Name: 數據和資訊圖表。數字信息速成班 #8 (Data & Infographics: Crash Course Navigating Digital Information #8)
Uploaded: 2021-01-14T10:29:19.000Z
Duration: 13 min 2 s
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This is Crash Course: Navigating Digital Information.

第二類條件句型

So what would you say if I told you that 90% of people polled say that they love Crash

Course and think we offer consistently reliable and accurate information on the most important

And you'd be kind of right, but I would also be kind of right, because I did do that

survey, and 90% of people did agree with those positive statements about Crash Course--but

I surveyed 10 people who work on Crash Course.

It would've been 100%, but Stan said, “Is this for a bit?

Anyway, whether it's 4 out of 5 dentists or 9 out of 10 crash course viewers, source

We like to think of data as just being cold, hard facts, but as we've already learned

in this series, there is no single magical way to get at the singular truth.

We have to place everything in its context--even statistics.

Okay, so data is raw quantitative or qualitative information, like facts and figures, survey

Data can be derived from observation, experimentation, investigation or all three.

It provides detailed and descriptive information about the world around us.

The number of teens who use Snapchat, the rate at which millennials move in or out of

a neighborhood, the average temperature of your living room -- those are all data points.

And data is a really powerful form of evidence because it can be absorbed quickly and easily.

Like we often consume it as numbers, like statistics, or as visual representations,

But as Mark Twain once famously noted: “There are three kinds of lies.

Statistics can be extraordinarily helpful for understanding the world around us, but

because statistics can seem neutral and irrefutable, they can be used to profoundly deceive us

The truth is neither data nor interpretations of it, are neutral.

Humans gather, interpret, and present data and we are flawed, complex, and decidedly

Unfortunately, we often take data at face value.

Just like with photos and videos, we can get stuck in the “seeing is believing” trap

because we don't all have the know-how to critically evaluate statistics and charts.

Like a Stanford History Education Group study from 2015 bears this out.

SHEG, developed the MediaWise curriculum that this series is based on.

And they asked 201 middle schoolers to look at this comment on a news article.

As you can see, the comment includes healthcare statistics, but doesn't say where they came

It doesn't provide any biographical information on the commenter either.

But, 40% of the students indicated they'd use that data in a research paper.

In fact many cited the statistics as the reason they found the comment credible and useful.

The sheer existence of quote unquote data enhanced its credibility despite there being

Whenever we come across data in the wild, we should ask ourselves two questions:

Does this data actually support the claim being made?

Here's an example when it comes to data relevance.

At the 2018 U.S. Open, Serena Williams was penalized for yelling at the umpire and smashing

On the court, she argued that men yell far worse things at umpires and physically express

their emotions all the time without being penalized and a few weeks later, journalist

Glenn Greenwald cited a New York Times story in a tweet:

“Now, NYT just released a study of the actual data: contrary to that narrative, male tennis

players are punished at far greater rates for misbehavior, especially the ones relevant

to that controversy: verbal abuse, obscenity, and unsportsmanlike conduct”

And also he linked to a table that showed that far more men have been fined for racket

throwing and verbal abuse than women during grand slam tournaments.

However, as statistician Nate Silver helpfully pointed out, this stat only shows that men

are /punished/ more, which could be because they misbehave more.

So all these statistics actually show is the raw number of punishments, not the rate of

To get the rate of punishment we'd have to divide the number of punishments by how

many times men and women misbehave, and that data isn't provided here.

So the data in the end does not support Greenwald's tweet at all, making his claim that male tennis

players are punished more frequently… problematic at best.

To be fair Serena Williams claim is also anecdotal, although, you know she does watch a lot of

We also need to investigate whether the source providing the data is reliable, and we can

That means opening new tabs to learn more from other sources about:

who commissioned the research behind data , who conducted the research, and why

We also need to know if the source of the the information is authoritative, or in a

good position to gather that data in the first place.

Like remember in episode 3 of this series when we talked about the claim that Americans

We couldn't confirm how many straws Americans actually use every day, but we did see that

sources across the web cited that statistic even though we found out that it came from

a 2011 report written by a then-nine year old child, Milo Cress.

To come up with the figure, he called up straw manufacturers to ask how many straws they

There's no way of knowing if those manufacturers were telling the truth, or if the group he

called is representative of the whole industry.

He was obviously a very bright and industrious 9 year old, but he was 9!

Thank you for being careful in how you navigate digital information friends.

A more reliable source of such far-reaching information might be a nonpartisan research

organization like the Pew Research Center.

They're known for reliable, large-scale studies on U.S. trends and demographics.

Once we know who a source of data is, whether they're authoritative, and why they gathered

it, we should ask ourselves what perspective that source may have.

They could have a vested interest in the results.

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數據和資訊圖表。數字信息速成班 #8 (Data & Infographics: Crash Course Navigating Digital Information #8)

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