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Lies, Damned Lies, and Statistics

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"Aw, people can come up with statistics to prove anything, Kent. 'Forfty' percent of all people know that!"
Homer Simpson, The Simpsons ("Homer the Vigilante")

This well-known saying is part of a phrase often attributed to Benjamin Disraeli and popularized in the U.S. by Mark Twain:

"There are three kinds of falsehoods: lies, damned lies, and statistics."

Numbers and formulas are supposed to represent "objective scientific data" you cannot deny which have been examined by intelligent and experienced experts. The Consummate Liar wants his forgeries to look undeniably "scientific", so why not use the magic of numbers that the not-so-math-literate masses could never deny? They say that statistics don't lie, and while that may be true, liars do use statistics.

This trope covers all instances of Artistic License – Statistics where someone manipulates statistics to present a misleading picture of the truth. The problem is, people do not pay attention to the context, just the numbers. For example, the statement "Brand X is 84% fat-free" sounds good until you realize that this means the food product is 16% fat by weight. Also, "fastest-growing" could mean that there used to be one customer and then there were five more, making a five-hundred percent increase. You should also notice Absolute Comparatives: it's fastest-growing, but specifically compared to when/what?


The whole business of throwing percentages at people in advertising, politics, and other forms of propaganda is almost destined for this kind of abuse. Relative measures are more likely to be understood accurately, and thus are less likely to be used in advertising.

The bogus uses of statistics are intended to imply a causal link between two elements when they are not linked, the link is questionable, or the link is opposite to what is implied. A beautiful example? "Coca-Cola causes drowning". By looking at statistics on drowning and Coca-Cola sales, you can see a link — more people go swimming on hot days, and more people buy Coke on hot days. Likewise, birth rates per head of population are higher in areas where there are more storks — because birth rates are always higher in rural areas, which is where one finds the Delivery Stork. Correlation does not equal causation; if it does, then we might also conclude that global warming is caused by a decline in pirate population and that 100% of Homo Sapiens who consume dihydrogen monoxide will cease vital functions and decompose.


Be aware of the Law of Very Large Numbers. Any fraction of a very large number is likely to be a large number, no matter how small the fraction is. It is estimated that 2,135,000 Americans have used cocaine (including crack) in the past month. But that's only 0.7% of the population! So, is this a lot of people, or not?

You should also be on the lookout for the related effect where things are made more remarkable than they really are. The odds that any given ticket will win a raffle may be very small, but it is certain that one will be a winner. You'd notice being dealt a royal flush in spades at poker, but the odds of it happening are exactly the same as those for being dealt any other hand of five specified cards.

Then you can get the kind of statistical abuse in which you are careful to define the question to get you the answer you want. What is the most popular book in the world? Depends if you mean most copies in existence (Quotations from Chairman Mao), most copies ever sold (The Bible) or fastest-selling ever (Harry Potter and the Deathly Hallows).

Statistics are like studies: who made them and who paid them matters a lot. Want to "prove" that video games cause violence? Get a group of scientists that are already savvy about this and don't mind the lack of ethics. Have them draw from a very small pool of test subjects that are known to display violent behavior. Mental hospitals, prisons, schools for children with behavior disorders, what have you. Do some generic tests that are guaranteed to show up positive, come up with numbers, and presto, instant headline. "Recent test shows 77% of subjects become more violent after playing Mortal Kombat." Most people won't bother with reading the article the whole way through and will just look at the headline. This works with anything from comic books and rock to watching Brokeback Mountain or voting for specific parties, basically anything. See Push Polling for a specific form of this.

Confirmation Bias, or the tendency for people to search out statistics that support their preconceived notions and ignore statistics that don't, is the reason for many of the entries on this list. The forgery mentioned above is also the reason most scientific and medical studies are done double-blind (meaning it's all anonymous, neither the researchers nor the participants know who's in the experimental group nor who's in the control group) and should allow for a chance at being falsified by Real Life (see also The Scientific Method). But you should beware of any advertisements touting a "double-blind" study, especially late-night ads because they tend to violate the truth-in-advertising laws.

In the end, statistics are not lies and statistics don't lie: people lie about the statistic itself or how it is interpreted. Some don't lie, they are simply ignorant, as are most members of the public in terms of statistical interpretation. See Logical Fallacies and Critical Research Failure.

Put another way, by baseball announcer Vin Scully:

"People use statistics the way a drunk uses a lamp post — for support, not illumination."

See also Nine out of Ten Doctors Agree, which is much a sub trope to this, and Absolute Comparative, where the use of statistics is avoided entirely by comparing the product to nothing.

When adding examples, please remember that this trope is not about amusing statistical fallacies, but about using statistics to misrepresent the truth.


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  • Nine out of Ten Doctors Agree that the phrase "Nine out of Ten Doctors Agree" has been practically a stock phrase in advertising since the early 20th century.
    • "Nine out of ten dentists recommend Trident for their patients who chew gum." The tenth dentist was insistent that his patients never chew gum at all, but surprisingly, Trident didn't want you to know about that. One interesting case happened in Portugal, where two ads were being broadcasted on national TV during the same period (and sometimes even in the same commercial break) claiming, respectively, that '90% of dentists use toothpaste X' and '8 out of 10 dentists recommend toothpaste Y to their family'. Together, if you stop to think about it, they imply something is not quite right about those professionals' concern over their own family...
    • Or that an awful lot of dentists are unmarried orphans, hence can't recommend it to a family they haven't got.
    • In a similar vein, a commercial for Five Hour Energy states that 4 out of 5 doctors wish for their patients who use energy supplements to use low-calorie energy supplements. Think about that: They specify patients who already use energy supplements, meaning they didn't count any doctors who recommend that their patients not use energy supplements at all.
  • A Trojan Condoms commercial claims that the United States ranks between two African nations in HIV cases. This means nothing since the population of the USA is much higher than either of those countries!
  • An old advert for Guinness ran with the quote "88.2% of statistics are made up on the spot", attributed to Vic Reeves. Most (95.639055252364%) of these will have ridiculous precision. (Source unknown)
  • Fletcher Knebel was apparently responsible for "Smoking is the leading cause of statistics", the most famous of which is "100% of non-smokers die".
  • In Montreal, there was an ad campaign run by a gum company whose gum came in round shapes instead of the usual square shapes. The ad said, "100% of people who chew square gum die."
  • Ever wonder how all car insurance companies manage to advertise that "people who switch from <competing company> to <our company> save an average of <a large amount of money or substantial percentage>"? It's because the sample population "people who switch" is almost entirely composed of "people who are going to save a big chunk of money doing so", or else why would they bother to switch? Since no record is kept of the percentage of people who would not save any money and therefore don't switch, the cited statistic has almost no meaning.
  • As the Great Cable TV/Internet/Voice wars began ramping up, they tended to fish from similarly Small Reference Pools for their commercials, typically along the lines of "Of all customers who switched from <company> to <company>, over 53% that switched back did so because they realized they were paying less before." This is said in rapid-fire and/or low-key speech, while the 53% is emblazoned on the screen, making you think that half of the people that switched had come back, instead of that being a sub-statistic OF those that switched back: that figure is never stated.
  • A banner ad right here on TV Tropes promoted The Church of Scientology, rhetorically asking, "Why is it the world's fastest-growing religion?" Hmmm, maybe because this religion that cannot be named for legal reasons was founded less than 100 years ago, and most major religions are thousands of years old and likely have grown as much as they ever will? Or because they count ad clicks as memberships.
  • An ad for an internet phone service claimed that you could save $200 a month by switching, citing a chart showing all the associated fees and pricing. The product for sale listed a price of $25 a month with no installation or other fees, while the sample phone company was cited a price of $120, with $80 in associated fees. Disregarding the fact that you would only save $175 if taken at face value, the price of $120 was for six months of phone service, and the fees would have only been paid once. Looking at just price per month, the internet phone cost more than the sample company.
  • A cellular phone service in the US claims to have cheaper phone bills... if you bring your own phone. If you buy a phone from them, you have the option of buying the phone outright, or paying it off in two years, which brings the bill up to what the bigger carriers charge for a similar deal.
  • The term "unlimited bandwidth" that internet and cellular phone service providers love to advertise has gotten a lot of bad flak because people have found out yes, there is actually a limit to how much bandwidth you can consume from your provider before they start taking punitive action. Perhaps it was "unlimited" when speeds were so slow you couldn't manage to breach it even if you constantly were downloading something.
  • There's a billboard along a freeway in Michigan, advertising a dentist willing to do implants for only a couple hundred dollars. Next to it is a statement saying "Voted best dental office in Michigan". Just below that, in smaller text, is the disclaimer "by our dental staff".
  • The German ad for Fisherman's Friend Mint bonbons said nine of nine real men liked Fisherman's Friend bonbons. Shortly after throwing one of their test subjects overboard.
  • One ad for milk lays down the claim that 50% of children don't get enough of the nutrients common in milk. It then tries to scare the viewer into giving their kids more milk by playing this as if it were a 50/50 chance, which would only be the case if all children drank the same amount of milk but 50% of them didn't absorb the proper amount of nutrition from it.
  • Hand sanitizers and antibacterial soaps always claim to kill "99% of germs" on packaging and in commercials. What they don't say — or will only say in in tiny print on the bottom of the screen — is that this was in a laboratory. There's a difference between killing germs in a petri dish and killing germs on your hands, and when tested under real-world conditions, the kill rate is closer to 40%.

