Question Type:
Weaken
Stimulus Breakdown:
Conclusion: Less likely to be hurt in an accident if you drive large vs. small car.
Evidence: From study of 10,000 people who were in an accident, low % of people driving large cars were injured while high % of people driving small automobiles were injured.
Answer Anticipation:
We ultimately need to argue that you're more likely to be injured in an auto accident if you drive a LARGE car. In this study, a lower % of people driving large cars were injured. Is there some way that this study could be flawed / incomplete / misleading? A popular trend on LSAT is to present a statistic that only looks at one segment of a population. This study only looks at people who WERE involved in accidents. It doesn't look at people who weren't involved in accidents. However the conclusion is just about driving large car vs. driving small car. If the conclusion were phrased, "Thus, if you are involved in an accident, you are less likely to be injured in a large car" then it would be more in line with the study. The study doesn't give us information about people who weren't in auto accidents. Maybe small cars are way less likely overall to be involved in an accident. IF you get into an accident in a small car, you're more likely to be injured. But that wouldn't mean that IF you drive a small car, your more likely to be injured in an auto accident.
Correct Answer:
D
Answer Choice Analysis:
(A) This does nothing to to differentiate large vs. small
(B) This doesn't really help us address large vs. small in terms of injury / acccident safety.
(C) Medium is irrelevant, since the conclusion is just comparing small to large.
(D) Bingo! This is getting at the leftover statistical group we thought about. If only 10% of large car drivers get injured during accidents, but 80% of large car drivers get into accidents, then 8 out of every 100 large car drivers get injured in an accident. Meanwhile, if 50% of small car drivers get injured during accidents, but only 10% of small car drivers get into accidents, then 5 out of every 100 small car drivers get injured in an accident. If all this math is too complicated to understand, just remember to prephrase the anti-conclusion: "one is MORE likely to be injured in an auto accident if one drives a large car". This answer helps us argue that point.
(E) This does nothing to to differentiate large vs. small
Takeaway/Pattern: Statistics are famous for providing incomplete, distorted snapshots of reality. LSAT frequently phrases a statistic in the evidence in a way that only addresses part of a situation. Then the conclusion speaks to the ENTIRE situation, leaving us to wonder about the missing piece. One question says that "our weather predictions are the best, because WHEN we predict rain, we're correct more often than any other station." Okay, but what about when you DON'T predict rain? Are you STILL correct more often than any other station?
#officialexplanation
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Q13 - A recent study of 10,000
Would you please go over this question? Is there any flaw in the argument?
Thanks!
Thanks!
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- bbirdwell
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Atticus Finch
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Re: Q13 - A recent study of 10,000
This argument is all about breaking down the sub-groups of the 10,000 people. You must be very watchful of the use of percentages, always asking yourself "percent of who?"
So, here are the facts:
10,000 people were involved in accidents. How many were driving? We don't know. How many were driving large cars? We don't know. How many were driving small cars? We don't know.
Of those driving large cars, a low % were injured.
Of those driving small cars, a high % were injured.
And here is the conclusion:
driving a large car makes you less likely to be injured in an accident.
The flaw here is that we can't say anything about likelihood unless we know more about the relative proportion of large-car accidents to small-car accidents. For example, consider these numbers:
10,000 accidents
9,999 involved people driving large cars. A low % of these were injured. Let's say, 10%? That's 999 out of 10,000.
1 involved a small car, and a high % were injured. Let's say 100%. That's 1 out of 10,000.
See how many ways we can manipulate these numbers? Furthermore, in order to draw a conclusion about the actual likelihood of being in an accident, we'd need to know what % of all accidents involve small and large cars.
This is how (D) works to weaken. It posits that the large autos are far more likely to be in an accident in the first place. In other words, a much higher % of accidents involve large cars. And, as you can see in the example above, a low % of a high % of the total can be a greater number than a high % of a low% of the total.
So, here are the facts:
10,000 people were involved in accidents. How many were driving? We don't know. How many were driving large cars? We don't know. How many were driving small cars? We don't know.
Of those driving large cars, a low % were injured.
Of those driving small cars, a high % were injured.
And here is the conclusion:
driving a large car makes you less likely to be injured in an accident.
The flaw here is that we can't say anything about likelihood unless we know more about the relative proportion of large-car accidents to small-car accidents. For example, consider these numbers:
10,000 accidents
9,999 involved people driving large cars. A low % of these were injured. Let's say, 10%? That's 999 out of 10,000.
