Correlation Arguments                                                                        (Problems printing? Click here.)

Causal Claims

Causality is basically a relationship between one object or event and another object or event. If we were to say that A causes B, we would mean that there is a relationship between A and B such that whenever A occurs, we should expect B to occur also. Causal claims are therefore conditional predictions. They are predictions about what will happen next IF something else has just happened. Causal arguments are therefore attempts to get people to believe in these predictions. Causal arguments cannot prove that anything other than a relationship exists. No causal argument can prove that A exists or that B exists. For this reason, causal arguments can only establish relationships between known entities. If we don't already know that A exists and that B exists, we cannot make a causal argument about A and B. (We will cover arguments that prove things exist in a later chapter.)

Here are some causal claims.

a. Tobacco consumption, whether chewing or smoking, causes cancer.
b. Abolition of the fairness rule caused and continues to cause the American population to become more and more conservative.
c. The way America administers welfare tends to keep people on welfare even when they would like to become independent.
d. Moderate drinking is actually better for you than not drinking at all.
e. Rain causes accidents in Southern California
f. Rain causes more accidents when it comes after sunny days than it does after rainy days.

Notice that none of the above statements are arguments. Arguments come with supporting reasons, which are not present in any of the above sentences. Thus, while some of the claims given above may seem plausible to you, none of them as yet come with any reason for you to believe them. This means that if you believe any of these claims you are either taking my word for it (which you shouldn't do) or you are believing on the basis of a feeling, (which you definitely should not do!)

Similarly, neither of the following more elaborate claims is an argument.

g. Car accidents are mostly caused by accident goblins, who are surrounded by a magic aura that causes drivers to loose control of their vehicles. Accident goblins don't like hot concrete or asphalt, but they love to dance in the rain, so when it rains in Southern California, the accident goblins all come out to dance in the rain. This means that on rainy days there are far more accident goblins on the roads than usual, so of course the accident rate goes up.

h. The increase in accidents on rainy days is caused by Hydrogenic Ion Depeletion. The speed and level of electrochemical activity in the brain is influenced by the availability of positive ions in the bloodstream to act as "electron sinks" facillitating axon recovery after nerve impulse propagation. (This is the time an axon takes to get ready to carry the next nerve impulse.) The main source of positive ions for this purpose is atmospheric oxygen and nitrogen ions, which enter the bloodstream through the lungs along with the far more plentiful non-ionic oxygen. Free ions are very susceptible to surface effects, and are attracted to the surfaces of raindrops as they fall. This depletes the atmosphere of positive ions because it removes them from the air faster than new ones can be made by sunlight. Although this condition is not dangerous for animal life, it does result in a small but measurable slowing of brain activity, with a concomittant degradation of judgement and increase in reaction times.

The reason that I don't consider either of these statements to be arguments is that neither of them comes with any reason to believe in any part of the story. No evidence is given to support the existence of accident goblins or hydrogenic ion depletion. Rather, the claim is just elaborated with the addition of details, but details are not evidence. It's true that one or other of these explanations may feel plausible because it feels like the kind of explanation you're used to, but a feeling is no reason to believe something.

Correlations

A "correlation" is a relationship between two kinds of event. If two types of thing teend to occur together, they are correlated. For instance, in most public places, clothes and people are correlated. At public parks, for instance, we rarely see clothes without people, or vice versa. A causal claim is basically a claim that, whether or not two types of event were correlated in the past, they will be correlated in the future.  The following are all examples of claims about correlations.

i. Groups composed entirely of smokers have been found to contain more cancer cases than groups of nonsmokers.
j. After the abolition of the fairness rule, the American population began a slow but stready and continuous drift to the right.
k. People who try to get off welfare in America succeed less often than people who try to get off welfare in European countries.
l. Moderate drinkers are healthier than nondrinkers.
m. The accident rate always goes up whenever it rains in Southern California
n. The first day of rain after a dry spell always has more accidents than later rainy days. This difference is more pronounced when rain follows a _long_ dry spell.

The following are claims that do not involve correlations.

o. Tobacco is harvested in late June, early July, which means that the astrological sign of all cigarettes is Cancer.
p. The Fairness Doctrine was abolished by Ronald Reagan, a far right wing President.
q. Welfare officials like their jobs, and make more money when there's more people on welfare.
r. Nondrinkers deprive themselves of the pleasures of intoxication, noncoordination, somnambulation and regurgitation.
s. I aquaplaned once. Woooooooo! It was fun.
t. If I was an accident goblin I'd get the hell off the roads when the accidents start happening.

Now there's two things I want you to think about here. The first thing is that in every one of the first group of statements there's one type of thing whose presence (or absence) seems to vary with the presence (or absence) of another kind of thing. The second thing to think about is to ask yourself whether any of the second group of statements gives any logical reason to believe any of the causal claims

Exercise 1. If  any of the claims ("o" through "t") made immediately above were true, would any of them logically support any of the causal claims ("a" through "f" made at the top of this chapter?

Causal claims can only be justified on the basis of established correlations. It is often said that "correlation does not prove causation." This is completely and utterly false. Correlation is the only thing that ever proves causation. It's true that not every correlation proves causation, but every causal relationship that has ever been proved, has been proved on the basis of a correlation . (Thus the claim that "correlation does not prove causation" is logically analogous to the claim that "evidence does not prove guilt" in a court of law.) The trick here is to figure out which correlations prove causation, and which don't.

For an illustration of this idea, see this cartoon

But also read about some clearly spurious correlations www.tylervigen.com/spurious-correlations, Why do we think that these correlations don't imply causality?

A correlation argument is an argument that attempts to establish a causal relationship by pointing to a particular kind of correlation that is claimed to exist between two types of event. For instance, the following are all correlation arguments.

aa. Groups composed entirely of smokers have been found to contain more cancer cases than groups of nonsmokers, so tobacco consumption, whether chewing or smoking, causes cancer.
ab. Abolition of the fairness rule caused and continues to cause the American population to become more and more conservative. We know this because, after the abolition of the fairness rule, the American population began a slow but stready and continuous drift to the right.
ac. People who try to get off welfare in America succeed less often than people who try to get off welfare in European countries, from this it follows that the way America administers welfare tends to keep people on welfare even when they would like to become independent.
ad. Moderate drinkers are healthier than nondrinkers, so moderate drinking is actually better for you than not drinking at all.
ae. Rain causes accidents in Southern California, because the accident rate always goes up whenever it rains in Southern California.
af. The first day of rain after a dry spell always has more accidents than later rainy days. This difference is more pronounced when rain follows a _long_ dry spell, so rain causes more accidents when it comes after sunny days than it does after rainy days.

But these arguments are definitely not correlation arguments:

ag. Tobacco consumption, whether chewing or smoking, causes cancer, because tobacco is harvested in late June, early July, which means that the astrological sign of all cigarettes is Cancer.
ah. The Fairness Doctrine was abolished by Ronald Reagan, a far right wing President, so abolition of the fairness rule caused and continues to cause the American population to become more and more conservative.
ai. The way America administers welfare tends to keep people on welfare even when they would like to become independent, because welfare officials like their jobs, and make more money when there's more people on welfare.
aj. Moderate drinking is actually better for you than not drinking at all. This follows from the fact that nondrinkers deprive themselves of the pleasures of intoxication, noncoordination, somnambulation and regurgitation.
ak. I aquaplaned once. Woooooooo! It was fun, so rain causes accidents in Southern California
al. Rain causes more accidents when it comes after sunny days than it does after rainy days, I know this is true because if I was an accident goblin I'd get the hell off the roads when the accidents start happening.