    Anime and Manga 
  • Shizuo in Durarara!! maintains that the series's troll, Izaya, is behind "99% of all the weird crap" that goes on the setting. Sure, Shizuo can get irrational when mad, and will even use statistics and percents to maintain points. ...Did we mention Izaya's a troll? We can only assume that he means every single weird thing.

    Comic Books 
  • An old Archie story had one of the characters becoming a statistics-obsessed nut for the duration of the story, only for Jughead to start citing statistics that horrified them and lead them to run away in fright, at which point Forsythe noted that some ridiculously high percentage of people who quote statistics "make 'em up on the spot!"
  • Batman: The Penguin says this quote word-for-word in Detective Comics #684, at the same time pulling a You Have Failed Me on a newly-acquired henchman who, through statistics, "proved" that a broad daylight robbery had a 0% chance of being foiled by Batman.
  • Judge Dredd: The Dark Judges famously use the statistic that none of the people they execute will ever commit another felony again as proof that death is the cure for crime.
  • In Asterix and Cesaer's Gift, when Orthopedix is challenging Vitalstatistix for chiefship, he tries to court Fulliautomatix's vote by buying his anvil. Later, during the debate, Vitalstatistix says under that his leadership anvil sales went up 100%, and Orthopedix replies that you can make statistics prove anything you like.

    Comic Strips 
  • Dilbert:
    • Dogbert once sold "value-priced lottery tickets;" half price, odds of winning only one in ten million less.
      Sucker: Hey! This is for yesterday's lottery!
      Dogbert: And your point is...?
    • The Pointy-Haired Boss tells the employees that he's found out that 40% of sick days are taken on Monday and Friday, and declares this to be "unacceptable". Asok laughs until he realizes that the boss is actually that stupid.

    Films — Live-Action 
  • Bowling for Columbine: Moore exaggerates the level of gun violence in the United States through spurious use of statistics, specifically comparing the amount of gun-related deaths in several western countries by citing gross figures for each country and not per capita stats. Even aside from that, the numbers he cites didn't match any known independent studies. Eventually, it was revealed that he took US Government crime statistics for gun homicides, and added uses of guns for self-defense and the use of guns by police.
  • Fat Head:
    • The obesity epidemic is actually because the parameters for who is considered overweight vs. obese was changed. Then there is the shift in age demographics; when the median age of the population changes from 26 years old to 35 years old, it's to be expected that the average person's weight would be an extra 10 pounds. Ethnic diversity also plays a role, with African Americans and Latinos more prone to heavier builds. Tom even noted that it took him several hours on a busy street corner to find even a handful of shots of extremely heavy people. He argues that these statistics are manipulated by NGOs with political agendas and government agencies that are more concerned with securing funding than actually solving problems.
    • Ancel Keys deliberately messed with his research to "prove" the lipid hypothesis, throwing out more than half the countries he examined because their data did not fit his pet theory that animal fats are bad for human health (despite humans having evolved to eat fruit and meat, not grains). For instance, Chile ate little fat but got a lot of heart disease, while Norway and Holland ate a lot of fat but got little heart disease. He was not the only one who deliberately messed with the data, either.

  • Darrell Huff's "How To Lie With Statistics" was printed in the '50s. It's usually available on eBay, still in print, and is a very easy read that shows you all the basics. To give you an idea, there's a long section devoted to the fact that there are least three different methods you could use to get something you could reasonably call an "average", and for some data sets at least one of them can be very different from the others. For example, if a company says their average wage is 3 times minimum wage might actually pay everybody around 3x minimum wage (the types of average called the "median" or "mode"), or they could pay everybody minimum wage (or even less, if they can somehow do that and get away with it) except the boss who gets thousands of times that, bringing the type of average formally known as the "mean" up.
  • Spoofed by America (The Book), which included a graph on "Growth of Misleading Charts". Two different bar heights represent the same number.
  • A book entirely revolving around poking fun at this is Spurious Correlations. A spurious correlation is when two variables appear to be related, but one variable is clearly not causing a change in the other. The author used statistical software to find correlations between variables that had nothing to do with each other, like finding out that the divorce rate in Maine is positively correlated with the amount of margarine consumed in the state.
  • A Sailor of Austria, by John Biggins. A government official produces a graph showing that Austria-Hungary will be the dominant naval power in the Mediterranean by The '60s, the historical irony being that the empire had disintegrated by 1918. The worth of this man's calculations are shown when he assigns Otto Prohaska's submarine for a long-range mission for which it's blatantly unsuited — not only is it a small coastal submarine, there's been no allowance made for where they are going to store the food, fuel and lubrication oil for such a trip. His response when this is pointed out is simply to order Otto to go ahead regardless and leave in a huff.