1 involved a small car, and a high % were injured. Let's say 100%. That's 1 out of 10,000.
See how many ways we can manipulate these numbers? Furthermore, in order to draw a conclusion about the actual likelihood of being in an accident, we'd need to know what % of all accidents involve small and large cars.
This is how (D) works to weaken. It posits that the large autos are far more likely to be in an accident in the first place. In other words, a much higher % of accidents involve large cars. And, as you can see in the example above, a low % of a high % of the total can be a greater number than a high % of a low% of the total.
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- pinkdatura
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Re: PT59, S3, Q13 - A recent study of 10,000 people who were
Thank you for the explanation, bbirdwell. 
Would you pls see if I haven't mis-understood your explanation?
the likelihood of large car injured in accident=the likelihood of large car involved in accident X the likelihood of injured rate once involved in accident?
Sorry I am bad at math
Would you pls see if I haven't mis-understood your explanation?
the likelihood of large car injured in accident=the likelihood of large car involved in accident X the likelihood of injured rate once involved in accident?
Sorry I am bad at math
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Atticus Finch
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Re: PT59, S3, Q13 - A recent study of 10,000 people who were
Pretty much. I don't know how to mathematically calculate it. I just know the calculation must include those two things: likelihood of a large car being in an accident in the first place, and the then likelihood of being injured.
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Vinny Gambini
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Re: Q13 - A recent study of
Firstly, my PrepTest may be wonky, but this should be under S3, while the Q13 in S3 should be here, in S2.
My question about this problem is that they talk about the likelihood of injury when one drives a large car vs a small car. In that case, even if large cars are far more likely to be involved in an accident if they are not injured, then it doesn't increase the likelihood that they will get injured in an automobile accident.
Using your example, even if more total people get injured while driving a large car and even if small cars get into accidents less frequently, if the small car passengers get injured more frequently than large cars (in your example, guaranteed), then the argument's conclusion is true- one is less likely to be injured in an automobile accident if one drives a large car rather than a small car. According to the stimulus, since the large cars will always have a low percentage of injury while small cars will always have a high percentage, doesn't that make small cars more likely to involve injury regardless of the proportion of small to large cars?
I chose (E) and looking back, since it affects both large and small cars, it is less likely to be the right answer. I just couldn't get over how (D) talks about frequency, when the stimulus is talking about the likelihood of injury. Is it because it draws into question how representative the sample may be?
My question about this problem is that they talk about the likelihood of injury when one drives a large car vs a small car. In that case, even if large cars are far more likely to be involved in an accident if they are not injured, then it doesn't increase the likelihood that they will get injured in an automobile accident.
Using your example, even if more total people get injured while driving a large car and even if small cars get into accidents less frequently, if the small car passengers get injured more frequently than large cars (in your example, guaranteed), then the argument's conclusion is true- one is less likely to be injured in an automobile accident if one drives a large car rather than a small car. According to the stimulus, since the large cars will always have a low percentage of injury while small cars will always have a high percentage, doesn't that make small cars more likely to involve injury regardless of the proportion of small to large cars?
I chose (E) and looking back, since it affects both large and small cars, it is less likely to be the right answer. I just couldn't get over how (D) talks about frequency, when the stimulus is talking about the likelihood of injury. Is it because it draws into question how representative the sample may be?
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- ManhattanPrepLSAT1
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Atticus Finch
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Re: Q13 - A recent study of
I think I might see where answer choice (D) is failing you.
The reason why it's okay for answer choice (D) to discuss the relative likelihood of small and large cars to be involved in an accident is the way the conclusion relates to the evidence.
The evidence discusses the likelihood of injury in an accident. The conclusion discusses the likelihood of being injured when driving a either a large or small car. That slight shift in what the likelihood of injury is from suggests that the frequency with which large and small cars are involved in accidents is relevant.
Make sense?
pathosj Wrote:I just couldn't get over how (D) talks about frequency, when the stimulus is talking about the likelihood of injury.
The reason why it's okay for answer choice (D) to discuss the relative likelihood of small and large cars to be involved in an accident is the way the conclusion relates to the evidence.
