calling the same potential client hundred times in a row, can get you a restraining order only.
If qualitative input and output of an attempt would be taken in account, quantity of an attempt would not really be that significant.