    Live-Action TV 
  • Yes, Minister:
    • There's a very interesting section on this. In a discussion about conscription, Sir Humphrey demonstrates to Bernard how statistics can be obtained which prove both sides of the discussion correct, through the use of leading questions that are not included in the reporting of the survey concerned.
    • Another episode combines this with Hypocritical Humor; during one of their many arguments, Hacker brings up some facts to support his point only for Humphrey to superciliously note that Hacker's facts are based on statistics, which are thus unreliable as per this trope. When the argument gets a bit more heated, however, Humphrey begins to cite some statistics that prove his point, only to catch himself and quickly refer to them as 'facts'. Hacker is quick to point out the hypocrisy.
  • ABC loves to put out press releases trying to make the previous night's viewership of their shows look good. With their big hits, this isn't so bad; winning the timeslot in total viewers or Adults 18-49 (the demographic used to set ad rates, and thus the figure used to determine whether or not a show gets renewed) is definitely something to be pleased about (unless there's a huge skew between total and A18-49 viewership, but that's another matter). No matter how poorly-watched a show is, however, the ABC PR department can find some figure that sounds good but doesn't actually mean the show's doing well. They frequently put up demographics that aren't really indicative of a show's survival (e.g. women 18-34, or the adults 25-54 demo that only some cable channels use for ad rates), give the amount that the show built on its lead-in (usually when the lead-in was a repeat or another low-rated show, or a repeat of another low-rated show), or claim the show had the best performance in its timeslot among ABC shows since X weeks/months/years ago (when you look at the absolute ratings, all it says is that ABC's done even worse in the past; this is rarely used for hit new shows since there are usually better statistics for those).
  • Programs on Animal Planet are fond of citing how Americans spend more money annually on cat or dog food than on baby food. This is depicted as evidence that Americans pamper their pets like babies but overlooks several facts: that pets eat pet food for their entire lives, whereas babies only eat baby food for about a year and a half, and that many families have more than one pet at a time, but relatively few have more than one child of an age to eat baby food at the same time. Also, a baby often consumes breast milk from the mother which wouldn't show up in the statistics when calculating the cost of baby food. It also doesn't take into account the many people who make their own baby food, or feed their babies foods like applesauce or bananas that are already nice and soft; pet food is significantly harder to prepare.
  • QI is well known for deliberately phrasing questions like this in order to confuse the participants. One question was "What is three times more dangerous than war?"note  The answer given was work because three times as many people are killed each year in work-related accidents than die in wars. Now, consider how much time you spent working last year compared to how long you were in a warzone. This prompted unhelpful responses from the panelists: "What if you're a soldier?" "What if you work in a shoe shop, near a war?"
  • Monty Python's Flying Circus parodied the use/abuse of meaningless statistics in the sketch "Spectrum":
    Man: This bar in this column represents seventeen percent of the population. This one represents twenty-eight percent of the population! And this one represents forty-three percent of the population!
    Host: Telling figures indeed. But what do they mean to you? What do they mean to me? What do they mean to the average man on the street?
  • Parodied in Australian political satire The Dingo Principle:
    Listen to this: 40% of people support the Prime Minister and 50% support the Opposition.
    That's only 90%.
    Yeah, there was one guy who said the samples weren't big enough to be statistically significant.
  • Penn & Teller: Bullshit! point it out by having a man who makes poll research for the Republicans show he can make someone give two different answers to the same question by first asking: "Do you think the government expends too much in health care for immigrants?" The bystander answers "Yes". When he asks: "Would you deny an immigrant the right to treat himself? To give birth in a hospital?" and other medical services that go well beyond what the governments expend with immigrant health care, the answer now is: "No". Also, they make fun of the guy with his own mathematical wizardry by pointing out: "In this scene, ten cars pass by behind him. One guy from one of the cars shouts saying he sucks. This means that AT LEAST 10% of the American population believes he sucks".
  • In an episode of Psych, young Shawn attempts to justify his fear of shark attacks with the statistic that most shark attacks happen in about three feet of water. His dad points out that most swimming in general happens in about three feet of water.
  • The Wire: A major theme in the series is how organizations will "juke the stats" to make it look like the organization is more successful than it is. The police department will downgrade crimes when filing them to make the crime rate look like it's going down, or start focusing on low-level, trivial arrests to make the conviction rates go up. When Prez gets a job as a teacher, he immediately notices the same tricks being done in standardized testing to make it look like students are performing better. Reality plays almost no part in what the stats suggest.
  • In the BBC programme Shop Well For Less, Once an Episode they run a test where they compare different brands of the same product, however the conclusions they draw from these tests are often highly inaccurate. For example, in one episode they tested waterproof plasters by sticking three plasters on each person, with a different brand being used for each, and then having them swim for a set amount of time. The brand which had the most plasters remaining afterwards was deemed the winner, and they tried to use these results to claim that the cheapest brand was the best. However, there were a number of factors they didn't consider. The test group only consisted of five people, so it was unlikely that the results were statistically significant, and no statistical test was carried out to determine whether the results were significant. Even assuming that they were, the people in the test group were all of different ages and may have had different skin types, amounts of body hair, levels of activity when swimming, etc. These factors would have affected the ability of the plasters to stick to the skin. All the members of the group were also male so the results can't be applied to women. There's also the fact that adherence to the skin isn't the only factor which determines the quality of the plaster, you would also want plasters to be absorbent, not damage the skin when removed, promote healing of the wound, etc. Finally the plasters were tested on undamaged skin rather than a wound and may have performed differently when used as intended. So overall, the results of the test are pretty much useless and can't be used to conclude anything at all.
  • Firing Line: Buckley's 1981 interview with Dr. Thomas Sowell mainly focused on the misuse of statistics to allege institutional racism or sexism. As Sowell pointed out, the stats most often cited by those trying to push that particular political agenda are group-level comparisons of "wage gaps", but when one factors in variables such as age, experience, profession, and workload, those differences either diminish or disappear, or even show a disparity in the other direction.

  • The Arrogant Worms' song "Don't Go Into Politics" recommends that audiences avoid the fields of politics, science, and music. To support their argument, it points out that people like George Washington, Albert Einstein, and Leonard Bernstein did so, and they're all dead.

    Print Media 
  • Newspapers love doing this with drug-related stories. It's almost impossible to see Ecstasy mentioned in a British newspaper without the qualifier "That killer drug", the supporting statistic is that a dozen people die per year from consuming it. Yet over the course of a year they will rack up an impressive body count in stories about fatal car accidents without ever devolving into calling cars "Those murderous rampaging kill bots" How many Britons drive? How many take E? And how many deaths are caused by legal drugs? - cigarettes, alcohol, over the counter medications, misused prescriptions... And that's not even counting the fact that comparing legal and illegal things is a comparison of apples and oranges. Alcohol was much more dangerous during prohibition as it often wasn't pure and alcohol concentrations were often higher than usual as this was more interesting to smuggle. If Ecstasy were legal people would be educated about its use and avoid harmful interactionsnote , impurities would not be an issue, an accidental overdose from misjudging the dose impossible and it would probably be sold in 25-50mg pills instead of 200mg. Taking those factors into account in the statistics wouldn't help to support the viewpoint of the author, so they are generally left out.
  • An Ars Technica article discussed the statistics usually used by software developers to complain about piracy. Specifically, the article pointed out that the statistics most commonly cited are most likely not only bullshit but old bullshit. Amusingly enough, the image used for the related post on Gamepolitics was a pie chart divided into three sections, marked "Lies/Damned Lies/Statistics".
  • The Column 8 column in the Sydney Morning Herald once referenced a statistical correlation between the difficulty of the sudoku on a given day and the price of petrol.
  • There is a semi-famous magazine article from 1958 called "The Dread Tomato Addiction" that correlates the consumption of tomatoes with everything from death to communism. It can be found here. There is a similar article about bread that can be seen here.

  • There is a book produced for people in radio every year that compiles countless statistics about all stations taken from polls. These are used to attract advertisers. The less successful stations that have very few listeners are often forced to hire people who read through the book to get as many favorable statistics as possible, no matter how convoluted they may be. With the huge amount of data in the book, it's possible to say, for instance, that 85% of married men aged some arbitrary amount with income in some arbitrary range and who own a ferret will love your show, even though they represent a tiny proportion of the population. Of course, if you're selling ferret food, that's exactly whom you want to reach.

  • The Australian Football League managed to turn an increase in positive drug tests into a decrease in positive drug tests. [1]
  • A joke about a U.S.-U.S.S.R. athletic event. When the American wins, the Soviet media reads that the Soviet athlete finished second, but the American finished next-to-last.

    Stand-Up Comedy 
  • A stand-up comedian once said, "There is a direct correlation between being a serial killer, and being born. Show me one murderer who was never born."

    Tabletop Games 
  • One of Bothered About Dungeons & Dragons (BADD)'s favorite weapons was a list of over 500 Americans they claimed were gamers who had committed suicide in the same year. Thus role-playing games somehow cause suicide. Except that even if you take this bogus statistic at face value, 500 suicides a year is still a lower percentage of suicides than clergy and a tiny fraction of the average.
    • Patricia Pulling, the leader of this organization, once said in an interview that "8% of the Richmond VA-area population is involved with Satanic worship at some level." When asked where that figure came from, she said that she estimated (read: pulled from her butt) that 4% of the teenagers and 4% of the adults engaged in Satanic worship. She then added them together and got the 8%.
    • Another time, BADD cited an increase in suicides corresponding with a major Dungeons and Dragons release. Again, however, there's no evidence that's not simply a coincidence, as similar statistics can be used to prove that the release of a Britney Spears CD caused suicide numbers to jump.

