Advocate: A study of people who had recently recovered from colds found that people who took cold medicine for their colds reported more severe symptoms than those people who did not take cold medicine. Therefore, taking cold medicine is clearly counterproductive.

Summarize Argument: Phenomenon-Hypothesis
The advocate argues that taking cold medicine is counterproductive. She supports this claim by citing a study wherein people who took cold medicine reported more severe symptoms than did those who didn’t take cold medicine.

Identify and Describe Flaw
This is a “correlation doesn’t imply causation” flaw, where the advocate sees a correlation and concludes that one thing caused the other without ruling out alternative hypotheses. Specifically, she overlooks two key alternatives:
(1) The causal relationship could be reversed—maybe people with more severe symptoms are more likely to take cold medicine!
(2) Some other factor could be causing the correlation—for example, maybe in parts of the world where colds tend to be more severe, cold medicine also happens to be more widely available.

A
treats something as true simply because most people believe it to be true
The advocate’s premise is a study, not a general belief. Furthermore, we have no reason to think that most people believe her conclusion or her premise to be true.
B
treats some people as experts in an area in which there is no reason to take them to be reliable sources of information
The advocate doesn’t arbitrarily treat anyone as an expert. Rather, she cites the results of a study wherein people reported on their own symptoms—a subject in which people do have some expertise!
C
takes something to be true in one case just because it is true in most cases
The advocate’s conclusion is extremely general; she does not mention any specific cases.
D
rests on a confusion between what is required for a particular outcome and what is sufficient to cause that outcome
The advocate’s argument doesn’t mistake sufficiency for necessity. She doesn’t claim in either the premise or the conclusion that cold medicine is sufficient or necessary to cause severe cold symptoms.
E
confuses what is likely the cause of something for an effect of that thing
This is the cookie-cutter flaw of confusing correlation and causation. The advocate’s argument forgets that the causal relationship could be reversed—maybe people with more severe symptoms are more likely to take cold medicine!

8 comments

When a chain of service stations began applying a surcharge of $0.25 per purchase on fuel paid for by credit card, the chain’s owners found that this policy made their customers angry. So they decided instead to simply raise the price of fuel a compensatory amount and give a $0.25 discount to customers paying with cash. Customers were much happier with this policy.

Summary
A chain of service stations charged a $0.25 fee per purchase for fuel paid for with a credit card. This caused the service station’s customers to be angry. Instead, the chain decided to raise the overall price of fuel and offer customers a $0.25 discount for paying with cash. The service station’s customers were happier with this policy.

Strongly Supported Conclusions
Sometimes people’s reactions to a situation depends in part on how that situation is presented to them.

A
People usually adopt beliefs without carefully assessing the evidence for and against those beliefs.
This answer is unsupported. We don’t know from the stimulus under what circumstances people will usually adopt beliefs.
B
People’s perceptions of the fairness of a policy sometimes depend on whether that policy benefits them personally.
This answer is unsupported. We don’t know from the stimulus whether people think this policy is fair. We can’t infer from their happiness that they think it is fair.
C
People usually become emotional when considering financial issues.
This answer is unsupported. We don’t know from the stimulus under what circumstances people usually become emotional.
D
People often change their minds about issues that do not make significant differences to their lives.
This answer is unsupported. We don’t know from the stimulus under what circumstances people change their mind. We don’t even know if the customers who were previously angry are the same customers that are happier after the policy change.
E
People’s evaluations of a situation sometimes depend less on the situation itself than on how it is presented to them.
This answer is strongly supported. The only thing that changed in this scenario was whether or not customers were aware of the surcharge.

4 comments

Scientist: A number of errors can plague a data-collection process. Since examining the collected data enables researchers to detect many of these errors, it is standard practice for researchers to correct collected data. However, in my field, there is a striking tendency for such corrections to favor Jones’s theory; that is, the majority of corrections result in the corrected data’s being closer than the uncorrected data to what Jones’s theory predicts.

"Surprising" Phenomenon

Why do data corrections in the scientist’s field tend to favor Jones’s theory?

Objective

The right answer will be a hypothesis that explains why these data corrections gravitate towards what Jones’s theory predicts. The explanation must either signal that Jones’s theory is correct and errors naturally stray from the theory, or that those doing the data-corrections are themselves biased towards Jones’s theory.

A
Researchers normally give data that is in line with a theory the same weight as data that conflicts with that theory when they are determining whether to accept that theory.

If anything, it seems possible that researchers are giving data less weight when it strays from Jones’s theory. We also have no idea whether or not the theory has been accepted yet.

B
Researchers in the scientist’s field give data that conflicts with Jones’s theory greater scrutiny than they give data that is in line with Jones’s theory.

Researchers go looking for errors in data that conflicts with Jones’s theory. Data that falls in line with Jones’s theory, on the other hand, goes unremarked and uncorrected. This explains why data is corrected to align with Jones’s theory.

C
Researchers in the scientist’s field are more likely to pursue lines of research that they expect will favor theories they accept than to pursue other lines of research.

It doesn’t matter what researchers expect ahead of time. We need to know why their data-corrections align with Jones’s theory.

D
Even if researchers fail to detect errors in a data-collection process when they examine the data that they collected, that does not guarantee that no such errors exist.

This may be true, but why do researchers mainly detect errors that are then corrected to bring data in line with Jones’s theory? This doesn’t tell us enough about the data-correction process.

E
Researchers in the scientist’s field have formulated several other theories that attempt to explain the same range of phenomena that Jones’s theory attempts to explain.

Why do data-corrections favor Jones’s theory rather than these other theories? If anything, this only complicates things since we now know there are other theories to choose from.


39 comments