In social science research, "highest education level attained" would

I think the answer should be C.
We can challenge the conclusion but we cannot challenge evidence or premise.
@VERITASPREPKARISMA carcass,
Please help!

I think the answer should be B.
The given findings show trends.

Two things:
- Education attained and proficiency in chess are co-related but it is not clear whether the co-relation is positive or negative. So, any statement which concludes (positive or negative) based on this relation may not be true.

- Marked positive co-relation means that there is a trend which shows positive relation between education attained and salary. But there is always a "possibility" that 1 or 2 points in the trend graph do not fall on average trend line.

C can be rejected because no clear relation between education and chess proficiency. And use of word "usually" makes the option worse.
B is true, for the reason of "possibility"stated above.

In social science research, "highest education level attained" would refer to the most advanced grade or degree achieved by an individual—for some individuals, it may be a grade in grade school, and for other individuals, it may be a Bachelor's Degree, a Master's Degree, or Ph.D. (which is considered the highest education level). A recent study has shown a strong correlation between highest education level attained and proficiency in chess. Another result, studied at many points throughout the 20th century, shows a marked positive correlation between highest education level attained and income level.

Assuming the statements above are true, what conclusion can be drawn from them?

A) If one practices chess enough to raise one's proficiency, one has a good chance of raising one's income level.
The given correlation in argument is mistaken for causality. people who play chess may have good income level and vice-versa but chess does not ensure income level.

B) It is possible that a person who has attained only a sixth grade level of education could earn more than a person who has a Ph. D.
(This is a perfect example of inference with no exaggeration.)

C) If Jane has a Ph. D., and Chris has not finished his undergraduate degree, then Jane will usually beat Chris in chess.
(We cannot guarantee anything such as this particular case even if there is a possibility)

D) The average salary for people who have completed three-year Master's Programs is higher than the average salary of people who have completed two-year Master's Programs.
(we cannot be so sure although there is a possibility)

E) An individual's proficiency at chess rises consistently during that individual's years of school, and levels off once that individual has finished her years of formal education.
(This is an extreme case of inference. what if the person does not play chess at all.)

my two cents :- argument says "Ph.D. (which is considered the highest education level)." and another point "positive correlation between highest education level attained and income level."
but at the same time argument mentioned that "for some individuals, ..." which is i guess the main point. For some
highest education is related to highest degree for some it is highest grade
but yes highest education is positively related to income.
B is indeed the right answer.
because person earning more may have 6th grade education but not phd. Still he earns more.

On C , which is too extrem because of "usually"

Experts please explain

Though i am still in the process of 'digesting' the logic behind the correct answer, the OE has definitely made me realise a few points that i have been overlooking all this while.
1) Correlation DOES NOT imply Causality
2) Correlation is a generic trend, it doesnt warranty specific outcomes (avoid this for inferences mostly).
Here's a link for more on this- https://magoosh.com/gmat/2013/gmat-criti ... pulations/

Below is the OE from Magoosh.

(B) is the credited answer. In the population view, higher education level is correlated, on average, with higher income, but this doesn't apply at the individual level. Indeed, despite the overall population pattern, it would certainly be possible to find someone with a sixth-grade education who struck a fortune and therefore was richer than many people with Ph.D.'s. It wouldn't be likely, if we picked a random person with a sixth-grade education and a random Ph.D., but it would be possible.

(A) plays on the correlation-causality fallacy. Chess is correlated with education level, but doesn't "cause" education level. Education level is correlated with income, but doesn't singlehandedly "cause" income. There is no reason to conclude what (A) says.

(C) plays on the fallacy of scope. Yes, there's a correlation in the overall population, but just because Jane has a Ph.D. and Chris doesn't even have an B.A., we can't automatically assume that Jane is better at chess.

(D) is tricky. The "education level" variable implied the idea of "length of time being educated", but that's not explicitly part of the variable. The question very clearly says one of the last three categories is "Master's Degree", so all master's degree would fall into this category, irrespective of the duration of the program.

(E) also plays on the correlation-causality fallacy. In general, folks who are more proficient at chess are more likely to pursue higher degrees, but it's not that step-by-step in their year-by-year learning process, they are steadily learning more about chess. In other words, the education does not strictly "cause" the proficiency in chess.

Nothing in the passage indicates whether it is possible or not possible that a person who has attained only a sixth grade level of education could earn more than a person who has a Ph. D.:It is possible not because something in the passage confirms it, but because nothing in the passage does not eliminate the possibility.

In choice C, Statement is made lighter by using the word "Usually". If this word were not there, I would not have selected choice C. But, this word gave me a second thought that it is not always that he will win.. moreover, the evidence is given in favor of this choice.

How to avoid this trap? I still did not find any solid reason to reject this choice. Please help !

In choice C, Statement is made lighter by using the word "Usually". If this word were not there, I would not have selected choice C. But, this word gave me a second thought that it is not always that he will win.. moreover, the evidence is given in favor of this choice.

How to avoid this trap? I still did not find any solid reason to reject this choice. Please help !

Your argument would be valid if instead of Jane and Chris, "randomly selected person" were mentioned - C could then be concluded: Usually a randomly selected person who has a Ph.D. would beat a randomly selected person who has not finished undergraduate studies.