Exercise 2. One of the following is a correlation argument. The other isn't. Say which is which and explain why.

A. We compared 100 random moderate drinkers to 100 random nondrinkers, and found that the moderate drinkers were healthier than nondrinkers, so moderate drinking is good for you.
B. Moderate drinking is better for you than nondrinking because "teetotaling" sounds like "teetertottering," and that can't be good.


Some Points About Causal Reasoning.

"Causal" reasoning is reasoning about cause-and-effect relationships. Correlation arguments do not support claims about the existence or non-existance of objects, nor about the occurance or non-occurance of events. They just support claims about causal relationships. Thus no correlation argument would support a claim that tile roofs exist, nor would any causal argument support a claim that baldness happens. But if someone wanted to support a claim that tile roofs cause baldness, well, then, that claim would have to be backed up by a correlation argument. (Notice that a causal claim is just a claim that A causes B. It is not a claim that anyone knows how A causes B.)

Causal relationships are usually not one-to-one relationships. Causes can have multiple effects, and effects can have multiple causes. Cigarette smoking does not cause cancer, emphysema or heart attack in everyone who smokes cigarettes. But we can bet that a group of a thousand people who smoke heavily we will see more cases of cancer, emphysema and heart attack than in a demographically identical group of a thousand nonsmokers. And ciggies are not the only things that cause cancer, emphysema and heart attack. So a cause is something that makes the effect more likely to happen but usually does not guarantee that the effect will happen.

It is important to remember that causal arguments do not have to come with explanations. When smoking was established as a cause of cancer, nobody had any idea how smoking managed to cause cancer. Nevertheless, the strong correlation between smoking cigarettes and getting cancer convinced reasonable people that a causal link existed. It didn't matter that nobody had any idea how smoking did it, all that mattered was that the correlation between cigarettes and cancer was so strong that no other explanation made sense. All that is necessary to establish a causal link is that a strong correlation be established. Explanations are immaterial to this correlation, so the lack of an explanation is never a weakness in a causal argument.

The way to evaluate a causal argument is to ask whether the known correlation is strong enough to justify the causal claim and, if it is, to then ask if all other causal possibilities have been eliminated. If it is, and they have, then your argument is good. If it isn't, or they haven't, then the argument sucks. While an argument that tile roofs cause baldness would have to start with some correlation between tile roofs and baldness, it wouldn't get very far unless it included reasons to eliminate all other possible causes of baldness, like, for instance, salsa music. (We wouldn't have to eliminate UFOs however. The fact that something has never been proved to exist is generally enough to remove it from consideration when we're talking causes.)

If somebody were to say that we should abolish tile roofs because they cause baldness we would evaluate his "causal claim" by asking him to give evidence of a correlation between baldness and tile roofs. If it turned out that men started losing their hair the moment they went under a tile roof, and that men who never lived under tile roofs never went bald, then we would have a strong correlation, and good reason to think that tile roofs cause baldness. If it turned out that men went bald or not independently of whether or not they lived under a tile roof, then we would have no correlation, and no reason to think that tile roofs cause baldness. So a causal argument that comes without at least some evidence of a correlation is always a bad argument.

Exercise 3. Answer the following questions, and explain your answers.
i. Are causal arguments required to explain how the purported cause causes the effect?
ii. Are causal arguments required to show that the purported cause is the only thing that ever causes the effect?
iii. Are causal arguments required to show that the purported cause absolutely always causes the effect?
iv. Can a causal argument succeed without showing that the purported cause is at least sometimes correlated with the effect?
v. Can a causal argument be based on a "cause" that hasn't been previously proved to exist?

Anecdotal Evidence

An "anecdote" is a little story about some event that supposedly happened at some time to some person. The kind of anecdote we're concerned with here is an anecdote that says one thing happend at the same time as another time, or that a certain type of thing tends to happen after a certain other type of thing. Anecdotes generally concern unusual events and unexpected correlations (that's what makes them interesting), and they can be valuable in suggesting lines of research, but they can never prove causal claims all by themselves.

Before 1910, lung cancer was virtually unknown. A single case of lung cancer would be news in the medical community, and a doctor who saw a case would want to talk about it. Starting about 1918, doctors in industrialized countries began seeing, and talking about, the surprisingly new high rate of lung cancers they were starting to see. Some of these doctors also noted that, almost entirely without exception, the people who had these cases of lung cancer were smokers. For non-smokers, the rate of lung cancers remained almost vanishingly low. A non-smoker who got lung cancer was still a very, very rare thing. These facts, reported informally by doctors in letters to medical journals and by word of mouth, strongly suggested that smoking causes lung cancer. But they didn't prove it.

There are several reasons why we cannot take anecdotes, even a large number of anecdotes, as proving anything. For one thing, ill-intentioned people often make stuff up to discredit people of groups they don't like. Other times, people invent explanations for events and then pass these invented explanations off as fact. Anecdotes can also arise simply from mistakes. People are generally not good reporters of their observations, and will often report distorted versions of what they themselves saw. Also, anecdotal reporting is uncontrolled. If we hear ten reports of a smoker getting cancer, we have to determine whether these ten stories concern ten different smokers, or just one smoker whose story was heard by ten different people, each of whom then told the story to us. Even when the anecdotal evidence is of high quality, as when trained professionals, such as doctors, carefully report cases that are clearly distinct from each other, we still have to be careful, as there is the possiblity of error or unknown common cause.

Thus, anecdotal evidence can be invaluable in telling us what to think about and where to spend our research dollars, but it cannot prove anything directly.

Smoking and Lung Cancer

Mill's Methods

John Stuart Mill figured out five different ways to support a causal connection, depending on what kind of evidence you have. (These methods may turn out to be "just common sense.") I've noticed that students often have a hard time understanding explanations of Mill's methods. However, when I give those students exercises designed to test their ability to apply Mill's methods, they find those exercises ludicrously easy. This suggests that what I grandly describe as "Mill's Methods" can be figured out by community college students with no previous training in those methods. So, if you don't understand these explanations, don't worry about it. You will probably be able to do the exercises anyway.

First, some terminology. A positive correlation is when two things tend to happen together. Tile roofs and baldness are positively correlated if it is the case that tile roofs tend to show up every time baldness occurs, and vice versa. It's when two things tend to be absent at the same time. Tile roofs and baldness are positively correlated if it is the case that tile roofs tend to be absent every time baldness is also absent, and vice versa. (I'm not sure those "vice versas"

A negative correlation is where occurances of one thing are correlated with non-occurrences of another thing.

Mill's method of agreement relies on positive correlations. It basically says rule out everything that is not necessary to bring about the effect, and what is left over is more likely to be the cause. Say we have a population of one thousand bald men and the only thing all of them have in common is that each of them spends long periods of time under a tile roof. If this were true, then anything else that was offered as a candidate for the cause could be eliminated by pointing out that somebody got bald without being exposed to that thing. Since tile roof is the only thing that cannot be so eliminated, we have good reason to think that tile roof is the cause.

Mill's method of difference says rule out everything that is not sufficient to bring about the effect. Say we have a population of one thousand hairy men and one bald man who lives apart from them under a tile roof. The only thing the hairy men all have in common is that none of them lives under a tile roof. In this case any other causal candidate could be eliminated by pointing out that somebody was exposed to that thing without getting bald. Since tile roof is the only thing that cannot be ruled out that way, we have good reason to think the tile roof is the cause of the baldness.

Mill's "joint method" just means applying both methods together to the same data set. If two things are both positively and negatively correlated, then that could be strong evidence that one of them causes the other.

Mill method of concomitant variation says look for something that varies in proportion to the effect. Say that Al has lived under tile for 7 years and is 10% bald, Ben has lived under tile for 14 years and is 20% bald, Cal lived under tile for 21 years and is 30% bald, Don has lived under tile 28 years for 40% baldness, Ed has 35 years and 50%, Finn 42 years and 60%, Greg 49 years and 70%, Hal 56 years and 80%, Ian 63 years and 90% while Jack has spent seventy years living under a tile roof and is completely bald. Since the amount of baldness goes up and down with the time of residence under tile, and if nothing else correlates in this way, this would give us good reason to think that living under a tile roof causes baldness. Remember that the corespondance doesn't have to be one to one. It can be any ratio at all, just as long as that ratio is constant across instances.

Mill's method of residuals is a way of figuring out how much of some effect can be attributed to some particular cause. Say that we know that polka music causes baldness in 4 percent of listeners, plaid shirts cause baldness in 8 percent of wearers, and that jumping jacks cause baldness in 16 percent of jumpers. And say that we know that these are the only causes of baldness apart from tile roofs. Finally say that we know that yesterday one million men wore plaid shirts to do jumping jacks to polka music under a tile roof, and 40 percent of them became bald. Ignoring the tile, we can account for no more than 32 percent of these baldnesses, (4+8+16=28), so being under a tile roof must cause baldness in at least 12 percent (40-28=12) of men.

Now apply Mill's methods to the following problems, and then evaluate the arguments that follow the problems. See if you think the person making a causal argument in each dialog is correctly applying Mill's methods.

Several patients at Chicago Soap Hospital are experiencing bizarre drug side effects. The hospital administrator, Dr. Whatmeworry, is going crazy, and has hired several people to figure out what is going on. Unfortunately, none of them seem to know what they're doing. Your job is to sort through the arguments and figure out who, if anyone, knows what he's talking about. (To make this easier, assume that only one drug is causing each effect, and that clinical trials were not done.)

Some patients in Ward 1 are turning into fairies and have turned several doctors into animals. The patients who are growing gossamer wings and buying pixie hats are on Unicorp, Verlag, Xindeco and Zydigm. Those who are merely looking on in horror are on Verlag, Zydigm and Unicorp.

The patients in Ward 2 have all acquired the ability to shoot low energy laser beams from their eyeballs, which they use to irritate their nurses, warm beverages and vaporize insects. Patient Abel is on Terraplex, Omniken, Shegos and Permax. Patient Baker is on Omniken, Shegos and Terraplex. Patient Cooper is on Terraplex, Shegos and Permax. Patient Dasia is on Shegos, Omniken and Permax.

Ward 3 Patients are channeling famous generals of the past. They are now in great demand by TV networks as commentators on various wars. The camera crews are disrupting hospital operations, and one patient is faking symptoms (pretending to channel Buffy the Vampire Slayer) in order to get on The McLaughlin Group. Patient Killian is channeling Caesar and Napoleon. She is on Invap 40mg, Kolvox 100mg, Minafax 300mg, and Nasdaq 1mg. Patient Lomax is channeling Rommel, Wellington, Alexander and Sun-Tzu and she is on Invap 10mg, Kolvox 200mg, Minafax 600mg and Nasdaq 2mg. Patient Miles is just channeling Vinegar Joe Stilwell and she is on Invap 30mg, Kolvox 50mg, Minafax 900mg and Nasdaq 1mg. Finally, Patient North is channeling Grant, Zhukov and Sharon. She is on Invap 20mg, Kolvox 150mg, Minafax 600mg and Nasdaq 4mg.

Some patients in Ward 4 are growing extra limbs, which are presenting interesting possibilities for getting around the ward and possible future sporting events. Patient Eggar is growing an extra left foot from his right elbow, and is on Quindor, Dynastar, Comdex and Gennum. Patient Harris has no extra limbs, and is on Dynastar, Fitel and Gennum. Patient Frank amuses children with the extra arm growing out of his left kneecap, and is on Comdex, Dynastar, Fitel, Quindor, and Gennum. Patient Irvin is perfectly normal and on Fitel, Gennum and Comdex. Patient Gregg makes interesting gestures with the extra hand that has grown out of where his nose used to be. He is on Quindor, Comdex, Fitel and Dynastar. Patient Jakes has two arms growing from his tailbone, and can give himself a back massage. He is on Fitel, Gennum and Comdex.

Now, there's two ways you can approach the following exercises. First, you could start by ignoring the given arguments and apply Mill's Method's yourself before comparing your answers to those given in the dialog analysis exercises. (This means doing exercises 8 through 11 before exercises 4 through 7.) Or, you could do the dialog analysis first and Mill's methods after.

Dialog Analysis Exercises.

Find the weaker argument in each pair, and then explain in your own words why it is weak.

4.size="12" face="Arial">Daryl. Don't take Zydigm! All of the people who turned into fairies took Zydigm, so it must be the cause!
Gwendolyn. Not everybody who took Zydigm turned into a fairy, so it might not be the cause.

5.size="12" face="Arial">Aliya. The drug that gives people the ability to shoot laser beams from their eyes must be Terraplex. Able, Baker and Cooper all took Terraplex, and they all got laser vision.
Karson. Yeah, but Dasia got laser eyes too, and she didn't take Terraplex.

6.size="12" face="Arial">Gianni. The drug that lets you channel famous generals must be Nasdaq. Miles took 1 milligram of Nasdaq and channeled just one general, that's a 1-to-1 correlation, so Nasdaq must be the drug.
Susana. But Killian also took 1 milligram of Nasdaq, and she channeled 2 generals. Lomax took two milligrams, but she channeled four generals! Neither of those is a 1-to-1 correlation, so Nasdaq probably isn't the drug. And anyway, it doesn't have to be one unit of the drug to one general. We have to look for a situation where the number of generals goes up and down in exactly the same way that the dosage of the drug goes up and down.

7.size="12" face="Arial">Zoie. Dynastar must be the drug that is causing the extra limbs. Eggar, Frank and Gregg all took Dynastar and all grew extra limbs.
Tristian. But Harris also took Dynastar and didn't grow any extra limbs, and Jakes grew extra limbs without taking Dynastar.

Mill's Method Exercises

8. What is most likely causing the fairification in ward 1, and which of Mill's methods is appropriate here?

9. What is most likely causing people to get laser eye in ward 2, and which of Mill's methods is appropriate here?

10. What is most likely causing the general disorder in ward 3, and which of Mill's methods is appropriate here?

11.What is most likely causing the limbular proliferation in ward 4, and which of Mill's methods is appropriate here?


Direct and Counter Arguments in Causal Reasoning.

You will remember from the last chapter that a counter argument says something explicitly about the logic of another argument, whereas a direct argument gives independent reasons for believing some particular conclusion. When a direct argument is opposed by a counter argument, the counter argument gives a reason to think that the direct argument hasn't proved it's conclusion, but does not give us any reason to believe any other conclusion.

A. Tobacco consumption, whether chewing or smoking, causes cancer, because tobacco is harvested in late June, early July, which means that the astrological sign of all cigarettes is Cancer.
B. In astrology "cancer" is just the name of "the crab," which refers to a certain portion of the sky. It has nothing to do with the disease called "cancer."

