In the class I teach on data reasoning, @callin_bull, we stress that if something seems too bad to be true, it probably is. 8% infected in 10 days is clearly too bad to be true even for a control group, let alone a treatment group.
Thanks to @AriDerrow for unpacking the error. https://t.co/vod77R3jsL
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Sadly, Twitter still does not have an option to report a post for making false claims that are likely to increase vaccine hesitancy. Not that
@bopinion should be suspended. Hanlon’s razor applies here— this is clearly incompetence rather than malice.Show this thread -
Goodness. I thought this was just a stupid tweet. No. It’s actually in the Zev Chafets article! This needs to be corrected immediately, Bloomberg
@business.pic.twitter.com/OlFHOhE8IY
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@business@bopinion has screwed up the correction. If 0.02% are diagnosed with COVID, that means 99.98% — not 92% — are COVID-free. If you can't get percentages right with two tries and help from the internet, it's time to find a new line of work. https://twitter.com/bopinion/status/1357834159310438401 …This Tweet is unavailable.Show this thread -
Third time is the charm. Thank you Bloomberg
@business@bopinion.https://twitter.com/bopinion/status/1357884202725818371 …Show this thread
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Wow, huge and concerning error. Ick.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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I'm a little surprised the daily case counts in Israel haven't dropped more now that 37% of the country has had at least one dose.pic.twitter.com/6kNaMoMwDo
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Israel has segments of society that live almost completely separately. I.e ultra orthodox, who are particuarly vaccine hesitant and resist lockdown rules.
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My pet peeve is how energy reporters can’t seem to understand the difference between power and energy: “New solar farm will produce 250 megawatts per year”.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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Is it really media innumeracy or a lack of training on the dangers of confusing absolute and relative risk, a methodology often used in persuasion to inflate the perception of effectiveness of interventions?
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In this case using relative vs absolute risk makes the intervention seem *less* effective, i.e. it causes them to say that it is 92% effective vs >99% effective.
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