2016: A Year of Data-Driven Confusion

Curated by: Small Business Management

Quantified data, statistics and data visualisations often catch our attention more than just words. That much is not new. But this year, the impact of misleading data claims and campaigns led to unexpected consequences in some of the world’s largest economies. In fact, political campaigns over the past 18 months have been characterised by “relentless statistical crossfire”, despite these “statistics” being biased and incomplete, or even completely falsified, with seemingly few consequences.

For example, this year in the United States, pre-election polling data had Clinton winning, right up until the votes started rolling in. Though it turns out that she did win the popular vote, polling data on a state level differed from the actual election outcome. What are the implications if this inaccurate, misleading or uncertain poll data in fact impacted voter behavior?


While it will take months to review in detail why the polls differed from reality, some high-level reasoning can be offered already. For one, there are many potential methodology issues that might lead to inaccuracy in election polling, but as Mona Chalabi, US Data Editor at the Guardian, wrote the day after the election, readers probably didn’t want to hear ‘it’s

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