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Wildly inaccurate election forecasts highlight Big Data challenges

  • Nov 17, 2016
  • 1 min read

For several weeks I was receiving daily messages on my phone from the New York Times’ Upshot column, which confidently predicted Trumps chances of winning at around 5 per cent most days.

The Upshot data was crunched from many different polls and fed into a special algorithm based on historical and other relevant data. Other organizations also used reams of Big Data to feed their analytical models and were coming to similar predictions: Trump would lose. [1]

[1] By Tom Foremski for ZDNet


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