A recent report determined that although only three percent of drivers on Maryland highways equipped their vehicles with radar detectors, thirty-three percent of all vehicles ticketed for exceeding the speed limit were equipped with them. Clearly, drivers who equip their vehicles with radar detectors are more likely to exceed the speed limit regularly than are drivers who do not.
The conclusion drawn above depends on which of the following assumptions?
(A) Drivers who equip their vehicles with radar detectors are less likely to be ticketed for exceeding the speed limit than are drivers who do not.
(B) Drivers who are ticketed for exceeding the speed limit are more likely to exceed the speed limit regularly than are drivers who are not ticketed.
(C) The number of vehicles that were ticketed for exceeding the speed limit was greater than the number of vehicles that were equipped with radar detectors.
(D) Many of the vehicles that were ticketed for exceeding the speed limit were ticketed more than once in the time period covered by the report.
(E) Drivers on Maryland highways exceeded the speed limit more often than did drivers on other state highways not covered in the report.
OA is B. What's wrong with D?
Maryland- Assumption Ques!
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Hi joyseychow,joyseychow wrote:A recent report determined that although only three percent of drivers on Maryland highways equipped their vehicles with radar detectors, thirty-three percent of all vehicles ticketed for exceeding the speed limit were equipped with them. Clearly, drivers who equip their vehicles with radar detectors are more likely to exceed the speed limit regularly than are drivers who do not.
The conclusion drawn above depends on which of the following assumptions?
(A) Drivers who equip their vehicles with radar detectors are less likely to be ticketed for exceeding the speed limit than are drivers who do not.
(B) Drivers who are ticketed for exceeding the speed limit are more likely to exceed the speed limit regularly than are drivers who are not ticketed.
(C) The number of vehicles that were ticketed for exceeding the speed limit was greater than the number of vehicles that were equipped with radar detectors.
(D) Many of the vehicles that were ticketed for exceeding the speed limit were ticketed more than once in the time period covered by the report.
(E) Drivers on Maryland highways exceeded the speed limit more often than did drivers on other state highways not covered in the report.
OA is B. What's wrong with D?
When working on arguments you should ask yourself what the evidence establishes and what the author is trying to prove (conclusion). The author must support every idea in the conclusion, so a good place to start is to ask: "what ideas are in the conclusion that are not in the evidence." If there are new ideas in the conclusion that were not in the evidence, then that must mean that he is assuming something about those new ideas.
Then ask: "what ideas are in the evidence that are not in the conclusion?" The assumption will bridge the gap between these differentially present ideas. This is the classic Kaplan method.
Applied here:
The evidence establishes that a disproportionate number of vehicles ticked for speeding are equipped with radar devices (3% of all cars are equipped but 33% of all cars ticketed for speeding are equipped with radar).
The conclusion is radar-equipped cars are more likely to exceed the speed limit regularly (than do cars that are not radar-equipped).
One thing making identification of the assumption difficult here is that it makes common sense. But we know that the evidence is not good enough to establish the conclusion. But applying the method here makes this question very easy.
What is the idea in the conclusion that is not in the evidence?..."more likely to exceed the speed limit regularly".
And what is the idea in the evidence that is not in the conclusion? "being ticketed for speeding"
{The idea of radar-equippedness is in both the conclusion and evidence, so we ignore it}
Now, let's bridge the gap: "being ticketed for speeding means more likely to exceed the speed limit regularly."
Now we aggressively scan for a match. We can ignore any choice that doesn't have both of these terms.
Then, choice B is correct.
We can also use the Kaplan denial test. The question is asking for an assumption on which the argument depends. That means that without that assumption, the argument will fail to hold. So let's deny choice B and see what happens to the argument. ..So what happens if those who are ticketed for speeding are actually LESS likely to exceed the speed limit regularly? Then, clearly the argument will fall apart. Because, in the absence of choice B the argument fails to hold, choice B is an assumption on which the argument depends.
Choice D is wrong because in order for the argument to hold, the author need not assume that they were ticketed multiple times. What happens to the argument if we deny D? Many of the vehicles were ticked ONLY once....doesn't matter, they were still ticketed, and the argument does not fall apart .