The evidence discusses the likelihood of injury in an accident. The conclusion discusses the likelihood of being injured when driving a either a large or small car. That slight shift in what the likelihood of injury is from suggests that the frequency with which large and small cars are involved in accidents is relevant.
Make sense?
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Vinny Gambini
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Re: Q13 - A recent study of
The evidence does not discuss the likelihood of an injury in an accident without reference to the size of the car. That is to say, the size of the car is conveyed by the evidence and the conclusion refers to a higher chance of being injured if one drives a large car rather than a small car.
This is the stimulus verbatim:
"A recent study of 10,000 people who were involved in automobile accidents found that a low percentage of those driving large automobiles at the time of their accidents were injured, but a high percentage of those who were driving small automobiles at the time of their accidents were injured. Thus, one is less likely to be injured in an automobile accident if one drives a large car rather than a small car."
10,000 people were involved in an accident (how many injured vs non-injured is unknown, how many large car drivers vs small car drivers is unknown). This is the evidence and the discussed likelihood of injury does not exclude reference to large and small cars. In fact, it specifically states that the percentage of injuries for large cars is low (which I take as less than 50%), whereas the percentage of injured for small cars is high (which I take as higher than 50%). Guaranteed.
The conclusion states that "one is less likely to be injured in an automobile accident if one drives a large car rather than a small car". So, what does it matter if large cars get into more accidents?
I'll illustrate my problem with the answer choice in what I believe to be an equivalent analogy. A study in which 10,000 people ate hotdogs revealed that a low percentage of skinny people suffered a heart attack, but a high percentage of fat people suffered a heart attack. Thus, one is less likely to have a heart attack if one is skinny rather than fat.
The correct answer choice that would equivocally say that skinny people are far more likely to eat hotdogs doesn't really weaken anything for me. Unless it would be to state that perhaps eating more hotdogs prevents heart attacks or ,in terms of the original stimulus, that getting into more accidents prevents injury (highly unlikely).
This question and answer makes me sad.
This is the stimulus verbatim:
"A recent study of 10,000 people who were involved in automobile accidents found that a low percentage of those driving large automobiles at the time of their accidents were injured, but a high percentage of those who were driving small automobiles at the time of their accidents were injured. Thus, one is less likely to be injured in an automobile accident if one drives a large car rather than a small car."
10,000 people were involved in an accident (how many injured vs non-injured is unknown, how many large car drivers vs small car drivers is unknown). This is the evidence and the discussed likelihood of injury does not exclude reference to large and small cars. In fact, it specifically states that the percentage of injuries for large cars is low (which I take as less than 50%), whereas the percentage of injured for small cars is high (which I take as higher than 50%). Guaranteed.
The conclusion states that "one is less likely to be injured in an automobile accident if one drives a large car rather than a small car". So, what does it matter if large cars get into more accidents?
I'll illustrate my problem with the answer choice in what I believe to be an equivalent analogy. A study in which 10,000 people ate hotdogs revealed that a low percentage of skinny people suffered a heart attack, but a high percentage of fat people suffered a heart attack. Thus, one is less likely to have a heart attack if one is skinny rather than fat.
The correct answer choice that would equivocally say that skinny people are far more likely to eat hotdogs doesn't really weaken anything for me. Unless it would be to state that perhaps eating more hotdogs prevents heart attacks or ,in terms of the original stimulus, that getting into more accidents prevents injury (highly unlikely).
This question and answer makes me sad.
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- ManhattanPrepLSAT1
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Atticus Finch
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Re: Q13 - A recent study of
The risk of being injured while driving a large car is a product both of how often large cars are involved in accidents, and how often injuries occur in large cars that are involved in accidents. The stimulus provides us with the frequency that injuries occur in accidents involving large cars, but it does not specify the rate that large cars are involved in accidents.
If it were true that large cars were much more likely to be involved in accidents, then the low injury rate for large cars would be dragged back up by the high frequency of accidents themselves. I can totally see why this is challenging, I just spent a long time looking at this one, but information on the frequency that small and large cars get into accidents is relevant to the conclusion about the likelihood of people driving small and large cars getting injured.
Let me know if I need to try explaining this anther way!
If it were true that large cars were much more likely to be involved in accidents, then the low injury rate for large cars would be dragged back up by the high frequency of accidents themselves. I can totally see why this is challenging, I just spent a long time looking at this one, but information on the frequency that small and large cars get into accidents is relevant to the conclusion about the likelihood of people driving small and large cars getting injured.