Notice that argument B, while it kicks argument A right in the head, does not give us any reason to think that tobacco doesn't cause cancer. Now, when a direct argument is opposed by another direct argument, the second argument gives us a reason to think that a different conclusion is true, but it doesn't give us any reason to think there's anything wrong with the first argument. So argument B is a direct argument.

A. Moderate drinkers are healthier than nondrinkers, so moderate drinking is actually better for you than not drinking at all.
B. People who drink ten or more drinks every day tend to have a wide variety of serious health problems, so it follows that moderate drinking will cause moderate health problems.

Notice that, again, the second argument in this pair doesn't give us any reason to think that there's anything at all wrong with the first argument. It says absolutely nothing about the logic used in argument A, and so gives us no reason to think that that logic is bad. So it's a direct argument.

A. Abolition of the fairness rule caused and continues to cause the American population to become more and more conservative. We know this because, after the abolition of the fairness rule, the American population began a slow but stready and continuous drift to the right.
B. Okay, abolishing the fairness rule might have caused the rightward drift, but you haven't eliminated other possible causes, such as wars, terrorism, scaremongering by politicians, or even just aging in the population. Untill you've looked at and accounted for all other possible causes, you're just not going to have a credible argument here.

Argument A refers to a strong correlation: As long as the fairness rule has been absent, the country has been drifing to the right. Argument B doesn't challenge that data, but points out that there may be other causes for the rightward drift. (As in the Ferlinghetti example given below.) This is getting into the nuts-and-bolts of argument A, and means that argument B is a counter argument. Also notice that argument B does not support the idea that abolishing the fairness rule didn't cause the rightward drift, it just supports the idea that argument A fails to prove that it did.

Exercises

For each of the following dialogs, figure out if the second argument is a direct argument or a counter argument.

12. A. Moderate drinkers are healthier than nondrinkers, so moderate drinking is actually better for you than not drinking at all.
B. Now, that implies that a nondrinker who started drinking moderately would experience an improvement in health, even if he made no other changes. But have you thought about the possibility that moderate drinking might be associated with a desire to enjoy life? If moderate drinkers tended to be happy people with active lifestyles who just had drinks when they socialized, and nondrinkers tended to be depressed, sedentary people who didn't socialize, that might account for the difference without any beenficial effects from the alcohol.

13.  A. Rain causes accidents in Southern California, because Caltrans figures show that the accident rate always goes up whenever it rains in Southern California.
B. That can't be true. I have statistics here from the National Association of Slip-And-Sliding Rain Dancers, and their records show no increase in the accident rate when it rains.

14.  A. Rain causes accidents in Southern California, because I always see many more smashed cars on the side of the road immediately after it has rained Southern California.
B. But Southern California is also very smoggy. Smog obscures vision, and rain washes smog out of the air, making it easier to see things. Which means it's possible that there's just as many accidents when it's dry, but you just don't see them because they're hidden by the smog.


Evaluating Causal Arguments

To evaluate a causal argument you must figure out two things. First, you must figure out whether the causal claim offered is a good explanation for the observed correlation. Second, you must figure out whether or not there is any other reasonable explanation for that correlation. If it turns out that the offered causal claim really isn't a good explanation for all of the observed facts, then the argument is no good. If it turns out that some other explanation for the observed facts is just as good an explanation as the causal claim, then the argument is no good.

Since basically any bad causal argument can be called a "false cause" fallacy, I'm going to continue my discussion of bad causal arguments under that heading.

False Cause

The classic False Cause fallacy assumes a causal connection based on a trivial correlation.

Interviewer. "Coach, can you tell me why the fans are tossing cans of beans on to the field?
Coach. "Well, we haven't done well this season. We only beat Milwaukee, Dallas and Fargo. Just before that Milwaukee game I was embarrassed by a noisy attack of flatulence. Then, as I was psyching the team up for the Dallas game..."
Interviewer. "That was you? I thought it was a low-flying jet!"
Coach. "No that was me..."
Interviewer. "And the cheerleaders who fainted before the Fargo game?"
Coach. "Me again, I'm afraid."
Interviewer. "And so the beans..."
Coach. "If you'll excuse me, I think I can choke down another can.

I love your sister, but every time she comes to California we have an earthquake. So we can't invite her again until I've finished earthquake-proofing my collection of decorative plates.

Just because something is the only cause you can think of doesn't mean it has any causal relationship to the effect.

Pete: Since 1985, the average SAT scores of the incoming freshmen at Miskatonic University have consistently been about 10% better than they were before 1985. Nothing important changed in or around 1985. In fact, we've checked all the things that the schools could be doing that could possibly cause a rise in SAT scores, and we found that none of them changed significantly, so it isn't due to anything that local educators are doing.
Ona: Have you forgotten that I‘ve been teaching at Miskatonic since 1985. Obviously, that's the reason.
Pete: How do you figure that?
Ona: Well, duh, before I got here, the scores were bad. After I got here, the scores got better.

Sometimes people commit false cause when they get confused about causal relationships. People often assume that one thing causes (or must cause) another thing merely because the two things are strongly associated in their minds. But a mental association is a far cry from a causal relationship.


Ignoring Possible Alternative Cause.

One way to look at causal arguments is to see them as claiming that the only way to explain the frequency of a certain event is to assume that it is caused by some particular other kind of event. This means that whenever there's something else that's equally well correlated with the effect, it follows that that something else could just as easily have been what caused the effect, and so the argument fails to prove the causal conclusion it was intended to prove.

Causal reasoning requires careful attention to detail, and a willingness to follow the evidence wherever it actually leads. Consider the following problem.

Exercise 15 The village of Ferlinghetti has been famous for its locally produced mineral water for about 150 years. However, the village also has a problem with adult asthma. Many of the town's adults spend much of their time coughing and wheezing. Locals believe that the mineral water reduces or prevents the asthma and have been drinking more and more of it since the asthma problem was first identified in 1852. The asthma problem has grown slowly but steadily worse, with no interruptions, since the early 1850s. Asthma attacks do not get any worse or any better at any particular time of day or time of year. The leading citizens in the town have identified four possible causes of the asthma. A tin mine in the mountains produces runoff, which runs into the local river, from which the town draws all its drinking water. (Fortunately, the mineral water comes from a deep mountain spring that is not at all affected by the runoff.) A perfume factory in the next valley produces fumes, which drift over to Ferlinghetti. Farmers in the nearby plain use a special kind of wheat, which releases pollen that is carried into Ferlinghetti by the prevailing winds. Bats from the local woods fly into the town at night to feed on insects, and leave fur and skin flakes that hang in the air for about an hour after they fly through. The tin mine has been in continuous operation at the same level of production since Roman times. The perfume factory was built in 1843, but was completely shut down for both world war one and world war two. The special wheat was introduced in 1840. The local species of bat was discovered and classified in 1845 when local kids found caves containing both the bats and accumulations of bat droppings that proved to be dozens of feet thick. You are a scientist called in to investigate the situation and discover the cause of the asthma problem.

size="12" face="Arial">The town mayor argues, "it's the tin mine in the mountains, because that runoff water does get into the local drinking water. It must have started running off in 1852 and the amount of water running off must have gotten larger and larger since then."

The chief of police claims that "the perfume factory has to be the cause. There must be something in the perfume fumes that causes asthma, and they must have been using it continuously since 1852."

The town drunk confides in you that "the wheat must be the cause. They've been growing it continuously since at least 1852, so it's perfectly well correlated."

And the town librarian says "it's the bats! Aaaaaaaaaaagh! They're after me! Keep them away, keep them away! Send for Buffy now!"

