Self-study
Advertisement: Support VIVVY, a video-based foreign language course for children, was introduced seventeen years ago. ████ █████ ███ ██████ ████ █████ ███ █████ ████████ ██ ███ ██████ ███ ████ ███ ██████████ ██████████ █████████ ██ ██ ████ █████ ████ ██████ ███ ███ ██████ ███ ██ ███ ██ ██████ █ ██████████ ██████████ ████████
Method of Reasoning
The author concludes that any child who uses VIVVY can be expected to become a successful university student in the future. He supports this conclusion by providing an example of three people who used VIVVY in their childhood and grew up to become successful university students.
Identify and Describe Flaw
This author commits the cookie-cutter flaw of confusing correlation with causation. The author has presented three individuals whose use of VIVVY is correlated with success in university; however, he has not provided evidence that VIVVY caused their success in any way. The author then concludes that there is a causal relationship between use of VIVVY and success in university, stating that any child who uses it can be expected to be successful in university. However, without proving that the relationship between VIVVY and success in university is anything beyond a correlation, the author’s argument is unsupported.
10.
Which one of the following ████████████ ████ ███████████ ██ ████████ █████████ ████ ███ ████████ ██ ███ █████████████ ██ ███████
a
Similarly, you could ████████ ████ ███ ███ ██████ ██ ███ ███ ███████ ██ ███ █████ █ █████████ ██████ █████ ████ ██████ ██████████ ███ ████ █████ █████████ ███████ ███ █████ █████ ██████ ███ ███████ ████████
This author confuses correlation with causation. The author presented three individuals whose use of a good luck charm is correlated with winning the lottery; however, he has not provided evidence that the good luck charm caused them to win. The author then concludes that there is a causal relationship between a good luck charm and winning the lottery. Unless he proves the relationship between good luck charms and winning the lottery is anything beyond a correlation, his argument is unsupported.
b
Similarly, you could ████████ ████ █████ ██████ ███ ██████ ██ ███ ████ ██████████ █████ ████ ██████ ██████ ███ █████████ ███ ████████ ███ ███████ ███████ ███ ████ █████████ ███ ██████ ████ █████████ ██ █ ███████
Wrong flaw. This conclusion is not supported—if someone Jesse went to the picnic with has food poisoning, there are several ways he could have contracted it as well, and the argument rules out none of them. This answer choice differs from the stimulus because it does not commit the error in using causal logic that the stimulus does. Additionally, it uses three people as an example and concludes about one of them, whereas the stimulus used three students as an example but concluded about future students.
c
Similarly, you could ████████ ████ █████ ██████ ███ ██████ ███ ███ ████ █████████ ███ ████ ██ ████ ████ █████ ████ ███ ████████ █████ ██████ ███ ████ ████ ███ ██████ ██ ██ ████ ████ ███ █████ █████ █████████ ███ ███ ████ ████ ███ ████ █████ ██████ ███ ████ █████
Wrong flaw. This argument fails because it states that any employee hired in the last year could expect to be laid off, then concludes that only the employees hired in the last year will be laid off. What if employees of longer tenure at the company will be laid off for other reasons? Without accounting for these other employees, the argument is unsupported. This argument does not confuse correlation and causation like the stimulus does.
d
Similarly, you could ████████ ████ ████ ██████ ███ ████ █████████ █████ ██████ ████ ███ █████ ██████ █████ ████ ██ ███ █████████ ██████ ███ █████ ██████ ███ ███ ██████ ██ ███ █ ████████ ██████ ███████████ ███ █████ █████ ██████ ████ ██████ ████████ ████████
Wrong flaw. Getting the occasional speeding ticket does not imply that you routinely speed—it only implies that you were speeding on those specific occasions. A couple of speeding tickets does not prove anything about someone’s day-to-day driving habits, so this argument is unsupported. This differs from the stimulus because there is no causation-correlation confusion, and the author does not apply something about Ken, Norma, and Mary to a different group in the conclusion.
e
Similarly, you could ████████ ████ █████ ████████ ███ ████ ███ ██████ ██ ███ ████ █████ ████ ████████ █████ ██████████ ██████████ █████ ████ █████ █████ ██████ ██████ █████ ███████████ ███ ████ ██████ ███ █████████ ████ █████ ████ ████ █████ █████
Wrong flaw. This conclusion isn’t supported without a good reason to compare this year’s graduates to last year’s. Just because most people found jobs last year does not mean the chances are the same this year—the current graduates may face a recession or hiring freeze that past students did not. Without explaining why the job chances of both groups are similar, this argument is unsupported. This flaw differs from the stimulus because there is no confusion between correlation and causation.