Let me know if I need to try explaining this anther way!
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Vinny Gambini
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Re: Q13 - A recent study of
Alright, I think I understand it now. In the range of how severe accidents can be, small and large cars can still be equal in likelihood of injury. The skewed percentages can be a result of large cars getting into more accidents than small cars without altering this likelihood.
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Vinny Gambini
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Re: Q13 - A recent study of 10,000
I mistook "one is less likely to be injured in an automobile accident if..." for"in an automobile accident, one is less likely to be injured, if...".
Can my mistaking be justified?
If it can, than A would be the answer because the study might not be representative for the case in general because small cars can drive faster than usual if the speed limit is very high.
Can my mistaking be justified?
If it can, than A would be the answer because the study might not be representative for the case in general because small cars can drive faster than usual if the speed limit is very high.
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Jackie Chiles
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Re: Q13 - A recent study of 10,000
I d vote for A as well.
I think this question's logic itself is poor. The conclusion should be "Thus, fewer people are injured when driving a large car from the accidents in the study." , then will make D a legitimate correct answer.
When the conclusion is about likelihood (possibility) in any accident (the conclusion says, "in an automobile accident" = in any auto accident), which is not about the factual number of injured people, the high possibility of injury for small car drivers is because of the high speed limit totally makes sense.
What I learned from this question is:
1. Some of the LSAT questions are poorly written.
2. We should not take the answers too strictly according to the logic, bc the questions are poorly written
3. In order to get good score, we need to figure out what kind of answers that LSAC is really expecting, even though the questions are poorly written. It's like when a women asks you is she has gained weight, the answer choices are:
A) Yes
B) No
C) I don't know
D) Possible
E) Impossible
But the correct answer is B for you to get that 1 point.
So choose B to get that point once you know what they are expecting to hear although the logic is poor. Don't argue, just make the wise choice.
Make sense?
I think this question's logic itself is poor. The conclusion should be "Thus, fewer people are injured when driving a large car from the accidents in the study." , then will make D a legitimate correct answer.
When the conclusion is about likelihood (possibility) in any accident (the conclusion says, "in an automobile accident" = in any auto accident), which is not about the factual number of injured people, the high possibility of injury for small car drivers is because of the high speed limit totally makes sense.
What I learned from this question is:
1. Some of the LSAT questions are poorly written.
2. We should not take the answers too strictly according to the logic, bc the questions are poorly written
3. In order to get good score, we need to figure out what kind of answers that LSAC is really expecting, even though the questions are poorly written. It's like when a women asks you is she has gained weight, the answer choices are:
A) Yes
B) No
C) I don't know
D) Possible
E) Impossible
But the correct answer is B for you to get that 1 point.
So choose B to get that point once you know what they are expecting to hear although the logic is poor. Don't argue, just make the wise choice.
Make sense?
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Atticus Finch
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Re: Q13 - A recent study of 10,000
Well, I think you are (understandably—it's normal) frustrated with the test, but I can't agree with this assessment. 
Learning logic actually is the way to excel on the test, and the questions are written quite precisely overall, although of course there is the occasional bad egg. This one isn't too bad, actually. It's a weaken question, and via the logic Brian laid out, (D) weakens it best. (A) doesn't weaken it. It doesn't matter if (A) is true or not in terms of whether the conclusion or not is still valid.
Were most accidents in the study in areas with high speed limits? If yes, okay, it still seems like it's safer to be in a big car.
Were most accidents in the study in areas with high speed limits? If no, so what? Based on the finding, it still seems like it's safer to be in a big car.
Keep plugging away on the logic. Don't settle for just deciding a question is poorly written...it's much rarer than you think.
Learning logic actually is the way to excel on the test, and the questions are written quite precisely overall, although of course there is the occasional bad egg. This one isn't too bad, actually. It's a weaken question, and via the logic Brian laid out, (D) weakens it best. (A) doesn't weaken it. It doesn't matter if (A) is true or not in terms of whether the conclusion or not is still valid.
Were most accidents in the study in areas with high speed limits? If yes, okay, it still seems like it's safer to be in a big car.
Were most accidents in the study in areas with high speed limits? If no, so what? Based on the finding, it still seems like it's safer to be in a big car.
Keep plugging away on the logic. Don't settle for just deciding a question is poorly written...it's much rarer than you think.