Apply careful causal reasoning to the problem. You will find the answe very clear once you write down and organize all the facts given above. (You can print out just this problem if you download ferlinghetti.htm or ferlinghetti.rtf.)


Ignoring a Possible Common Cause

Remember that a strong correlation, by itself, does not prove causality. The right way to show causality is to demonstrate a strong correlation that cannot be exaplained any other way. When there is another reasonable explanation for the putative causal relationship, the argument commits the fallacy of "ignoring a possible common cause." Remember, it is sometimes the case that two things are correlated, not because one causes the other, but because some third factor causes both.

Every time I put on a little weight, I lose a little hair. So if I exercise and go on a diet, I'll stop losing my hair.

Ignoring a common cause might be easier to understand if it was called "ignoring a possible common cause" because it is the fact that some third thing might be causing the correlation that makes the argument fail. Strictly speaking, all you have to to refute any causal argument and it is a very popular fallacy. It is often commited by people who want to believe that drug use, by itself, causes crime. If there is any reasonable possibility that a person's criminality and drug use have a common cause, such as poor upbringing or exposure to scofflaw culture, such as could reasonably be thought to have caused criminalty without exposure to drugs, then the correlation between drug use and criminality cannot prove that the drug use caused the criminal tendencies.

Even when there is a strong correlation that cannot be reasonably explained without assuming a causal realtionship between the two events, people may be confused about which is the cause and which is the effect. People can commit false cause by completely reversing a causal relationship. That is to say, two things are correlated, but the wrong thing is identified as the cause.

Reversing Cause and Effect

Have you noticed how Jane gets depressed every time her cancer gets worse. If we could just cheer her up, that would take care of that nasty cancer!

Here the arguer has reversed cause and effect. by mistaking the effect for the cause and the cause for the effect. The two things are undoubtedly correlated, and there is no third element that could cause both things, but the wrong event is identified as the cause.

Reversing the Direction of the Effect

Finally, a more subtle, and perhaps more common fallacy is when an arguer correctly identifies a cause, but reverses the direction of the effect. The arguer mighy, say, have noticed that the masses of water shot out of fire-hoses are associated with building fires, but erroneously assumes that adding the water to the building causes the fire, or that adding water makes the fire burn more fiercely. Because I can't think of a better name for it, I call this reversing the direction of the effect.

Why do we have drug laws? We have to have them because of all those drug-related murders! Those dealers will kill to keep their activities secret, you know!

Notice that the arguer here believes that laws against possession, use and sale of drugs reduce the murder rate. Also notice that the arguer does not offer any data whatsoever. Finally, notice that the arguer ignores a well-known causal relationship between criminalization of activities and murder. Students of history will recall that the criminalization of alcohol trafficking in the United States was followed by an enormous increase in the number of murders related to alcohol trafficking. This murder rate was drastically reduced by the later legalization of alcohol trafficking. Generally speaking, people do not kill to conceal activities that are not illegal.

But the government of Slobovia had to imprision those peaceful protestors! Don't you know that disagreement with the government can escalate to violent opposition?

Here the arguer correctly connects political repression with changes in the level of political violence. But he illegitimately assumes that political repression reduces or prevents political violence. The right way to prove such a thing would be to give evidence that repressive countries tend to have lower levels of political violence than non-repressive countries, which he has not done.

Begging the Question

I want to emphasize very strongly that a mental association is no substitute for actual evidence. Just because two things are associated in your mind, or you think that one thing must cause another, you cannot even begin to have an argument to that effect until you come up with some real facts. To argue that one thing must cause another merely because you think that it must be so is simply to beg the question. Consider the following.

size="12" face="Arial">Rylan. Of course welfare causes dependency! It just stands to reason that people on welfare will want to stay on welfare for as long as possible.
Aspen. Are you crazy? I think it stands to reason that people on welfare will want to get off welfare as soon as possible. We can't both be right, so I don't think talking about "stands to reason" tells us anything about welfare.

Notice that Rylan offers his own opinion as evidence. Unsupported by evidence, his claim that his opinion "stands to reason" is nonsense. Things only stand to reason when they are supported by a logically compelling argument. Offering one's personal opinion as evidence is not an argument. Aspen, however, has a logically compelling argument. Notice that her conclusion is just that arguments like Rylan's can't prove anything. True, her opinion that people on welfare will want to get off welfare as soon as possible is just her opinion, but it is a fact that she holds that opinion, which shows that Rylan's opinion isn't the only one out there, which is enough to show that Rylan's argument is no good. (Generally, people who tell you that something "stands to reason" instead of giving you an argument are simply trying to cover the fact that they have no argument.)

People can of course commit fallacies when attacking a causal argument. The most common fallacy in this area is red herring.

Red Herring

The "inconvenient fact" method of attacking causal arguments doesn't always work. Sometimes the fact in question isn't even remotely inconvenient for the argument. When this happens, the person attacking the argument has committed a red herring fallacy.

Suppose that the "Hacking Cough" study is a long-term study comparing a group of heavy cigarette smokers to a group of nonsmokers has found that, over time, cases of lung cancer crop up in the smoking group at a rate five times that which they crop up in the non-smoking group. Some people take the Hacking Cough Study to have proved that cigarette smoking causes lung cancer. Other people claim that it doesn't prove that cigarette smoking causes lung cancer. If we pretend that these people give the following arguments, we would be pretending that they all commit red herring fallacies, because all the following arguments are red herrings.

The Hacking Cough Study doesn't prove that smoking causes lung cancer because it is a fact that some people who smoke heavily never get lung cancer.

You cannot claim that the Hacking Cough Study proves that smoking causes lung cancer because no one, including the authors of the study, can explain just how it is that smoking manages to cause lung cancer.

Plenty of nonsmokers get lung cancer, so it can't be true that cigarette smoking causes lung cancer.

The first argument is a fallacy because the statement "A causes B" only means "A raises the probability that B will happen," not "A always makes B happen." The second one is a fallacy because causal arguments don't have to provide explanations. Strong evidence of a strong correlation always establishes a cause and effect relationship, whether or not we can explain that relationship. And finally, the third argument is also a red herring because the study doesn't have to prove that smoking is the only cause of lung cancer in order to prove that it is a cause of lung cancer.

Consistency With Available Evidence

Sometimes people will insist that some causal claim is true even though all the evidence they have implies that it is false. The following is a paraphrase of an actual conversation. (Only the names have been changed.)

size="12" face="Arial">Beau. It's obvious that welfare causes dependency, because someone who's getting money without working is going to want to keep on taking it easy.
Issac. You know, I don't think it's fair of you to project your own preferences on other people. What makes you think that people on welfare feel the same way you would in that situation?
Beau. What are you talking about? I wouldn't feel that way! I'd want to get off welfare as soon as possible.
Issac. Oh, sorry. I guess you were basing this on people you know. Still, you shouldn't assume that the people who end up on welfare are like the people in your family, and your other friends and acquaintances.
Beau. Hey! None of my family are like that! None of my friends would want to stay on welfare. In fact, I don't know anyone who would.
Issac. So you're saying that someone who's getting money without working is going to want to keep on taking it easy, even though all of the actual human beings you know about wouldn't want to keep on taking it easy, even if they were getting money without working.
Beau. Now you've got it.

