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Statistics, when used in a misleading fashion, can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator.
The President's Falsehoods, Misleading Claims and Flat-Out Lies. [141] [142] By October 9, 2019, The Washington Post ' s fact-checking team documented that Trump had "made 13,435 false or misleading claims over 993 days". [143] On October 18, 2019, the Washington Post Fact Checker newsletter described the situation: A thousand days of Trump.
Strategies that may be more effective for lasting correction of false beliefs include focusing on intermediaries (such as convincing activists or politicians who are credible to the people who hold false beliefs, or promoting intermediaries who have the same identities or worldviews as the intended audience), minimizing the association of ...
The new ad features giant on-screen text with the words “global war,” attributing them to a July article by the media outlet Axios, as the ad’s narrator says, “Their weakness invited wars.”
Take one measure of labor market earnings — the pay (including benefits) of the 80% of workers who are not managers or supervisors at work. For decades before 1980, these workers’ hourly pay ...
How to Read Numbers: A Guide to Statistics in the News (and Knowing When to Trust Them) is a 2021 British book by Tom and David Chivers. It describes misleading uses of statistics in the news, with contemporary examples about the COVID-19 pandemic, healthcare, politics and crime. The book was conceived by the authors, who are cousins, in early ...
Now, with less than a week to go until Election Day, social media users have continued to share misinformation about Trump, from altered images and fake posts to false claims about his court cases ...
Visualization of Simpson's paradox on data resembling real-world variability indicates that risk of misjudgment of true causal relationship can be hard to spot. Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined.