Travel writer: A vacationer should

Answer choices

1. A

   Reasonable Logic3% picked this

   A tossed coin has come up heads 100 times in a row. It is therefore reasonable to believe that the coin is not fair,

   While this is tempting because we're primed to look for the Gambler's Fallacy, and the "coin flip" is the classic example used to illustrate it. But this argument makes sense. It's astronomically unlikely that a fair coin would come up heads 100 times in a row, so while that wouldn't 100% prove it's not a fair coin, it would certainly support a very reasonable suspicion that it's not a fair coin.

   3%
2. B

   Correct86% picked this

   If there are 10 adult male baboons in a troop, the chance of an average adult male baboon ascending to dominance in any given

   Why this is right

   This only mimics the move from Premise to Intermediate Conclusion (it has no 2nd conclusion), but as we suspected, that is the main error LSAT wants us to catch. This answer, like the original argument, interprets average rates too literally and thinks that past data points influence future probability. The idea of Gambler's Fallacy is that because the probability of tails is 1/2, if you get heads a few times in a row, you feel overdue for some tails. That's an incorrect understanding of probability, though, which balances out to 1/2 over an infinite time scale. In this argument the author is acting like an adult male that hasn't ascended to dominance over the past 10 years is now overdue to ascend to dominance. What do we mean by "interpreting probability too literally"? If I have a six-sided die, the probability of rolling a 4 is 1/6. Rolling a 4 is one of six possible outcomes, so it has a 1/6 probability. Does that mean that if I roll a die six times, I'm guaranteed to get exactly one 4? Of course not. But that's how the author is thinking about probability. If the average rate of airline accidents is 1 every 5 years, then over any 5 year time span, an airline should have exactly 1 accident. If a baboon has a 1/10 probability of ascending to dominance, then over any 10 year time span, that baboon should have ascended to dominance exactly once.

   Skill tested: Parallel Flaw · how this choice captures the argument's function is the move to repeat next time.

   86%
3. C

   Different Flaw4% picked this

   On a given day, an average resident’s chance of being involved in a traffic accident in a certain city is 1 in 10,000.Therefore, the

   This argument is attempting to apply a probability statistic to an individual, but it's unclear whether the statistic can be properly applied to that individual. If I say, "the chance that an NFL player is left-handed is 1 in 8. Thus, Marty, an NFL player, has a 1 in 8 chance of being left-handed", that would be a reasonable application of a statistic. But this probability statistic is about "average resident", and it's not clear that a 5-year old would really constitute an average resident (5-year olds might not be in cars nearly as much as other age groups). If we accept that Marty qualifies as an average resident, then there is no flaw. If we think that Marty doesn't qualify as an average resident, then that's a different flaw from the original.

   4%
4. D

   Different Flaw1% picked this

   The average adolescent who works full-time in a certain country makes about 76 cents for every dollar that an adult who works full-time there

   This is a flawed argument, but it's not committing a Gambler's Fallacy, it's just doing an inappropriate comparison and basically failing to consider how weighted averages might ruin its conclusion. The argument establishes a three part inequality: part-time < full-time < full-time adolesc adolesc adult We know that the full-time adolescents make an average of 76% of what the full-time adults do. And we know part-time adolescents make even less. So it would be a valid conclusion to think that "the average adolescent who works part-time makes less than 76 cents for every dollar made by a full-time employed adult". But since the conclusion just says "employed adult", it includes part-time and full-time adults. We don't have any information about what part-time adults make. Even though it would go against our common sense, it's possible that part-time adults make less than part-time adolescents. part-time < part-time < full-time < full-time adult adolesc adolesc adult We would know that part-time adolesc make less than 76% of full-time adults, but in this inequality they make more than 100% of part-time adults. So if you compared what part-time adolescents make to what all employed adults make, the % would be something higher than 76%. You don't need them to make MORE money for this conclusion to be wrong. If part-time adolescents make 100% what part-time adults make (i.e. they get paid the same), that would also ruin the conclusion. It would still mean that part-time adolescents make more than 76% of what all employed adults make (the percentage would be a weighted average between 76% and 100%, based on what share of employed adults work part-time vs. full-time).

   1%
5. E

   Weak Match6% picked this

   Though until recently this chess grandmaster had responded to opening move X with move Y half of the time, in the current tournament he

   This argument does treat probability literally, in a way. It thinks that if this master has been responding with Y 90% of the time, then he's 90% likely to respond with Y in the next instance. This is different in an important way, though: In both the original argument and in the correct answer, the author is looking at an average rate for X occurring and thinking that someone is overdue for X and so their probability of X is now higher than before. In this argument, the author thinks the probability of Y occurring on the next move will be the same as it's been for previous instances in this tournament.

   6%