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Vinny Gambini
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Re: Q13 - A recent study of 10,000
I still don’t fully understand this question. I suspected that the fact that the study was limited to 10,000 accidents was problematic. Like bbirdwell said, only 1 of those 10,000 accidents could have involved a small car. If that small car driver were injured, then using the resulting data, “100% of those driving small cars are injured” to conclude “small car drivers are more likely to be injured in accidents than drivers of large cars” would be inaccurate to say.
So my question is would this issue be solved if we were told that the group of 10,000 accidents was randomly selected from all accidents? Or would the only way to solve this issue be to have full information of all accidents that involve large and small cars?
This lead to me realize that I don’t understand why (D) would weaken the argument. Lets say large cars are involved in more accidents than small cars. Why would that weaken the conclusion?
I came up with this example:
OF ALL ACCIDENTS --
Large cars: 1000 accidents | 100 injured →10% of large car drivers injured
Small cars: 50 accidents | 25 injured →50% of small car drivers injured
Conclusion: “Thus, large car drivers are less likely to be injured in automobile accidents than small car drivers.”
This makes sense to me! LOL --Okay small cars get in much fewer accidents than large cars but when they do 50% of drivers are injured! I don’t understand what's wrong here. I’m definitely taking “more likely/less likely” to mean frequency/percentage. Is that thinking correct?
Any help would be greatly appreciated!
So my question is would this issue be solved if we were told that the group of 10,000 accidents was randomly selected from all accidents? Or would the only way to solve this issue be to have full information of all accidents that involve large and small cars?
This lead to me realize that I don’t understand why (D) would weaken the argument. Lets say large cars are involved in more accidents than small cars. Why would that weaken the conclusion?
I came up with this example:
OF ALL ACCIDENTS --
Large cars: 1000 accidents | 100 injured →10% of large car drivers injured
Small cars: 50 accidents | 25 injured →50% of small car drivers injured
Conclusion: “Thus, large car drivers are less likely to be injured in automobile accidents than small car drivers.”
This makes sense to me! LOL --Okay small cars get in much fewer accidents than large cars but when they do 50% of drivers are injured! I don’t understand what's wrong here. I’m definitely taking “more likely/less likely” to mean frequency/percentage. Is that thinking correct?
Any help would be greatly appreciated!
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- aiheduru
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Vinny Gambini
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Re: Q13 - A recent study of 10,000
lissethbayona Wrote:I still don’t fully understand this question. I suspected that the fact that the study was limited to 10,000 accidents was problematic. Like bbirdwell said, only 1 of those 10,000 accidents could have involved a small car. If that small car driver were injured, then using the resulting data, “100% of those driving small cars are injured” to conclude “small car drivers are more likely to be injured in accidents than drivers of large cars” would be inaccurate to say.
So my question is would this issue be solved if we were told that the group of 10,000 accidents was randomly selected from all accidents? Or would the only way to solve this issue be to have full information of all accidents that involve large and small cars?
This lead to me realize that I don’t understand why (D) would weaken the argument. Lets say large cars are involved in more accidents than small cars. Why would that weaken the conclusion?
I came up with this example:
OF ALL ACCIDENTS --
Large cars: 1000 accidents | 100 injured →10% of large car drivers injured
Small cars: 50 accidents | 25 injured →50% of small car drivers injured
Conclusion: “Thus, large car drivers are less likely to be injured in automobile accidents than small car drivers.”
This makes sense to me! LOL --Okay small cars get in much fewer accidents than large cars but when they do 50% of drivers are injured! I don’t understand what's wrong here. I’m definitely taking “more likely/less likely” to mean frequency/percentage. Is that thinking correct?
Any help would be greatly appreciated!
Let me take a stab at this... This question was very tricky and most of all, it taught me something about the LSAC I keep on getting reminded but don't always remember: The same flaws on this exams keep recurring, but they have very nifty ways of describing them.
Let's make a simpler version of this argument: (I used to play soccer and I'm a huge Arsenal fan
)Over the 2014-15 Champions League season (35 games)
A higher percentage of English players in the CL scored goals that did Belorussian players in the CL
Therefore, English players are more likely to score goals in the Champions League than Belorussian players.