The first point is, of course, that Beau's conclusion is contradicted by all the evidence he has. He's saying that all people are suceptible to being made dependent by welfare even though all of the people he knows lack that suceptibility. The second point to notice is that Beau is not even using the right kind of strategy to establish a causal claim. His first statement is actually a question begging fallacy, since the statement "someone who's getting money without working is going to want to keep on taking it easy" is simply a more general statement of the claim "welfare causes dependency." The two claims are not different enough to make the premise acceptable to anyone who rejected the conclusion. Issac treats Beau's argument as a generalization as a way of getting Beau to admit that he has evidence that contradicts his conclusion. Beau may indeed be generalizing, since he might have an idea in his head of what he thinks a typical welfare recipiant is like, and is generalizing from this imaginary person to real welfare recipients. Of course, imaginary evidence never counts. (Therefore arguments based on imaginary evidence always commit the relevance fallacy of red herring.)

Causal Chains and Slippery Slopes

The fallacy of slippery slope combines a whole string of dubious causal claims. The difference between a slippery slope fallacy and a legitimate causal chain argument is that the legitimate argument depends upon a series of well-established causal relationships while the slippery slope includes at least one dubious or speculative causal claim.

Censoring hardcore pornography will soon lead to censorship of softcore pornography, which in turn will lead to suppression of harmless erotica like swimsuit photos, and that itself will finally cause censorship of nude pictures in medical textbooks.

If you make marijuana legal then it'll be magic mushrooms. If 'shrooms, then speed, and after that, peyote! Then cocaine won't be far behind. Which means crack! And what about heroin? And acid! Then there's angel dust, and finally those designer drugs that make people's heads explode! So if we make marijuana legal, decent people won't be able to sleep for the sound of all the exploding heads.

Would legalizing marijuana cause 'shrooms to become legal? Would legalizing 'shrooms cause speed to become legal? Would legalizing speed cause peyote to become legal? Would legalizing peyote cause crack to become legal? Would legalizing crack cause heroin to become legal? Would legalizing heroin cause angel dust to become legal? Would legalizing angel dust cause designer drugs to become legal? Is there anything about legalizing one drug that makes it impossible, or extremely difficult to avoid legalizing the next drug in the sequence? If there's any point where we can legalize one (relatively harmless) drug without having to legalize the next (more harmful) drug, the causal chain snaps, and the slippery-slope argument fails.

(Slippery-slope is what logicians call a presumption fallacy, because the arguer illegitimately assumes that, because the first element in a chain seems to him to be associated with the second element in the chain, it will then follow that allowing the first element to exist will cause the second element to come to pass. But if a causal relationship has not been proved to exist between these two elements, then he simply cannot assume that one will cause the other.

Reasonableness

Another important issue in causal reasoning is the reasonableness of a causal prediction. A causal prediction is a claim that some action that we contemplate taking will have some particular effect. For instance, the claim that invading Iraq will make us more secure is a causal prediction because it holds that if we invade Iraq (as we just did), the foreseeable future will be more secure for us than if we had not invaded Iraq. An opposing causal prediction might be that the invasion will make us less secure. Such predictions can be partially tested by waiting until after the fact and seeing if the claimed effect actually comes to pass. In the case of the Iraqi invasion, for instance, the first prediction would lead one to expect decreased security at airports, fewer terrorist alerts and less money spent on homeland security, whereas the second prediction would lead one to expect at least a continuing high level of security, more terrorist alerts and more money spent on homeland security. But there are two problems. The first is that there may be other factors involved, so that the real effects are hidden. For instance, it may in fact be true that the invasion increases our security, but some other independent factor, (say, the final fruition of a terrorist plot that was begun well before the invasion was announced, or the loss of competent security administrators in a car accident) decreases our security, hiding the gain from the invasion. The second problem is that we need to be able to predict the effects of our actions before we act. We cannot undo an invasion, so we have to be sure of its effects before we go ahead and do it. For this reason, a great deal of causal reasoning is done without the benefit of definitive evidence regarding the particular kind of action contemplated. The best we can do sometimes is to think about what we might reasonably expect to happen based on generally known causal rules, and such thinking, like any thinking, always runs the risk of committing non-causal as well as causal fallacies. So look out for any and all of the fallacies we've learned previously as well as the causal ones.

If you're not already sick of hearing about the subject, here's a little story about causal reasoning: causalstory.htm

Reminder Facts, Opinions, Conclusions

Technically, a "fact" is a something that cannot reasonably be disputed, an "opinion" is just something someone believes, and a "conclusion" is something someone wants other people to believe. In terms of evidence, we can define a "fact" as a claim that is supported by compelling evidence, an "opinion" as a claim that someone thinks is supported by compelling evidence, and a conclusion someone says is supported by compelling evidence.

More Exercises

For each of the following argument pairs, I want you to do following things:

For each argument, decide whether or not it makes a causal claim. 
For each argument that makes a causal claim, decide whether or not that claim is based on a correlation argument.
For each correlation argument, identify the specific correlation.
For each pair of opposing arguments, decide whether or not the second argument is a counter argument.
For each counter argument, identify the specific part of the other argument that is being attacked.
For each pair of opposing arguments, figure out which one is the weaker argument.
For each weak argument, name the fallacy committed by that arguments.
For each fallacy figure out the key fact that kicks that bad argument in the head.

Remember that the right way to establish a causal relationship is to show that:
1. The thing that's supposed to be the cause is very strongly correlated with the effect.
2. Whenever the two things happen together, the thing that's supposed to be the cause happens before the effect.
3. The correlation cannot reasonably be explained any other way.

Remember that the very best critiques will include both the correct fallacy name and the crucial fact(s), explained in such a way that a reasonable reader will be able to immediately see why the weak argument is bad.

Once you have made your best effort to analyze all the arguments and write your own critiques, check your answers at the end of the chapter

Exercise 16. Raegan. How can you stand there and protest the war? Don't you know our boys are over there?
Rohan. Well, if there wasn't a war, wouldn't they be back here instead of over there?

Exercise 17. Glenn. Studies show that people who dance are five times as likely to have knobby knees as people who don't dance, so dancing causes knobby knees.
Savanah. Hah! That's ridiculous! Don't you know that every one of those studies included  a bunch of people who danced around for years and never got knobby knees, so it must be blindingly obvious that dancing doesn't cause knobby knees.

Exercise 18. Tobias. We must ban digital cameras immediately! A major 17-country study has shown that people who use digital cameras are 10 times more likely than non-digicam-users to become lawyers, and that the increase in lawyerism in any area is perfectly correlated with the local increase in digicam use. The study has been checked over by 217 experts who all independently certified it as perfectly conducted and demographically appropriate, with absolutely no reason to think that the study might be flawed in any respect. So we must ban digicams before we are buried in lawyers.
Leila. I've seen that study. I've read that study from cover to cover. And I can tell you we don't need to worry. This study fails to prove that digicam use causes lawyerism because it totally fails to explain how digicam use causes lawyerism.

Exercise 19. Everett. I've just discovered some disturbing news about Histafix, the medicine to relieve allergy symptoms. Did you know that once allergy sufferers start taking it, they almost never stop! Obviously, this means that taking Histafix causes dependence on Histafix. I just heard that thousands of people are taking Histafix even as we speak, so we should ban it now so that these people can be cured of their dependence on Histafix.
Kiersten. Um, maybe all these people keep taking Histafix because their allergies don't magically go away after they take a few doses.

Exercise 20. Tate. I just found out that exposure to Faux News causes blowhardery. It's been found that the more time people spend watching Faux News Network, the more likely they are to become irrational, fact-avoidant, gratuitously insulting pompous, brain-dead blowhards!
Kelsie. That's rubbish. I know hundreds of blowhards who never watched Faux News, so blowhardery has nothing to do with watching that Fair And Balanced network.