    Web Animation 
  • FreedomToons: Often, the videos will point out how some statistics that could be seen as a good thing give off a false impression.
    • Both "Government Good, Guns Bad!" and "Support Gun Control You Child Hating Bigot!!" point out that while gun violence in Australia has gone down since its gun ban, gun violence was already going down at an identical rate before its gun ban was put into law.
    • In "Only 2% Of Rape Accusations Are False???", Seamus calmly breaks down the actual statistics behind this claim and the uncomfortable truth that in the vast majority of cases, there's no conclusive proof either way.
    • This is the bread and butter of "The Debunkers" series, which stars two men living in a bomb shelter who spend their free time debunking YouTube videos. If a video they're analyzing gives a statistic, they'll cite the full context of the statistic which usually gives off a different impression than the out-of-context statistic implies:
      • "Debunkers vs. Medicare for All" goes into detail about the Canadian Healthcare System, and the myth that universal healthcare would fix everything. While it does have a universal healthcare system, there's so much red tape and bureaucracy that people can end up waiting months for emergency surgery, and citizens end up leaving Canada to find better healthcare in other countries. It also notes that despite the problems with America's healthcare system, the nation ranks first in the world in terms of quality, whereas Canada is ranked seventh.
      • "Debunkers vs. Abolishing the Electoral College" makes a statement that a pure popular vote is a bad idea. Claiming that it would lead to a case where states with large cities (Chicago for Illinois, Los Angeles for California, etc.) would eclipse the voices of less populated states.

  • Saturday Morning Breakfast Cereal:
    • This strip argues that any theory has a small percentage chance of success, and since all those percentage chances amount to 100%, he can create billions of theories as to why he won't die, and one theory as to why he will, making the likelihood that he will die statistically insignificant. He still dies.
  • xkcd:
    • This strip concludes that the news media got the supposed relationship between cell phones and cancer backward, i.e., cancer causes cell phones.
    • Also this one, which combines it with a dash of Hypocritical Humor:
      Newscaster: ... and in science news, according to a new study, 85% of news organizations repeat "new study" press releases without checking whether they're real.
    • And one about the significance of 95% confidence when you run 20 tests and only publish the interesting one.
    • Another comic points out that the observed mortality rate among humans is only 93%, overthrowing most "100% of people who do X die" statistics.
    • And again, noting that you could send customers a live bobcat instead of their ordered item 1/30 times and still have a 97% positive rating on Ebay.
  • Sleepless Domain: An early interstitial features a Magical Girl recruitment poster, which lists the benefits for active magical girls to register with the BMG. Among these, it cheerfully notes that registered magical girls have a 70% lower chance of experiencing serious injuries or fatalities than those who haven't registered. Note the lack of any absolute numbers in that statement — just how many registered girls are killed or injured on the job, and how many more are unregistered?

    Web Original 
  • Cracked:
  • Often used in the News Parody Chigüire Bipolar for example in Maduro has 65% of Maduro's popular support, according to polls.
  • The Onion does parody this from time to time.
    • An article was about a movement to shut down hospitals because "despite rapid advancement in medical technology, the world death rate remains at 100%."
    • Another article said that children are universally opposed to children's health care, with responses to the question "Do you want to go to the doctor?" ranging from "NO!!!!" to "inconsolable crying," but no children in favor.
  • From 'Fat, French and Fabulous', "Statistically, the average person has slightly less than two legs." Statistics are fun when you don't use them properly.
  • Tumblr has a meme that relies on a subversion of this for comedy, serving as an explanation of what a Statistical Outlier is. According to this meme, people in general do not eat 3 spiders every year. Rather, it is one guy named Spiders Georg, who eats over 10 000 spiders every night, who's messing with the results, which should be accounted for.

    Western Animation 
  • The Boondocks episode "The Color Ruckus" showed Uncle Ruckus as a child, being homeschooled by his mother, who at one point made this claim about George Washington Carver:
    Bunny Ruckus: "George Washington Carver was the man responsible for more peanut allergy deaths than any man in history!"
  • An episode of The Simpsons featured Homer forming a vigilante group to fight crime. At one point he recruits Jimbo (who calls the group "the drunken posse") on the basis that he can swing a sack full of doorknobs. Homer later gives an interview to the local news:
    Kent Brockman: Mr. Simpson, how do you respond to the charges that petty vandalism such as graffiti is down eighty percent, while heavy sack beatings are up a shocking nine hundred percent?
    Homer: Aw, people can come up with statistics to prove anything, Kent. Forfty percent of all people know that.
  • The Justice League was asked: "Maybe you'd care to explain why on your watch, 50% of marriages now end in divorce and the other 50% end in death!" Aside from the fact that the same was true before the formation of the League, until the end of time, a significant portion of marriages will end in death, as people do have a tendency to die, married or not. That and one can get divorced multiple times - absent resurrection, one can only die once. A somewhat more reasonable one is Godfrey's claim that since the League formed, "white-collar crime is up 3%!" While a more damning statistic, it's also the one kind of crime that the League doesn't get involved in much (not to mention it's a pretty small increase that could easily be unrelated).
  • An episode of Cyberchase featured Hacker using this. First, when trying to get hired as an exterminator at the Cybrary, he used two bar graphs that appeared to show that Hacker caught more bugs than his competitor but when the scales were added, Hacker's graph used smaller numbers than the other, causing the results to be inflated. Later, when the kids are trying to prove that the Cybrary is infested with bugs that are attacking the history section, he uses a graph with an inflated scale to make the bars look smaller and thus make there appear to be no problem.