Now, any soccer fan worth their salt would see numerous things wrong here (and note that the LSAC knows this, that why they made the arguments concerning accidents / more abstract matters/everyday matters - something that I'm sure they have research on that people will drag their assumptions into subconsciously )
The biggest thing here is that, it's well known in the soccer world that Belorussian teams RARELY, if ever make it to the Champions League - and if they do, the maximum amount of teams they can have is - 1! ( It usually alters between BATE Borisov or Dinamo Minsk..but that's irrelevant
) On the contrary, England is guaranteed at least 3 teams in the Group stages, but is allowed 4 (and with the Fair play rule coming up for the next season of the CL, 5 - but again, that's irrelevant ... ) Now, I'm sure by now you see what's wrong with this argument. It's a faulty comparison! if there are 4 English teams in the CL, you would expect more English players to score goals than one Belorussian team full of Belorussian players would. Now however, you need to have a clear picture of the data to make that comparison - (which is what Brain is alluding to by his calculation that he doesn't know (It's a concept called expected probability, but you don't really need to know it) - Basically you need more information on the information of the competition- In particular, you need EQUAL CIRCUMSTANCES between the two. This is the flaw here.
Now, her's whats so crazy about this problem - While I specifically went into the flaw of faulty comparison - We have been taught to doubt the relevance/methodology of all studies on the LSAT. So the flaw could also be described as - "The study is not relevant to the conclusion surmised" Notice my conslusion - I talk about the 2014-15 CL, but then I generalize to all Champions Leagues!!!! - This is WRONG. And if we were given a flaw question that was "easy" - i wouldn't be surprised to see that flaw there. But it's not easy - and it doesn't matter. We have reason to doubt that the study of the 14-15 CL is not relevant to all CL's - and so we should look for the answer that DIRECTLY hits on this ( that why A & C are so tricky- they allude to something being done in the study - but they dont hit on WHAT is being done)
Hopefully this helps most people out.
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Vinny Gambini
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Re: Q13 - A recent study of 10,000
I do not understand this question at all. I'm SO confused! Please help!
It seems like most people are taking the conclusion to mean that large cars are safer than smaller cars. But the conclusion did not say that. It merely says that IN an automobile accident, drive a large car is less likely to get you injured than driving a small car. Then why would D matter? Who cares about under what situation is an accident more likely to happen? We are talking about when accidents have already happened, it is less likely to be injured in a large car than in a small car. It’s like asking a police to choose whether to drive a large car or a small car, given the condition that he/she needs to crash into a criminal’s vehicle. Crashing is a given, not a choice. The only safety concern in this question is which choice is more likely to get you injured rather than more likely to get you into an accident.
Say there are 10,000 accidents in total. (9000 large car accidents and 1000 small car accidents.)
10% of those driving large automobiles at the time of their accidents were injured, and 50% of those driving small cars were injured. So 1000 were injured in an accident when driving large cars and 500 were injured in an accident when driving small cars.
It is incorrect to say that large cars are more likely to be involved in an accident and be injured.
But, what's wrong to say that giving an accident, driving large cars are less likely to be injured than driving a small car?
It seems like most people are taking the conclusion to mean that large cars are safer than smaller cars. But the conclusion did not say that. It merely says that IN an automobile accident, drive a large car is less likely to get you injured than driving a small car. Then why would D matter? Who cares about under what situation is an accident more likely to happen? We are talking about when accidents have already happened, it is less likely to be injured in a large car than in a small car. It’s like asking a police to choose whether to drive a large car or a small car, given the condition that he/she needs to crash into a criminal’s vehicle. Crashing is a given, not a choice. The only safety concern in this question is which choice is more likely to get you injured rather than more likely to get you into an accident.
Say there are 10,000 accidents in total. (9000 large car accidents and 1000 small car accidents.)
10% of those driving large automobiles at the time of their accidents were injured, and 50% of those driving small cars were injured. So 1000 were injured in an accident when driving large cars and 500 were injured in an accident when driving small cars.
It is incorrect to say that large cars are more likely to be involved in an accident and be injured.
But, what's wrong to say that giving an accident, driving large cars are less likely to be injured than driving a small car?
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Vinny Gambini
- Posts: 19
- Joined: July 21st, 2014
Re: Q13 - A recent study of 10,000
Conclusion: large cars are safer relative to small cars
Because they have a lower percentage of people getting hurt.
Weaken: what makes it unlikely that large cars are safer relative to small cars?
D: large cars get into accidents a lot more than smaller cars!
