Nice work from the Washington Post

Source: SurgeonGeneral.gov

Source: SurgeonGeneral.gov

It's easy to find misleading articles in the news. Today, we're going to focus on an article that does a nice job of explaining a complex, data-driven issue.

The article - "One of America’s healthiest trends has had a pretty unexpected side effect" — was published in the Washington Post. The basic premise is that, as smoking rates have declined, obesity has been on the rise. 

So, what does author Roberto Ferdman do well? 

  • He uses (and links to) established sources, including the Surgeon General, the Cleveland Clinic and the National Institutes of Health
  • He explains the methodology behind the research - including the fact that researchers had to approximate certain effects
  • Perhaps most importantly, he draws a distinction between correlation and causation. He quotes an obesity expert (Yoni Freedhoff) who said, "Obviously, it's hard to establish any causal relationship here, but I would definitely say it's plausible that the fall in smoking contributed to the rise in obesity."
  • Finally, he offers a takeaway that cautions people against reading too much into the study: "What exactly are we supposed to glean from the suggestion that the fall in smoking might have contributed to the rise in obesity? The answer is not that anyone should look back upon the days when more than half of the population smoked regularly with nostalgia. Rather, according to Baum, it's better to view the study's finding as more of a point of interest, a takeaway that allows us to look at how societal changes move like waves that ripple, touching other shifts, even if only slightly."

Read the full Washington Post article here

"Required reading" says Arkansas Business

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In a column that referenced John Oliver and Tyler Vigen (who we quote in our book), Arkansas Business editor Gwen Moritz argued that EVERYDATA "should be required reading in high school and for every journalist and journalism student in the universe."

Here are a few of our other favorite quotes:

"Using sentences and examples that even I can understand, Johnson and co-author Mike Gluck explain the way averages can be used and misused."

"They write about the problem with self-reported data... [and] warn us to consider whether important data might be missing."

"We can either be smart, skeptical consumers of data or suckers. Take your pick."

You can read  Gwen's full article here.

Where Does Polling Data Come From?

"Hillary Clinton holds a 12-point lead over Bernie Sanders nationally, but in a hypothetical match-up against Donald Trump, Sanders does much better than the current Democratic front-runner."

That was the lead paragraph from an NBC News article about the 2016 presidential election. And yes, that's what the polling data said. 

But - there's almost always a but - did you see where the data comes from? At the bottom of the article, they disclose that the poll was conducted online among adults who say they're registered to vote, and who take surveys on the SurveyMonkey platform.

Do you see the concerns? 

  • The poll was conducted online - which means if you don't go online, you wouldn't have been part of the sample set
  • It relied on self-reported data - that is, adults who claimed that they're registered to vote
  • The only people surveyed were those who use SurveyMonkey's platform

To their credit, according to the full methodology, data was "weighted for age, race, sex, education, region, and voter registration status" using Census Bureau and other data "to reflect the demographic composition of the United States." But that doesn't erase the fact that, as they state, "the sample is based on those who initially self-selected for participation," which in this case means "no estimates of sampling error can be calculated."

Are people who take online surveys - often for a chance to win a prize - representative of the general population? Even if they're weighted after the fact, we'd want to take a closer look at the data. Maybe it's perfectly valid. But, as I explain in my book, these are exactly the types of questions you should be asking - as an educated consumer of data - when you look at polls in the news.

Was Jonas Really a $3 Billion Dollar Blizzard?

As the East Coast digs out from the Blizzard of 2016, a recent report from Moody's Analytics estimates the cost of the Blizzard to be between $2.5 and $3 billion dollars. When there are major weather events of this nature, we often see these types of estimates calculated and widely reported in the media.

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Tablet vs Paperback?

In our forthcoming book, Everydata, we very briefly address an interesting study from the University of Oregon that finds "People actually recall more information when they read a printed newspaper versus reading it online." Our purpose in raising the study was not to closely examine the underlying statistical methodology (though we might have something to say about the sample of 45 people) but to introduce the concept that how you receive your data can also effect how you interpret or retain it.

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The Shaky Statistics on the Myth of the Holiday Weight Gain

Every year, we see a glut of stories in the media debunking the myth of the holiday weight gain.  The general narrative is one of disbelief that the average holiday weight gain is 5 to 10 pounds (see for example, this SF Gate story) and that the majority of weight gained by the average person in a year is gained during the period between Thanksgiving and Christmas.

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Trust Issues

In an interesting article from Business Insider, the results of a poll from Pew Research describing the most and least trusted news organizations in America are displayed.   According to this survey, the most trusted outlets are actually British- the BBC and the Economist.   At the bottom of the list are BuzzFeed and the Rush Limbaugh Show.

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