    Real Life 
  • During World War I, helmets were almost withdrawn from British soldiers. When Britain started issuing steel helmets to all soldiers on the western front in 1916, generals began to call for their removal as they increased incidences of headwounds twelvefold and doubled total casualties. The reason? If someone gets hit in the head by some woolly bear or flying frog (German H.E. or rifle grenade) shrapnel and lives it's a "head wound" and if they are unable to fight, the person is a "casualty"; if they die from a bullet in the brain, then they are a "fatality" and so don't appear on casualty statistics. Since helmets let more people survive, the number of head wounds soared. A politician used the numbers to support his position that "helmets are expensive and cause cowardice" (which, as it turns out is exactly the opposite of the kind of behavior helmets encourage, see below), and never explained what it really meant - doubly effective as most people don't know the difference between "casualty" and "fatality". The real justification behind the attempt to withdraw helmets narrowed down to, "all a dead soldier needs is a funeral." A wounded soldier gets dragged out of combat by at least one of his buddies, and then provided weeks, months or even years of medical attention. From a statistical standpoint, adopting helmets drastically increased the effectiveness of enemy weapons - and a lot of WW1 generals genuinely believed in disposable personnel. Luckily, more ethical parties changed the way they recorded casualties, or the helmets would likely have been recalled.
    • Likewise, the number of cyclists being treated for head wounds have increased massively since wearing a helmet became more widespread. Of course this is because they previously wouldn't have survived the accident at all.
    • Situations like the cyclists mentioned above also can also be attributed to the Peltzman Effect, aka Risk Compensation. This is the effect of a person being aware of greater safety ("I don't have to worry about hitting my head, I'm wearing a helmet!"), and taking greater risks due to the perceived increase in safety. So there actually could be an increase in injuries, due to more people taking greater risks.
    • Sick as it was, WW1 quickly devolved into a stalemate, at which point it was clear that the loser would be whichever side ran out of men or money first. With sufficiently large draft pools, conserving resources was more important than conserving manpower.... until 1915, that is, when they began to realise just how shallow their manpower-reserves actually were relative to the demands of the war. By 1917 they were basically doing everything they could to conserve their manpower, to the point that they produced enough helmets to equip even the logistics personnel (i.e. people who might but probably won't be facing shrapnel, bullets, etc, etc).
  • At some Reform Judaism synagogues, a popular "joke" to lead into the sermon is, "x% of deaths occur in a hospital, x% of deaths occur in a car, x% of deaths happen in the home...[continues on for a while] while there have been only three deaths in a synagogue, and no deaths ever reported while studying Torah! Clearly, the safest passion, therefore, is studying Torah."
  • Pretty much the oldest trick in statistics is implying that because X is increasing/decreasing and Y is doing the same or the opposite, then X must be affecting Y. In reality, this isn't necessarily so unless you can manipulate one of the variables. Without other evidence Y could be causing X, or they could both be caused by Z. For example if someone presents a graph that shows street violence is increasing as video games are getting more violent,note  they want you to think that violent games are causing street violence, but you can easily come to the conclusion that video games are becoming more violent as a reflection of a more violent society.
    • For an example of X and Y being manipulated by Z, the number of pipes burst and the number of sweaters worn both go up as a result of freezing temperatures. Someone who hates sweaters could take this information and make is into a graph of pipes broken versus sweaters worn, and from that data alone it would appear wearing sweaters causes pipes to burst.
  • A related strategy was used by US president Richard Nixon to portray marijuana as a gateway drug. His anti-drug team estimated that 80% of marijuana users go on to use cocaine; actually, 80% of cocaine users had started with pot, but only about one in 2,400 marijuana users (just under 0.042%) go on to use cocaine. And related to that, most people willing to take a drug as dangerous as cocaine are willing to take a drug as relatively safe as marijuana. It's the same reason most marijuana smokers have drunk alcohol at some point, and why most alcohol drinkers have drunk something with caffeine in it. Water: the Gateway Liquid.
    • One study cited by this article has experts ranking various drugs by their relative danger to individuals and those surrounding them. The original study appears to be fairly legitimate, yet the article commits a statistical sin of simply adding the value of 'harm to self' and 'harm to others' together to rank each drug. There is solid evidence that marijuana itself is very safe if vaped, as opposed to smoked. The same goes for nicotine, which was also found by the same study, commissioned by Public Health England, to be relatively harmless when the pure extract was vaporized. Alcohol is often perceived as less harmful than marijuana and cigarettes, despite the dangerous behaviours it can create.
  • When Ronald Reagan's Attorney General Edwin Meese wanted "proof" that pornography was evil, he created the Attorney General's Commission on Pornography. The commission members were a preselected cohort of anti-pornography campaigners. Not surprisingly, they discovered that statistics "proved" that pornography caused crime. However, the 1970 report of the President's Commission on Obscenity and Pornography, which was done by honest researchers and was highly praised for accuracy and honesty, discovered that there was "no evidence to date that exposure to explicit sexual materials plays a significant role in the causation of delinquent or criminal behavior among youths or adults."
  • In the heated German censorship debate about blocking sites allegedly containing child pornography, an organization in favor of this censorship law ordered a survey at a market research institute with questions asking if the person taking the survey is against child pornography and in favor of blocking the websites containing it. Over 90% answered 'Yes'. Another survey ordered by an opposing NGO — at the same institute no less — used a slightly different phrasing: Do you agree with blocking the content despite the fact that this content still exists and is easily accessible after the censorship? Over 90% answered with 'No'.
  • Many casinos like to advertise their slot machines with lines like "Up To 99% Payout!" to make it sound like the player has a good chance to win. First, "up to" means the payout could be 1% for all you know (although laws usually set a minimum). Secondly, even a 99% payout means that for every $100 you put in the machine, on average, you'll get $99 back, i.e. you still lose. That "99% payout" is also an average that is based on something like one million pulls (plays) on the machine. If you play 100 times in one slot machine, you're not getting a representative sample of that average. These machines work differently in the UK. UK Fun With Prizes are required by law to seek their set hold percentage within a certain number of spins (usually 10,000). To achieve this, they naturally cheat all the time. They also can be, and often are, programmed to go on a suck cycle and take in way more money then they need to, in order to save up for a large series of payouts later.
    • A machine may have one payoff rate if you bet a single coin per spin (which most casual gamblers do) and a completely different rate if you bet the maximum coins per spin. For example, the payout for a video poker game might be $1000 for a royal flush if you bet one coin, but $7500 if you bet five. The advertised payout rates assume the player is playing maximum coins, so a casino can have a slot machine that has a completely legal and legitimate payout ratio of one hundred percent (or even higher) and still manage to make money on it.
    • The payoff ratio is also allowed to assume "perfect play"; that is, the person playing the machine knows to do certain things that may be counterintuitive to a casual player or even an experienced player who has not fully analyzed a particular machine's payoff values, which are frequently different even on machines of precisely the same type right next to each other in the same casino.
    • Truth in Advertising laws require that if a set of machines is advertised as "Up to 99% Payout," then at least one of them must have 99% payout. Though there may very well be 50 other machines with 10% payout. Just don't expect that the "lucky" machine will be marked in any way, and since slot machines are computerized these days, most likely the lucky one changes by the day.
    • The history board on roulette tables gave the illusion that the previous numbers the ball has landed in means that it should have a higher chance of landing on a number not on the board. Except the roulette table has no concept of memory and the ball has an equal chance of landing on the same number as before no matter how many plays were made. If the roulette wheel has any bias at all, it's more likely in favor of the numbers on the board — but don't bet on it, as the gambling industry works very hard to ensure their devices are all truly random.
  • A common problem encountered is Simpson's Paradox, best demonstrated by example: Suppose Hospitals 1 and 2 are nearby, but 1 is better equipped for treating people with severe injuries, so proportionally more of the people taken there are badly hurt. It does better at treating badly hurt people than hospital 2, and also does better at treating people who are not badly hurt. However, since people who're badly hurt are more likely to die than people who're not badly hurt whether or not they go to hospital 1 or hospital 2, hospital 1 may still have a higher overall death rate.