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Hi geemat,geemat wrote:@testluv
lets say there are 100 cars => 3 have radar detector
now 3 cars are being ticketed => 1 have radar detector
in the abaove scenario. how does B hold?
Well, it can actually be the case that you exceed the speed limit on a regular basis but for some reason (maybe you're lucky), you always seem to evade being ticketed. Perhaps these are the non-radar-owners, and perhaps that's why they don't end up getting ticketed much (even though they are speeding on a regular basis).
It can also be the case that you don't exceed the speed limit very often but because you drive (on the highways) so frequently, you end up getting caught (and then ticketed) more. Perhaps these are the radar-owners.
So his argument, although it makes some common sense, is not necessarily correct. Remember that on GMAT arguments, the evidence will never be sufficient on its own to establish the conclusion. You can think of the assumption as being the missing piece of evidence.
Also, the issue isn't whether he is actually correct in his conclusion or not (it does not matter, he may be right, he may be wrong). Instead, it is the arguer's procession from evidence to conclusion that we are interested in.
I wasn't 100% sure if that was what you were asking about though, so if I haven't answered your question, just let me know.
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Thanks!! Understand it better knowTestluv wrote:Hi joyseychow,joyseychow wrote:A recent report determined that although only three percent of drivers on Maryland highways equipped their vehicles with radar detectors, thirty-three percent of all vehicles ticketed for exceeding the speed limit were equipped with them. Clearly, drivers who equip their vehicles with radar detectors are more likely to exceed the speed limit regularly than are drivers who do not.
The conclusion drawn above depends on which of the following assumptions?
(A) Drivers who equip their vehicles with radar detectors are less likely to be ticketed for exceeding the speed limit than are drivers who do not.
(B) Drivers who are ticketed for exceeding the speed limit are more likely to exceed the speed limit regularly than are drivers who are not ticketed.
(C) The number of vehicles that were ticketed for exceeding the speed limit was greater than the number of vehicles that were equipped with radar detectors.
(D) Many of the vehicles that were ticketed for exceeding the speed limit were ticketed more than once in the time period covered by the report.
(E) Drivers on Maryland highways exceeded the speed limit more often than did drivers on other state highways not covered in the report.
OA is B. What's wrong with D?
When working on arguments you should ask yourself what the evidence establishes and what the author is trying to prove (conclusion). The author must support every idea in the conclusion, so a good place to start is to ask: "what ideas are in the conclusion that are not in the evidence." If there are new ideas in the conclusion that were not in the evidence, then that must mean that he is assuming something about those new ideas.
Then ask: "what ideas are in the evidence that are not in the conclusion?" The assumption will bridge the gap between these differentially present ideas. This is the classic Kaplan method.
Applied here:
The evidence establishes that a disproportionate number of vehicles ticked for speeding are equipped with radar devices (3% of all cars are equipped but 33% of all cars ticketed for speeding are equipped with radar).
The conclusion is radar-equipped cars are more likely to exceed the speed limit regularly (than do cars that are not radar-equipped).
One thing making identification of the assumption difficult here is that it makes common sense. But we know that the evidence is not good enough to establish the conclusion. But applying the method here makes this question very easy.
What is the idea in the conclusion that is not in the evidence?..."more likely to exceed the speed limit regularly".
And what is the idea in the evidence that is not in the conclusion? "being ticketed for speeding"
{The idea of radar-equippedness is in both the conclusion and evidence, so we ignore it}
Now, let's bridge the gap: "being ticketed for speeding means more likely to exceed the speed limit regularly."
Now we aggressively scan for a match. We can ignore any choice that doesn't have both of these terms.
Then, choice B is correct.
We can also use the Kaplan denial test. The question is asking for an assumption on which the argument depends. That means that without that assumption, the argument will fail to hold. So let's deny choice B and see what happens to the argument. ..So what happens if those who are ticketed for speeding are actually LESS likely to exceed the speed limit regularly? Then, clearly the argument will fall apart. Because, in the absence of choice B the argument fails to hold, choice B is an assumption on which the argument depends.