Exercise 21. Mike. Gasolene is flammable, so I don't think it's a good way to put out that fire.
Karley. The need to pour gasoline on the fire has never been so clear. Ever since I started putting gasoline on the fire it's been getting fiercer and fiercer! So obviously, we need to go out and buy a lot more gasoline.

Exercise 22. Barry. I used to think that Reverend Jim was wasting his time with his Pray for Peace campaign, but it's really begun to foster a sense of community in our parish.
Julius. A sense of community is a good thing, but we must set it against the needs of people in other countries. Since Reverend Jim started his Pray-For-Peace campaign, four more wars have started. We must shut down this Pray-For-Peace campaign before even more countries are dragged into war!

Exercise 23. Wally. If we allow pornography in adult book stores it won't stop there. Soon it will be in the regular book stores, because they're book stores too. Then it will be in the libraries, because they're just bookstores that lend books instead of selling them. Schools have libraries, so it will soon be in the schools too! Well did you know that churches have schools too, so if we allow pornography in adult book stores it won't be long before it's in our churches too! Obviously, pornography should be banned absolutely
Xena. The people who want to ban pornography are mostly the same people who want to ban all discussion of sex. If we cave in on pornography they'll have a precedent to point to, which will make it easier for them to ban things like The Joy of Sex. If they succeed there, they'll go on to other things, like sex education. If we want to preserve free discussion of sexual matters, we should hold the line on pornography.

Exercise 24. Cullen. I think it's pretty clear that drinking bottled water causes mopery. A recent study has shown that people who drink bottled water are four times as likely to mope around as people who don't drink bottled water.
Sterling. Yes, but the study also showed that there's plenty of people who mope around without ever touching bottled water, so the study doesn't prove that drinking bottled water causes mopery.

Exercise 25. Quentin. I think we should go back to pumping oxygen into that sunken submarine. It would help the sailors.
Elisha. Since we stopped pumping oxygen into that sunken submarine the sailors have gotten sicker and sicker. This is a very serious situation which we must address immediately by making sure that there is absolutely no oxygen in that sunken submarine.

Exercise 26. Tanya. I've just heard some disturbing news. A major recent study just compared two demographically identical groups, one of which listened to classical music a lot, and the other didn't listen to classical music at all. The group of classical music listeners turned out to have a much higher percentage of white-collar criminals than the non listeners, so it looks like listening to classical music causes white-collar crime.
Alfred. I've seen the same study, and I can tell you that it totally fails to prove that classical music causes white-collar crime because nowhere in that study do they even begin to explain how listening to classical music goes about causing that white-collar crime.

Exercise 27. Humberto. It's beginning to look like drinking herbal tea makes people taller. They did a long-term study comparing a million adult herbal tea drinkers with a million adults who never, ever drink that disgusting rubbish. On average, the people in the herbal tea group got three millimeters taller for every year they drank herbal tea, while the demographically equivalent adults in the other group didn't grow at all.
Camila. Herbal tea doesn't make people taller. Plenty of people in that study drank herbal tea for years without getting any taller.

Exercise 28. Answer the following questions, and explain your answers.
vi. Can a correlation argument be based only on the fact that the "cause" is always absent whenever the effect is absent?
vii. Can a correlation argument work if something else is just as strongly correlated with the effect as the purported cause?
viii. Does the "cause" have to have a one-to-one correspondence with the effect?
ix. Is "it's the only thing I can think of" ever a good causal argument?

Exercise 29. Answer the following questions, and explain your answers.
i. Is it possible to make a successful correlation argument without any evidence of a correlation between the effect and the thing that’s supposed to be causing it?
ii. Is it possible to make a successful correlation argument without providing an explanation of how the purported cause might cause the effect?
iii. Is it possible to make a successful correlation argument without providing any evidence that the purported cause even exists?
iv. Is it possible to make a successful correlation argument if it is proven that the purported cause sometimes happens without being followed by the effect?
v. Is it possible to make a successful correlation argument based on a single incident?
vi. Is it possible to make a successful correlation argument if it is proven that the effect sometimes happens even though the purported cause is not present?
vii. Is it possible to make a successful correlation argument based only on the fact that no-one else can think of anything that could cause the effect?

For more practice, you can download and do the practice/makeup exercises. (Make sure the document margins are set to 0.5 inches or narrower.)

If you have time, I recommend the movie Fat Head. It's well made, informative and very funny. It also blows the lid off a bunch of pseudo-scientific myths that are very prevalent in our society. (It also debunks a few myths I used to be very fond of!)


Exercise Answers.

1. No. Even if all the claims ("o" through "t") were true, none of them would logically support any of the causal claims ("a" through "f") made at the top of this chapter?

2. "A" is a correlation argument because it claims that moderate drinking has been found to correlate with better health. "B" is not because it is based on a similarity between two words, which has nothing to do with correlations.

3.
i. No.
ii. Nope.
iii. Nuh-ah!
iv. Well, no.
v. Good god, no!
(Explanations for these answers can be found in the text preceding the questions. If my explanation isn't clear, please ask about this in class or by email.)

4. Daryl’s argument misses the fact that the patients who didn’t fairy-up also took Zydigm. (Gwendolyn alludes to this in her criticism of Daryl’s argument.)

5. Aliya’s argument is weak because she ignores the fact that Dasia got laser eyes without taking Terraplex. It’s possible that both Terraplex and another drug cause laser eyes, but it’s not likely. 

6. Gianni fails because his “1-to-1 correlation” is not a correlation at all, as Susana points out. The fact that a one-general patient took exactly one milligram is meaningless because “milligram” is an arbitrary measure. If the drug had been measured in “grains” (an old apothacary’s standard) it’s mass would have been 64.79891 grains. 

7. Zoie fails because she ignores the fact that Harris also took Dynastar and didn't grow any extra limbs, and Jakes grew extra limbs without taking Dynastar

8. There is one drug, Xindeco, that was only taken by the fairies, so Mill’s method of difference supports Xindeco as the cause.
(It is also possible, but less likely, that this is a coincidence, and that one of the other drugs causes the problem, but only in some people.)

9. Mill’s method of agreement much more supports the claim of Shegos to be the cause because it is the only drug taken by all four patients.

10. Susana is right that we have to look for what Mill calls “concommitant variation,” and we find it in Kolvox, which gives us one channeled general per 50mg.

11. If you examine the evidence you will see that there is one and only one drug that is always present when extra limbs are present and always absent when extra limbs are absent, and that drug is Quindor. This way of thinking is called "Mill’s combined method."

12. B is a counter argument. If we can reasonably explain the difference without assuming a health benefit from moderate drinking, then the differnce does not support the implication that there's a benefit.

13. B is a direct argument. The second argument just gives an alternative source of data. It doesn't give us any reason to question the evidence or logic given in argument A.

14. B is a counter argument. It offers an alternative explanation for the observed data. If that explanation turns out to be reasonable, argument A's data will fail to support argument A's conclusion. (The alternative explanation doesn't have to be proved true, it just has to be reasonable)

15. It’s the mineral water. It’s the only thing that correlates with the asthma. As the villagers began drinking it more and more, the problem got worse and worse. If it was the tin mine, the asthma problem would have started in Roman times and continued at the same level since then. The bats have been around longer than the tin mine, even though they were only discovered in 1845, so it’s not them either. The perfume factory shut down during both wars and the wheat only produces pollen in the summer, but the asthma problem didn’t go away during either war, and it exists even when there’s no pollen in the air, so neither of those is the cause. Consumption of the mineral water is the only thing that perfectly correlates with the asthma problem (key fact), so it’s the cause.