    Simpson's Paradox is when data shows one trend, but dividing it into categories shows the opposite trend. In the example above, hospital 1 has a higher death rate, but if the patients are split into categories based on severity of injury, it has a lower death rate in each category.
    • The same goes with good doctors and bad doctors, as told in the book Super Freakonomics. Good doctors are generally given tougher cases while bad doctors are given easier cases. However, if you look at death rates you see that some doctors have higher death rates, but these are usually the good doctors. Patients with serious cases are more likely to die, so good doctors lose a lot of their patients than, say the doctor who cures hiccups. The lesson is that you can be fairly certain that the doctor you receive at a hospital is competent enough to be assigned to you.
  • Italy got Südtirol, which used to be a part of Austria, to be added to their territory after World War II by using this kind of statistics to convince the Americans that the area was mostly populated by Italians. Which it wasn't. To this day, most of Sudtirol's population speaks German as a first language and watches German and Austrian TV, rather than the Italian channels.
  • Wolf Blitzer on polling information about the health care debate in American politics:
    We did that poll CNN Opinion Research Poll, that said, "You like this health care bill or not like it?" We just assumed, a lot of us, that the people who said they didn't like it because it was too much interference, or too much taxes or whatever. But if you take a closer look at people who didn’t like it, about 12% of those people who said they didn’t like it thought it didn't go far enough. They wanted a single-payer option, they wanted the so-called public option, they didn’t like not from the right, they didn’t like it because it wasn’t left or liberal enough. That’s how you got 50% of the American people who said, "We don’t like this plan." But only about 40 or 38% were the ones who said it was too much government interference.
  • In the 2004 US Presidential Election, Dick Cheney and John Edwards stated conflicting numbers regarding the Iraq war's casualties... and both men were partially right! Skip down to "90% of the casualties".
  • One statistic used to justify the creation of The Comics Code Authority was that a large percentage of criminals liked to read comic books, ergo, comic books influenced people to become criminals. Nobody pointed out that they were using the wrong statistic - they should have been asking what percentage of regular comic book readers became criminals.
  • The Victorian-era belief that masturbation could drive men insane was derived from a similar error, in that mental asylums reported frequent Dates With Rosie Palms among inmates. The fact that mental illness can impair inhibitions against such behavior wasn't considered, nor the fact that men locked up in an asylum had few other respites from misery, frustration, or boredom. Most importantly, nobody had the nerve to ask about the masturbatory practices of men who weren't institutionalized.
  • When Anthrocon decided to move from Philadelphia to Pittsburgh, one blogger who protested the move cited that only a tiny number of people would be as likely or more likely to attend Anthrocon if it moved to Pittsburgh. The organizers, however, heeded a different statistic: those that lived so far away that the move made little difference.
  • occasionally shows how statistics get misused. For example, here (on small samples it's quite possible that B isn't significantly different from A or C, but you can put it as "B isn't different from A, C is different from A, so we see that C is different from B", which is wrong) and here (limit the view to one of many multipliers which per se can't prove anything). Unsurprisingly, the areas with traditional relations to snake oil trade suffer most.
  • Cryptozoology buffs are fond of citing the fact that new species of animal are still being identified with some frequency, and alleging that this means many other "hidden" species must exist under mainstream scientists' noses. They conveniently overlook the fact that most such species discovered in the last few decades are either found in isolated locales where no biologist had previously looked for new species (caves, obscure jungle canyons, deep-sea ecosystems, tiny isolationist nations), or are "found" when DNA analysis reveals that what had been considered one species is, technically, two (e.g. African forest elephants being genetically distinct from plains elephants). Not to mention the fact that the vast majority of new species are things like insects, small birds and reptiles, or deep-sea fish, animals that can easily escape notice unless someone is looking for them, and not the magnificent megafauna monsters that cryptozoologists crave.
  • It was once reported that the US was using 250,000 bullets to kill a single insurgent in Afghanistan. The most major problem with this is that they conveniently forgot to explain that this included all the bullets the military was firing, even during training and weapons tests. Never mind mentioning that most bullets go toward suppressing fire or that most casualties in war are victims of bombs and artillery (which this statistic took the care to exclude). It was finally revealed that this number had used a lot of generous rounding to get to that number.
  • And while we've mentioned it rounding can be used to substantially change outcomes, especially if different methods of rounding are used at different points of the calculations.
  • The previous Iranian government (led by infamous president Ahmadinejad) was notorious for this. In a very obvious example, they reported the unemployment to have decreased by 50% while other independent sources suggested otherwise. Later it was discovered that they had changed the definition of an "employed" person from "one working at least 20 hours a week at a paying job" to "one working at least 2 hours a week". By removing the "paying" condition and cutting the time to one-tenth, they had managed to include people doing a variety of voluntary works and kids helping in family businesses a couple of hours each day (and still only managed to reduce the unemployment percent by 50% which goes to show how messed up their work was).
    • They did the same when calculating inflation percent. When every source (from independent economists inside the country to World Bank) was reporting a point to point inflation of above 40% (as was apparent in increased prices everywhere) the official sources reported inflation of 20% or less. How did they do it? By removing some essential items like rice from item basket (the selection of items whose prices were used to calculate inflation, originally including 300 items, mostly household and food products) and adding useless items unpopular electronic devices (like house alarms) to the basket. This had a two-fold effect: 1) It removed the most popular items that naturally experience a larger increase in price during inflation and 2) Added items with little increase in their price, increasing the population without increasing the calculated inflation.
    • In fact they were so bad at this that pictures of Ahmadinejad showing graphs (without title or source) and saying "I HAVE PROOF" is now a joke in Iran used to show when someone talks bullshit without evidence to back it up.
  • A commonly-cited factoid about the American Revolution is that roughly 1/3 of the residents of the Thirteen Colonies favored independence from Britain, 1/3 opposed it, and 1/3 were undecided or apathetic. The comedy series History Bites (based on the premise: what if TV had been around for 5,000 years) parodied Tom Paine as a spin-doctoring pundit:
    TOM PAINE: Only 1/3 of the colonists are opposed to independence. Now, you can't let a minority opinion like that influence public policy!
    INTERVIEWER: But the same number are in favor of independence.
    TOM PAINE: But now we're talking half of decided voters, which is essentially a majority. You can't ignore the wishes of half of decided voters!
    • The original "statistic" doesn't come from any actual poll anyway... it was an estimation made by John Adams, and he admitted he'd not done any research on that, just that it was his feeling on the matter.
  • The Church Of The Flying Spaghetti Monster has semi-famously pointed out the obvious correlation between the decreasing number of pirates worldwide and Global Warming.
  • Something of a historical subversion: During World War II, the Royal Air Force wanted to add more armor to their planes, but because of weight limits they needed to know which places needed the armor most. So, they examined the planes after they came back and counted how often bullet holes were found in certain areas... and then placed armor in places that showed the fewest bullet holes. This is because they'd spotted the flaw in their sample group; all they had to examine was planes that had come back. The data did not show, as might be assumed at first glance, places that planes were most likely to be shot. It showed places that planes could be shot and still fly home.
  • One of the reasons France is known as a bunch of cowards who can't make war is that its much-needed rifle update kept getting blocked by the argument "we have enough rifles". While it was true that France had a ridiculous number of infantry rifles, those numbers did not take into account that nearly all of them were flawed and most of them were really flawed. The reason it had so much was the French army was forced to try and replace the slow loading and antiquated Lebel riflenote  with the somewhat finicky Berthier during WWI. It was prudent to replace both of these anyway, but continuing to use them would have necessitated retaining old unreliable machine guns. When the Germans invaded, the French were caught in the middle of the slow-going replacement program and were forced to use effectively four rifles with two incompatible calibers. History can speak to the results. The lesson: statistics do not speak for quality.
  • A similar scheme based on the same logic was used by Soviet admirals to ask the government for resources to build new ships. The navy would ask for X amount of money to add four cruisers to the Soviet fleet. X would always look like a reasonable amount of money for four ships so the central government would approve. The navy would then bring three obsolete cruisers out of reserve and commission them then build one new cruiser. For the next year or so the navy would honestly say that they had four more commissioned cruisers than before and the politicians would be satisfied. Then the navy would quietly decommission the old cruisers and repeat the scheme.
  • Research into Psychic Powers in the 1970s ram up against this trope when people who (by pure luck) scored well on card-guessing procedures were singled out for re-testing under closer observation. Unsurprisingly, repeated tests found their apparent "powers" didn't work at all the second time around. Had the researchers re-tested the entire population of subjects again, not just the lucky guessers, they'd have found a similar proportion of high-scoring subjects randomly distributed among the volunteers. Instead, the idea that being observed made psychic powers wane was propagated to account for the "mysterious" decline.
  • Glurge-y Facebook spam will often end with something to the effect of, "Only 3% of your friends will be brave enough to share this," effectively trying to guilt the reader into helping the spam proliferate.
  • When reporting on the decline of a particular caribou herd in the Canadian Arctic (the Bathurst Herd), it's common for reporters and environmental groups to compare the current low numbers to the herd size in 1986 to demonstrate in how bad a shape the herd is currently in. What's never mentioned is that 1986 was the record high number for the herd count, and was 3 to 4 times the average number of animals counted in other years.