But the way option C is worded, it implies that Jane and Chris are two particular persons, and Jane is definitely better than Chris in playing chess - under usual circumstances Jane will (definitely) beat Chris. This statement, though likely, cannot be concluded because it is possible that (a particular person) Jane, in spite of having a higher education, does not play better chess than (another particular person) Chris.

Thanks sayantanc2k for detailed explanation. It really helped.

this problem is forcing me to change my mindset of approaching CRs....there is nothing in the passage that points out the kind of correlation expressed in the OA.

I agree with you in this - please refer to my post above:

in-social-science-research-193831.html#p1785269

In my opinion, such reasoning is not expected in the real test.

Hi Experts,

I chose "C" as the word "usually" melts down the argument and it isnt strong enough to factor in other reasons as well.

How come "B" is the right answer?

Regards,
Honneeey

Used to crave for "Likes" in former years, Now running behind "Kudos". :D

Your query has already been discussed here:
https://gmatclub.com/forum/in-social-sc ... l#p1785284

B is also wrong. I will explain why:

Argument gives that there is a correlation between higher education and income.
However there is nothing in the argument that express that could be possible someone have lower education and higher income

A correlation could be 100%, and is still possible that everybody that have higher education also have higher income, thus the B is wrong, is not a fact that could be concluded with the premises if you can have a negative case.

B would be correct if the question stated "in most of times higher educations result in higher incomes" or even "usually higher educations..." so you can expect would be exceptions.

(B) is the correct answer. In the population view, higher education level is correlated, on average, with higher income, but this doesn't apply at the individual level. Indeed, despite the overall population pattern, it would certainly be possible to find someone with a sixth-grade education who struck a fortune and therefore was richer than many people with Ph.D.'s. It wouldn't be likely, if we picked a random person with a sixth-grade education and a random Ph.D., but it would be possible.

(A) plays on the correlation-causality fallacy. Chess is correlated with education level, but doesn't "cause" education level. Education level is correlated with income, but doesn't singlehandedly "cause" income. There is no reason to conclude what (A) says.

(C) plays on the fallacy of scope. Yes, there's a correlation in the overall population, but just because Jane has a Ph.D. and Chris doesn't even have an B.A., we can't automatically assume that Jane is better at chess.

(D) is tricky. The "education level" variable implied the idea of "length of time being educated", but that's not explicitly part of the variable. The question very clearly says one of the last three categories is "Master's Degree", so all master's degree would fall into this category, irrespective of the duration of the program.

(E) also plays on the correlation-causality fallacy. In general, folks who are more proficient at chess are more likely to pursue higher degrees, but it's not that step-by-step in their year-by-year learning process, they are steadily learning more about chess. In other words, the education does not strictly "cause" the proficiency in chess.


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Also It is important to notice:

Correlation does not imply causality. This is tricky, because of course, the inverse is true: causality does, in fact, imply correlation. If A reliably causes B, then whenever you find A, you will be likely to find B. For example, smoking causes a large collection of undesirable conditions, including lung cancer, emphysema, and heart disease, and sure enough, it is highly correlated with each of these.

The catch, though, is that two things can be correlated and A does not cause B. For example, A & B would be highly correlated if they were the common response to the same underlying cause: for example, beer sales and ice cream sales are highly correlated, not because folks like having beer a la mode, but because another cause, hot weather, drives both. There are other more complicated relationships we will not explore here in which A & B would tend to show up together — that is, they would be correlated — but each would not be a relationship in which one is causing the other.

Another way to say this is: correlation is relatively easy to demonstrate. All you need is broad sociological or epidemiological data, and you can show correlation. Anyone with a data set and statistical software can demonstrate correlation. By contrast, demonstrating causality is often a major scientific achievement, sometimes worthy of a Nobel Prize. To demonstrate that A causes B, one would need to show dozens and dozens of conditions are met, only the most elementary of which is that A is correlated with B.

Official Explanation:

This question presents two correlations, education level with chess, and education level with income. We would do well to remember the two errors discussed in this blog.

(B) is the credited answer. In the population view, higher education level is correlated, on average, with higher income, but this doesn't apply at the individual level. Indeed, despite the overall population pattern, it would certainly be possible to find someone with a sixth-grade education who struck a fortune and therefore was richer than many people with Ph.D.'s. It wouldn't be likely, if we picked a random person with a sixth-grade education and a random Ph.D., but it would be possible.

(A) plays on the correlation-causality fallacy. Chess is correlated with education level, but doesn't "cause" education level. Education level is correlated with income, but doesn't singlehandedly "cause" income. There is no reason to conclude what (A) says.

(C) plays on the fallacy of scope. Yes, there's a correlation in the overall population, but just because Jane has a Ph.D. and Chris doesn't even have an B.A., we can't automatically assume that Jane is better at chess.

(D) is tricky. The "education level" variable implied the idea of "length of time being educated", but that's not explicitly part of the variable. The question very clearly says one of the last three categories is "Master's Degree", so all master's degree would fall into this category, irrespective of the duration of the program.

(E) also plays on the correlation-causality fallacy. In general, folks who are more proficient at chess are more likely to pursue higher degrees, but it's not that step-by-step in their year-by-year learning process, they are steadily learning more about chess. In other words, the education does not strictly "cause" the proficiency in chess.