16. Both arguments make causal claims. Reagan claims that protesting here endangers the boys over there. (Her argument can be paraphrased as "Protesting endangers our boys. Endangering our boys is wrong. So protesing is wrong.")  Rohan claims that keeping the boys in a war zone endangers the boys more. Neither offers any correlation. Rohan offers a direct argument. He gives no reason to question Reagan's argument. Raegan appears to be relying on the idea that homefront protests encourage the enemy to fight harder which endangers the combat troops. and it does seem reasonable that if the German people had protested the 1939 invasion of Poland, the Poles might have been encouraged to more strongly resist the blitzkrieg. The same applies for other Saddam Hussein’s 1990 invasion of Kuwait, and so on. In fact, if Mexico fell into the hands of an aggressive right-wing government that somehow managed to mount a successful invasion of the US, protests against this invasion by ordinary Mexicans would probably encourage Americans to more strongly resist the invasion, thus endangering the Mexican soldiers spearheading the invasion. Of course, there is the (key) fact that, if the invading government changed its mind and stopped the invasion, none of the soldiers would be in any danger at all, so if Raegan really cares about the troops' lives, she should also be trying to stop the invasion. The fact that it is the government (which Reagan supports) that is actually putting the troops in danger means that Reagan is technically comitting the fallacy of ignoring a possible alternative cause . 

17. Glenn makes a causal claim, Savanah does not. Glenn refers to "studies," which presumably are based on correnations. The correlation mentioned is between dancing and knobby knees. Savanah's argument is a counter argument because she refers to information contained in the studies Glenn is relying upon to support his claim.  If there's something wrong with those studies, Glenn's argument collapses. The key fact here is that causal claims only have to show an increased probability, so Savanah is wrong because Glenn is only claiming that dancing makes knobby knees more likely, not that it always causes knobby knees. Savanah is referring to something that isn't really relevant, so she's committing the red herring fallacy.

18. Tobias makes a causal claim, Leila doesn't. Tobias indirectly refers to correlations when he mentions the studies. Leila’s counter argument criticizing those studies doesn’t work because a causal argument only needs to prove the existence of a reliable correlation between two kinds of event. The key fact is that lack of explanation doesn’t matter so long as the correlation is proved. (Pretty much all known causal relationships lacked explanation when they were first proved.) Leila is making a fuss over something that doesn't matter, so she's comitting a red herring fallacy.

19. Everett makes a causal claim backed by a correlation argument. Kiersten attacks the logic of his argument, so she's making a counter argument. Notice that while she doesn't question Everett's data, she does question his interpretation of those facts. She's implying that his data doesn't mean what he thinks it means, which makes her comment a counter argument. What would it mean to say that someone is “dependant” on something? Presumably it means that the person finds himself unable to do without that thing even though he actually had no real need for that thing. Thus someone who is dependant on Histafix would be unable to stop taking Histafix, even though she actually did not need it to control allergy symptoms. To make his argument work, Everett would have to show that there is a significant group of people who provably do not have allergies, and who still find themselves unable to do without Histafix. Since he fails to even begin to prove the existance of even one person who both lacks allergies and stays on Histafix anyway, Everett’s argument fails completely. Since he correctly notes that people on the drug tend to stay on the drug, but fails to notice that this could be because allergies are permanant, he's committing the fallacy of ignoring a possible alternative cause. 

20. Tate makes a causal claim backed by a correlation argument. He cites a correlation between watching Faux and blowhardery. Kelsie attacks the logic of his argument, so she's making a counter argument. Kelsie’s argument fails. The key fact is that Tate is not claiming that exposure to Faux News is the only cause of blowhardery, only that it is a cause. It is perfectly possible for there to be more than one cause of blowhardery, so the existance of non-Faux blowhards doesn’t invalidate Tate’s argument. Kelsie is committing a red herring fallacy because the existence of non-Faux blowhards is irrelevant to the issue. (Another way to put this is that she think it's a key fact, but it isn't.)

21. Mike is not making a causal argument because he is not supporting his causal claim that gasolene is flammable. Rather, he is making that unsupported (but unquestioned) claim in support of his claim that gasolene is not a good way to put out a fire. This is a direct argument. Karley does not address his argument, but instead makes contrary a claim based on independent evidence, thus also making a direct argument. Karley has reversed the direction of effect. She wants the fire to go down, and advocates adding gasolene to achieve this, but (key fact) the addition of gasolene positively correlates with the fire getting fiercer, not with it going down. Notice that while Mike does not support his claim that gasolene is flammable, this is okay because that claim is commonly accepted and not challenged in this dialog, whereas Karley actuall cites evidence that contradicts her conclusion.

22. Barry and Julius make unrelated causal arguments, and so both make direct arguments. Barry claims that Rev. Jim’s Pray for Peace campaign has begun to foster a sense of community, which implies that he's seen this sense grow as the prayer campaign has progressed. This could presumably be challenged in various ways, but Julius does not do so. Instead, Julius points out that four more wars have started since the campaign began. However, (key fact) he does not say how many wars ended, or how many began before the campaign got going, and he ignores all the other possible causes of those four new wars. This seems like a weak correlation fallacy to me.

23. Both Wally and Xena attempt to make causal chain arguments. These attempt to string together cascades of proven causal relationships, so neither of them is a correlation argument. Neither criticises the other's logic, so both make direct arguments. Causal chain arguments only work if each link in the chain is a proven causal relationship. Wally’s argument is based only on his own definitions, so isn’t based on causal relationships at all. This makes it a definite slippery slope fallacy . Xena’s argument, in contrast, is based on claims about the real nature of the issues and the people involved and so if her description of the situation is accurate, her argument is at least plausible.

24. Cullen makes a causal claim based on a correlation (in the study) between bottled water and mopery. He's not talking about anyone else's argument, so it's a direct argument. Sterling talks about the study and gives no independent evidence, so he makes a counter argument.  Sterling commits a red herring fallacy because (key fact) Cullen is just arguing that drinking bottled water causes mopery, not that it is the only cause of mopery.

25. Quentin makes a causal claim (oxygen will cause the sailors to get better), but it's not based on any cited correlation. Neither argument refers to the other, so they're both direct arguments. Elisha is reversing the direction of effect here. The key fact is that cutting the oxygen made the sailors sicker, so  his evidence supports the claim that it is a lack of oxygen that is making the sailors sick.

26. Tanya makes a causal claim based on a correlation between classical music and white-collar crime. This is a direct argument. Alfred makes a counter argument by pointing out what he takes to be a flaw in the study. However, his argument is a red herring because of the key fact that you don’t have to be able to explain something in order to prove that it exists. If you can show a solid correlation, you’ve proved the causal relationship.

27. Humberto supports a causal claim with a correlation implied by the word "study," which is a direct argument. Camilla makes a counter argument by arguing with Humbert's interpretation of the data in Humberto's argument. She commits a red herring fallacy because the key fact is that Humberto does not have to prove that herbal tea always make people taller, only that it sometimes does.

28.
vi. No way.
vii. No. Are you kidding?
viii. Noooooooo.
ix. Ha! No.
(All answers are "no.")

29.
i. No.
ii. Yes.
iii. No.
iv. Yes.
v. No.
vi. Yes.
vii. No.

If you need to make up the quiz for this chapter, use the Make Up Exercise

For more practice, you can download and do the practice/makeup exercises. (Make sure the document margins are set to 0.5 inches or narrower.)

Copyright © 2013 by Martin C. Young

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