  • This is commonly done when reporting the unemployment rate in the United States. At the end of Barack Obama's presidency, unemployment was officially at 4.7%. However, the word "unemployment" is defined differently in the US than what most people assume it to be. The US defines "unemployment rate" as "percentage of working-age adults (18-65) receiving unemployment compensation," typically after getting laid off (you normally don't get it if you quit or got fired). The assumed definition of unemployment, "percentage of working-age adults who don't have a paying job," is called "labor force nonparticipation" and is closer to 40%. But that figure is also misleading because it includes people who aren't looking for paying work, such as the disabled, early retirees, stay-at-home parents, full-time students, or even those that simply gave up on searching. There's also the issue of under-employment, where yes Alice has a job, but it's part-time and/or minimum wage (or close to it), so she still relies on government assistance like food stamps or Medicaid. The true figure that people are looking for—the percentage of working-age adults looking for a full-time job that supports them without having to be on welfare—is difficult to pin down.
    • In the US, the U-3 Unemployment Rate is the "official" rate, and is defined as persons able to work and who want to work who have sought employment within the last 4 weeks. It does not include underemployment, disability, or people who aren't looking for work. While the technical definition of the U-3 rate are well-known to anyone with the right academic training, that hardly means much to the layperson. The problem is not with the metric, but with the way it gets interpreted. The U-3 is widely understood to be a proxy measure and an incomplete picture, but it's useful because it is relatively easy to measure. As long as it is consistent, it can serve as a barometer even with known flaws. More here.
    • Consider the above-proffered definition: "the percentage of working-age adults looking for a full-time job that supports them without having to be on welfare." As far as statistics go, it's very difficult to work with because it cannot define cases at the margin clearly.
      • First problem: what does it mean for a job to be able to support someone? The conditions for triggering public assistance in various states and nations are quite different; many nations provide public assistance even to quite well-off individuals. An objective measure such as a set poverty line might help clean up that definition into something useful. Additionally, is unemployment insurance considered "Welfare?" (Legally, it's not.) Additionally, the problem of defining "have to be on welfare." If a person could make ends meet with their full-time job and a second part-time job, do they "have to be on welfare?" What if they simply sold a house they purchased that is above their means and moved into much less expensive accommodations?
      • Second problem: working-age adults who are out of the labor force would be counted in the above definition. That definition would considered disabled, ill, or the unemployable to be unemployed even if they cannot work, as long as they want to work.
      • Third problem: a problem which also plagues the U-3 (and is well-known) is the rate would not count working-age adults who simply have given up looking for work. This is really common during an economic downturn.
      • Fourth problem: an individual who does not need to be on public assistance, even if they are looking for a job, would not be counted as unemployed. Thus, the person who doesn't have to be on welfare because they have a wealthy family, royalties/a pension, Veteran's or other disability, or just have savings to live off of while they look for work would all fail to be counted. This is a large gap, as most upper-middle-class and above workers keep a savings fund capable of sustaining them for some time if they leave their current job.
      • Fifth problem: jobs held by non-working-age persons would not count. Thus, the 70-year old physician or lawyer who still hold a job would not be counted, nor would the 17-year-old military member.
      • Sixth problem: the offered definition completely ignores the realities of part-time employment, independent contracting, and the "gig economy," concentrating only on full-time work. Someone who makes a solid living as a carpenter, consultant, or other independent contractor would not be figured into employment statistics as they move from one job to the next.
      • Seventh problem: much like the U-3, it cannot count some forms of underemployment. If a cardiologist has to wait tables to make ends meet, they are significantly underemployed.
  • This is how Barack Obama came to be known as the President with the highest deportation of foreigners in the United States. The common definition of this would have people assume the number derives from "number of people who have entered the United States border and were then removed for any reason." However, the statistic also includes people who attempt to enter at border controls and are refused (technically, never entered the country). At land crossings, a person trying to enter the United States and is turned away, there is no mechanism to stop them from attempting again until they get into the country... and each one is counted as a separate "deportation" under-reporting metrics.
  • All the major types of car reliability statistics are likely to turn into that:
    • The owner survey, listing the car owners' voices on reliability, is prone to people not wanting to admit their vehicle is unreliable, or the opposite: owners unfairly bashing their cars.
    • The assistance statistics, listing how often a certain model requires roadside assistance, don't account for failures that don't immobilize the car.
    • The inspection survey, listing the percentage of cars of certain age failing their inspection or the number of failures the inspector noticed on an average example of the model, don't account for failures that do not impact the inspection's outcome. Also, expensive cars are more likely to score well, because their owners are more likely to have the money required to keep them in good condition between inspections.
  • Whenever people cite Chicago as being a Wretched Hive due to its high number of murders, they conveniently neglect to compare that number to the city's population of 2.7 million. Crime rates for a city are measured per 100,000 residents, and while there are definitely rough parts of Chicago where crime is a major problem, it is not the most violent city in the United States by a long shot. It's also worth mentioning that most violent crimes involve people who know each other: gang violence, domestic violence, drug deals gone south, etc. So even if you live in St. Louis, the actual murder capital of the US, the odds of being victimized are relatively low if you're not living that kind of life.
  • The vegan website Vegan Street claims there's more protein in 100 calories of broccoli (11.1 grams) than in 100 calories of beef (6.4 grams). While true, there are only 31 calories in a cup of broccoli, meaning you'd have to eat over three cups of broccoli to get those 11.1 grams. Conversely, three ounces of beef contains 25 grams of protein. Furthermore, not all proteins are the same; ones from most plants don't have as many of the amino acids the human body needs.
  • The Church of Scientology is unsurprisingly quite fond of this trope. The most common is exponentially overstating the number of Scientologists there are. The church often times cites membership statics based on the sale of relevant books, but there are several problems with this. Chiefly, most people who buy Dianetics don't go on to join the church, quite a lot of them are buying the book out of Bile Fascination, and of the actual Scientologists who buy the book, most buy multiple copies.
  • Back in 1985, there was a study performed that showed that a woman who was still single at age 40 had only a 2.6% chance of ever getting married. Newsweek even stated that such a woman had a better chance of getting killed by a terrorist. That study is now recognized as severely flawed, for multiple reasons. Although it did draw on US Census data from around that time, it narrowed the sample size far too much. It looked only at white, college-educated women born between the mid-1940s and mid-1950s who had never been married before, so out of 70,000 households, only about 1500 were part of the study. It also used a parametric model, which was meant for making sense of past events, not making predictions about future ones. And it did not take into consideration women who were cohabitating with partners (but not legally married); those women were counted as "single." It also didn't differentiate between those who wished to be married and those who were still single at 40 by choice (since the latter group would likely not be inclined to try for marriage after 40 either). There were also population conditions endemic to that particular generation, so even if that study had been accurate back in 1985 note , and it wasn't, that data would be obsolete now.
  • The idea that if a woman wishes to have a child, she has to do it by age 35 OR ELSE has been studied multiple times. Problem is, almost all of those studies are getting their data, not from a large and well-controlled sample of modern women, but census data about French peasants from The Middle Ages! Few have ever even thought to question that data, but it's problematic for several reasons. First (and most obviously), it comes from an era before germ theory, modern medicine, fertility treatments (such as IVF), hospital births, advances in agriculture and nutrition, the feminist movement, understanding of eggs and sperm, and so much more. Secondly, it only looked at census data, which doesn't explain why few of these women were having children after 35. Sure, it could reflect that women of that time and place were going through menopause or perimenopause sooner than women today do. But it could also reflect a number of other things as well: Maybe these women had fertility problems, to begin with, many of which are now treatable. Maybe, since these were peasant farmers, they weren't getting adequate nutrition for regular ovulation or healthy pregnancies. Maybe they were dying early of diseases such as The Black Death, or dying in childbirth. Maybe sex after a certain age, in that time and place, was seen as "unseemly." Maybe their husbands had gone off to war or had died of diseases/malnutrition/etc. Maybe these women, compared to their younger counterparts, were more likely to use whatever contraceptive methods were available (or abort). We just don't know. What we do know, however, is that more modern data suggests that the decline in a woman's fertility generally happens, not in her mid-30s, but her mid-40s. Also, that the risk of live birth with a birth defect does double: from 0.5% to 1%. So many women can (and do) become pregnant much later in life than we've been led to believe, either with or without fertility treatments.
  • The famous statistic that 50% of all US marriages end in divorce. This oft-cited stat came from The '70s and early 80's due to more and more states implementing "no-fault divorce" laws during that time note . This is in addition women gaining far more financial independence during the same time period and no longer being trapped in unhappy marriages. But since then, the divorce rate has actually been declining, as later generations feel less pressure to marry before 30 or due to an unplanned pregnancy, So if a couple does tie the knot, it's because they actually want to be together rather than outside coercion. The statistic is also artificially raised by people getting married multiple times. Someone who divorces and remarries is much more likely to divorce again than someone still on their first marriage, as any Hollywood tabloid can attest.
