How to Lie with Statistics

Category: Mathematics
Author: Darrell Huff
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by eperdu   2019-11-17

There’s plenty of data to indicate climate change is real yet look how many people don’t believe it and further, don’t get me started on flat earthers.

If interested, this is an excellent book: How to Lie with Statistics

Edit: I realize it sounds like I’m dismissing the role and the possibilities of it, but that’s not the case. It’s just a tough row to hoe. :)

by franciscofernando   2019-11-17

by Another_juan_please   2019-11-17

How to Lie with Statistics - Darrell Huff

by Siganid   2019-08-24

If that were the case, one could simply show them the science.

In addition, the politicians we are discussing have access to the science already. Your excuse doesn't explain why the cdc would bury the evidence on dgu. It doesn't explain why the study of the assault weapon ban found it was worthless at best, but the writers still refused to say it was bad policy. Studies are done with a bias built in, and a predetermined outcome in an attempt to defeat what the proof already says.

The cherry picking and other "lying with statistics" techniques don't happen on accident.

The public might genuinely be fooled, but bloomberg, feinstein, clinton et al very obviously know that removing guns will kill people.

So what other motive is possible?

by smilingfiend   2019-08-24

by elmexiken   2019-08-24

Actually they do....

Also, you have anecdotal evidence, which is not much evidence at all.

Thirdly, this is a repost.

by destin325   2019-07-21

If every republican read how to lie with statistics -Darrell Huff (1954) Fox viewership would drop. Hell, Democrats or anyone for that matter should read this. It makes trusting a news source a lot harder when you immediately pick out devious tricks to engineer partial truths.

by Zamboniman   2019-07-21

Heh. Funny.

It's sure easy to confirm one's bias when you make stuff up.

Also, maybe even more significantly:

by 1Operator   2019-07-21

> effieokay: "Can anyone explain why the economic stats are so good and so bad at the same time?"

"How to Lie with Statistics"

by Stratoscope   2017-09-25
It's always best to use the maximum possible precision. This way people know they can trust your data.

Round numbers would lead people to believe you were just making things up.


How to Lie with Statistics, Darrell Huff and Irving Geis

by wyc   2017-08-20
How to Lie with Statistics is a classic on this:

by mathattack   2017-08-19
I like the story of the graph a lot more than the graph itself.

The two things I would like to see are:

- Per capita debt per person who attended college. (Or perhaps who graduated college) This would answer an implied question of "What if we're just getting more people going to college?"

- The salary legend should start at 0. This would put the relative movement of salary in a more accurate context.

I don't think fixing these changes the story of "The long term cost of college is going up, while the short term benefits are going down." but when I see tricks out of "How to lie with Statistics"[1] my BS detector goes up.


by billswift   2017-08-19
How to Lie with Statistics ( is a short, enjoyable read. It doesn't tell you how to do statistics, but it gives some warning about common problems.
by 234dd57d2c8db   2017-08-19
Unfortunately, sites like snopes and politifact also succumb to the same type of bias as the right-wing sites. See this article where politifact was handed propaganda material from the Clinton foundation and parroted it without doing any actual checking about AIDS drugs the Clinton foundation was funding:

Everyone has an agenda, follow the money, and trust no one. Whether it's right-wing like Alex Jones or Left-wing like the Tampa Bay Times a.k.a politifact, you need to be suspicious and do your own research if you want the truth.

by noott   2017-08-19

You should read this book. It's short, succinct and shows one problem with evidence - your view of the same data set can be skewed through clever manipulation.

A few examples are in order.

There are many instances in advertising where you want to show the average value of something, say the average weight loss for your new diet pill. "Average 20 pounds lost!"

Well, that's quite a trick. What average? They're likely to choose the mean, rather than median, because it is more sensitive to extreme values and would increase the "average" for the same data set. They'll never tell you which average they used.

There's a second trick in the example. 20 pounds lost? In what time span? Without specifying, which advertisers generally don't, it's not even clear if the pill is more effective than a proper diet.

Another common example of how to skew perception: the choice of axes on graphs. Say the GDP falls from 50,000 to 49,000 per capita for a country. If you choose the axis of the plot to range from 48,500 to 50,500 or so, it'll look like a catastrophic drop. If you choose the axis to range from 0 to 100,000, the drop will look insignificant. If you plot on a logarithmic scale, it might be hard to tell there's even a difference!

There are lots more examples. The problem is that data can be manipulated in tricky ways to reach whatever conclusion you want. Peer review in science is a counter-measure to this, which generally doesn't exist in politics.

by dougmc   2017-08-19

> Not significantly (8% in 2000 vs 7.4% in 2010) but it gives more context than just "there are more in 2010" in my opinion

If you torture the statistics enough, they'll generally confess to whatever you want them to. There's even an entire book on this sort of thing. (To be fair, the book's intent isn't so much to teach you how to do it, but more to teach you how to spot it and make you think about such things when reading other people's work. That said, reading it would probably help you do it better if that was your goal.)

That said, this particular example is a relatively mild one (and may even be accidental rather than intentional) -- there are much, much worse abuses out there.

by Websly   2017-08-19

Not directly political, but a prerequisite:

One of the most important books I've read.