Choice D is wrong because in order for the argument to hold, the author need not assume that they were ticketed multiple times. What happens to the argument if we deny D? Many of the vehicles were ticked ONLY once....doesn't matter, they were still ticketed, and the argument does not fall apart .
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Same here. Funny thing is that I still don't get the problem.Vipulvp wrote:@Testluv: Thanks for the explanation. I don't know why, but out of the 120 odd questions of the OG-12, I found this question the toughest. By a long way.
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very hard. it take me 1 hour to get the following:
I call this question CR QUESTION WITH MATH
suppose there are 100 person, 3 have radar, 97 have no radar
suppose there are 3 persons are ticketed, 1 of them have radar, and 2 of them have no radar.
or suppose there are 9 persons are ticketed, 3 of them have radar, and 6 of them have no radar
we can not suppose there are 12 persons are ticketed because there will be 4 person have radar-this contradict the fact that there are 3 person with radar.
so: there are 3 person with radar and 1 of them is ticketed
there are 97 persons without radar and 2 of them are ticket.
conclusion is that person with radar are more likely to be ticketed.
sound very nice.
COMING TO THIS POINT IS A GREAT STEP ALREADY.
we need to come to a hard-to-see assumption . One step harder
we need to assume a very simple thing but hard to see. the simple thing is that all the number above reflect the fact. that mean person who are ticketed frequently are persons who are ticket frequently. negation of this assumption means all the number 3 person, 97 person, 3 person and 6 person are correct number
PLEASE, GIVE YOUR IDEA ON MY EXPLANATION.
I call this question CR QUESTION WITH MATH
suppose there are 100 person, 3 have radar, 97 have no radar
suppose there are 3 persons are ticketed, 1 of them have radar, and 2 of them have no radar.
or suppose there are 9 persons are ticketed, 3 of them have radar, and 6 of them have no radar
we can not suppose there are 12 persons are ticketed because there will be 4 person have radar-this contradict the fact that there are 3 person with radar.
so: there are 3 person with radar and 1 of them is ticketed
there are 97 persons without radar and 2 of them are ticket.
conclusion is that person with radar are more likely to be ticketed.
sound very nice.
COMING TO THIS POINT IS A GREAT STEP ALREADY.
we need to come to a hard-to-see assumption . One step harder
we need to assume a very simple thing but hard to see. the simple thing is that all the number above reflect the fact. that mean person who are ticketed frequently are persons who are ticket frequently. negation of this assumption means all the number 3 person, 97 person, 3 person and 6 person are correct number
PLEASE, GIVE YOUR IDEA ON MY EXPLANATION.
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SORRY, I CORRECT WRITING.
we need to assume a very simple thing but hard to see. the simple thing is that all the number above reflect the fact. PERSON WHO ARE TICKETED FREQUENTLY ARE PERSONS WHO ARE VIOLATE FREQUENTLY. negation of this assumption means all the number 3 person, 97 person, 3 person and 6 person are correct number
we need to assume a very simple thing but hard to see. the simple thing is that all the number above reflect the fact. PERSON WHO ARE TICKETED FREQUENTLY ARE PERSONS WHO ARE VIOLATE FREQUENTLY. negation of this assumption means all the number 3 person, 97 person, 3 person and 6 person are correct number
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SORRY, I CORRECT WRITING.
we need to assume a very simple thing but hard to see. the simple thing is that all the number above reflect the fact. PERSON WHO ARE TICKETED FREQUENTLY ARE PERSONS WHO ARE VIOLATE FREQUENTLY. negation of this assumption means all the number 3 person, 97 person, 3 person and 6 person are INCORRECT number and of course, conclusion falls apart.
we need to assume a very simple thing but hard to see. the simple thing is that all the number above reflect the fact. PERSON WHO ARE TICKETED FREQUENTLY ARE PERSONS WHO ARE VIOLATE FREQUENTLY. negation of this assumption means all the number 3 person, 97 person, 3 person and 6 person are INCORRECT number and of course, conclusion falls apart.