  • Often used in arguments over the American Civil War to "prove" that it couldn't be about slavery because such a small number of people had slaves (setting aside the fact that even if the small number were true, that conclusion would not follow, as most wars have been fought for the benefit of the ruling class, and the phrase "a rich man's war, and a poor man's fight" is sometimes attributed to a Confederate private). Some will try to claim a ridiculously small number of, say, 2%; that's just a straight-up falsehood. Others will get more creative, and that is where statistical manipulation comes in. They'll compare the number of individuals who own slaves in their own name to the population as a whole. Here's why that doesn't work: say a planter has a wife and three children. Of these 5 people, how many own slaves? By this measure, only one (20%), the planter himself, because all the property is in his name. In a more honest calculation that looks only at households, the number of slaveowners jumps up to around 30%, and even that underestimates the economic impact of the institution, i.e., people connected to or who make use of slave labor without necessarily owning any themselves. For example: overseers, partners, and employees in corporations that owned slaves (fairly common in transportation and the building trades), the fact that slaves could be rented, etc. Sometimes, a different claim is made to back up the same line: that a slave was a very valuable commodity, often literally compared to a Cadillac or sports car, and thus could only be owned by the ultra-rich. And that's true...of a prime field hand. The fact that most slaves would not qualify as such is ignored; this is the equivalent of claiming that only the ultra-rich can own cars.
  • The idea that the average lifespan prior to the Industrial Revolution was only about 35 years. In actuality, plenty of people lived to be well into their 70's and older at that time, even without modern medicine. The reason the "average" lifespan was so low was because of high infant mortality. At that time, babies and children had a very high chance of dying before age 5 from disease or malnutrition. But if a child made it to puberty, they had a fairly good chance of making it to old age.
  • You may hear a statistic that "One in every _____ women/men will have X cancer". Usually, this is done to promote screenings for said cancer, or as part of "awareness" campaigns. What's usually not said is that this number includes all the diagnoses in that demographic, whether they survive or not, though it's often phrased as how many patients will die from that cancer.
  • There's also the "survival rate." As xkcd explains, sometimes a cancer cell or two or three will slip past whatever treatment(s) are given (e.g. chemotherapy, radiation, immunotherapy, whatever), or actually be resistant to it. Which means it may come back, or the tumor may metastasize (that is, pop up elsewhere in the body). The X-year survival rate actually refers to how many years you go without this happening. (For example, if your five-year survival rate is 60%, that means there's a 60% chance your tumor won't come back or metastasize within 5 years...but there's a 40% chance that it will.)
  • Another common tactic is to try and quantify things that aren't quantifiable. For example, a shocking amount of graphs use "gun control" as an axis point. Gun regulations are laws and it's impossible to turn into numbers. Which is why the results of these graphs change so much depending on who makes them. Even trying to compare on countries regulations as "more strict" than another is a bit difficult given the idiosyncrasies of law.
  • One common way of making changes in numbers (say, a change in graduation rates for high school students) look worse or better, depending on the goal, is to compare the numbers in question directly without placing those numbers in context. For example, if 99 out of 100 students graduate and one drops out, and the next year 98 graduate and two drop out, while it's technically correct to say the dropout rate has doubled or increased by 100%, it's also misleading. Similarly, if you have a poor educational system where only 25 out of 100 eighteen years old have a high school diploma, and raise that to 30 out of 100, while you have increased the number of graduates by 25%, in context your graduation rate is still abysmal.
    • This is also seen in reporting about almost anything that is, in context, a very small number. If, for instance, in the average year, old three people in the United States come down with a rare illness, a 33% jump in still a really, really small number of people.
  • If you look at a map of the United States where all counties are colored based on who they voted for president, using the standard red for Republicans and blue for Democrats, the map will often be heavily red. Many Republicans will use this as proof that they speak for the American people and that a handful of urban areas, which usually vote Democrat, shouldn't solely control the nation's leadership. One small problem: corn and cattle don't get a vote. Most solid red regions are rural and sparsely-populated; it may look impressive that all of West Virginia voted for Donald Trump in 2020, until you realize the entire state has fewer people than Brooklyn. A more accurate election map will only color population centers and not empty land, in which case the red and blue will be a lot more evenly matched.
  • An interesting way to skew results in your favor is to obviously make the poll biased. Most people will then vote against where they are being led either to prove that they are above control or just to spite the pollsters. The pollsters, who really are for the opposite of what they presented themselves, can then say "look people still agree with us, even when the polls are biased against us."
    • People wanting to screw pollsters has an interesting effect on statistics. A common example used to demonstrate this in statistics class are maps where a certain group of people were asked to find a certain country on the map. Ten to Twenty percent will point to somewhere in the middle of the ocean. Teachers point out that while it's possible for people to be that stupid, it's far more likely that was their idea of a joke.
  • Many studies have shown that men are more likely to develop sexual fetishes than women, and no one really knows why. However, most studies involving human sexuality rely on self-reporting, and it's possible that men are more likely to be honest about their kinks and explore them more actively, whereas a woman might downplay hers, due to society being more encouraging of men being openly sexual while shaming women for the same thing. The same thing applies to number of sexual partners; when men and women self-report on them, it's a common adage to either divide the number by 3 or multiply by 3 depending on whether it's a man or a woman making the claim.
  • Vladimir Lenin used a form of this in his propaganda book Imperialism, written to bolster Karl Marx's work for the 20th century after 70-odd years of contrary evidence to his prediction of "hypercapitalism", by suggesting that western capitalist economies had staved off inevitable collapse due to exporting surplus capital to their colonies, therefore making the "class struggle" global. As Thomas Sowell pointed out, aside from Lenin not citing his sources, the categories he used to illustrate his argument ("Europe", "Africa-Asia-Oceania", and "Americas") lumped together so many disparate economies under the same rubric that the data was completely useless at proving anything. In reality, the industrialized economies primarily invested in each other, not their colonies, which only further dismantles communist theory of an ever-increasing capital concentration leading to revolution.
  • The Soviet Union was infamous for overstating their accomplishments by running figures through arbitrary multipliers and claiming that is simply how Marxist-Leninist economics worked. Some of the more infamous examples:
    • The Soviets would add the value of components to finished products, and then the finished products themselves, to their GDP. Normally everybody only tabulates the finished product, but a screw driver made in the Soviet Union would have the handle, the shaft, and the screwdriver itself counted toward the Soviet GDP.
    • The exchange rate between the Rubel foreign currencies was eventually completely arbitrary, again making the economy look stronger than it was. For decades, the exchange rate of dollars to rubles was 3.75 dollars to the Rubel. This figure did not change despite the dollar experiencing inflation and the Rubel officially not. In reality a single dollar often went for more than eleven rubles on the black market, and in terms of comparative purchasing power in their native markets, the dollar was usually somewhat stronger, but not nearly so much as the black market price.
    • They would often inflated production numbers by listing product that had been stolen, spoiled, gone deflective, or never existed. Which backfired tremendously on the Soviets. It turns out the workers effectively did the same thing as the government by cheating on their own production numbers, thus meaning the government had to pay for material that was either bad, stolen, or never existed at all. The most famous incident was the Uzbikistani "Great Cotton Scandal," which revealed that essentially the entire Uzbek Socialist Republic was in on scamming the central govenment into paying for fictional cotton.
  • The old adage that you should drink eight glasses of water per day is misleading. The reality is that a healthy adult should consume a total of about 64 ounces or two liters of water in a day, but this includes the moisture in the foods you eat; you don't have to chug away. In fact, if you're eating three square meals each day, you can survive without drinking any additional water. It's not recommended (unless you're a desert tortoise), but you won't die.
  • In 2019, a study was publicized by the media for how many shootings had occurred in a matter of months in the United States to demonstrate a problem with gun culture. When you read the study, they state that they defined a shooting as any event where a firearm was reported even if it was not used, anyone was injured/killed, or was even present at all. Another study reporting the number of children killed by guns in the home defined a child as a dependent under the age of 25.
  • Sometimes smaller countries will compare negative statistics, like crime rates, directly to larger countries. Without dividing by population, this will invariably make the smaller country look better. This is why serious studies use "per capita" rather than absolute statistics.
  • Cases where a population that's a minority within a country is vastly overrepresented in its prison system. Depending on one's world view, they can be used to back an existing belief that members of the minority are inherently more prone to committing crimes, that members of the minority are more likely to find themselves in circumstances in which they are driven to crime to survive or that the justice system is being much harder on members of the minority than on those of populations that are underrepresented in the prison system. Multivariate analyses of such trends are rarely forwarded because they do not fit any side's particular narrative.
  • In an open letter to left leaning parties, Tony Blair noted how such parties often convince themselves that victory is assured because some of their flagship issues poll well. Essentially, just because, for example, spending more money on the NHS, repairing roads, and aid to the homeless all poll at sixty percent, doesn't necessarily mean it's the same sixty percent of the populace. After that, a specified proposal to solve an issue has less support than simply solving the issue. Then there are voters who will be turned away by your party's general attitudes about society and even more when a face is finally put to all these ideas. Yet every major left-leaning party seems to be shocked when they lose because they convince themselves their candidates are wildly popular just because the voter base broadly agrees with them on some of the issues.
  • Inverted when Darrell Huff was hired by the tobacco industry to apply How To Lie With Statistics to the stats showing pretty clearly that smoking causes cancer.

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Alternative Title(s): Lying With Statistics, Lies Damn Lies And Statistics