Because they have a lower percentage of people getting hurt.
Weaken: what makes it unlikely that large cars are safer relative to small cars?
D: large cars get into accidents a lot more than smaller cars!
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- hnadgauda
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Elle Woods
- Posts: 77
- Joined: March 31st, 2017
Re: Q13 - A recent study of 10,000
My thoughts on this problem as I did it the third time:
Core:
Out of 10,000 people involved in accidents, a low % of those driving large cars at the time of the accident were injured and a high % of those driving small cars at the time of accidents were injured.--> Driving a large car means that you are less likely to be injured if you get in a car accident compared to your chances of being injured in the same situation if you were driving a small car.
Gap: can't think of any right now...something seems fishy with the percentages though.
A: not relevant to core.
B: core is about what car you are driving when you get in an accident.
C: not relevant
D: this would weaken the argument! Remember % does not equal number!! So if 50% of 100 drivers of large cars got injured in accidents compared to 75% of 25 drivers of small cars--this means that the conclusion is not necessarily true!
E: ...no. out of scope!
Core:
Out of 10,000 people involved in accidents, a low % of those driving large cars at the time of the accident were injured and a high % of those driving small cars at the time of accidents were injured.--> Driving a large car means that you are less likely to be injured if you get in a car accident compared to your chances of being injured in the same situation if you were driving a small car.
Gap: can't think of any right now...something seems fishy with the percentages though.
A: not relevant to core.
B: core is about what car you are driving when you get in an accident.
C: not relevant
D: this would weaken the argument! Remember % does not equal number!! So if 50% of 100 drivers of large cars got injured in accidents compared to 75% of 25 drivers of small cars--this means that the conclusion is not necessarily true!
E: ...no. out of scope!
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- KenM242
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Vinny Gambini
- Posts: 24
- Joined: January 18th, 2018
Re: Q13 - A recent study of 10,000
The explanations above involving numbers and percentages say NOT to get the numbers and the probability mixed up, but I think that's exactly what they're doing.
Assuming (D) is true should not affect the 'already observed' result of less likelihood of being injured while in a large car in an automobile accident. It doesn't matter how you argue it; the result is already out.
The effect of assuming (D) is true is that
1. It is the quite the opposite of findings from the stimulus, and;
2. It is the ultimate statistics with utmost reliability.
1+2 shatter the conclusion stimulus. After all, who is to stay a sample of 10,000 is enough to trust it?
I thought this was one of those weaken questions where the correct answer choice presents a counter evidence with a stronger and more reliable source. In this case since we are to assume that (D) is TRUE, that would be the ultimate counter evidence that outright negates the findings of the said study in the stimulus.
It is very important that if someone thinks I'm wrong, they say it so that I don't mislead anyone with my logic if it is wrong.
Assuming (D) is true should not affect the 'already observed' result of less likelihood of being injured while in a large car in an automobile accident. It doesn't matter how you argue it; the result is already out.
The effect of assuming (D) is true is that
1. It is the quite the opposite of findings from the stimulus, and;
2. It is the ultimate statistics with utmost reliability.
1+2 shatter the conclusion stimulus. After all, who is to stay a sample of 10,000 is enough to trust it?
I thought this was one of those weaken questions where the correct answer choice presents a counter evidence with a stronger and more reliable source. In this case since we are to assume that (D) is TRUE, that would be the ultimate counter evidence that outright negates the findings of the said study in the stimulus.
It is very important that if someone thinks I'm wrong, they say it so that I don't mislead anyone with my logic if it is wrong.
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- Yu440
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Thanks Received: 0
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Jackie Chiles
- Posts: 40
- Joined: August 13th, 2018
Re: Q13 - A recent study of 10,000
Hello, I understand why D is correct. But I chose A during a timed practice because I thought it would show that the sample could be unrepresentative. If most of the accidents analyzed in the study occurred in areas with very high speed limits, then it's possible that accidents that happened in other areas show very different results -- i.e.. high percentage of injuries for large cars and low percentage of injuries of small cars. Is this too much of an assumption?
After review I decided that this answer choice doesn't explicitly compare large and small cars, therefore it is much weaker than answer D. Is this thinking correct?
Thanks!
After review I decided that this answer choice doesn't explicitly compare large and small cars, therefore it is much weaker than answer D. Is this thinking correct?
Thanks!