Alright, let's take a look at how you did on this question. First, we'll start by reading what the

question is asking for. So it says, the reasoning in the driver's argument is most vulnerable to

criticism on the grounds that this argument... what? And then the answer choices give us a

whole bunch of things that the argument does. But the key point is that this argument is going to

be vulnerable to criticism. And this raises two concepts that you're going to learn a lot more

about later on. First is, what is an argument? And second is, what does it mean for an argument to

be vulnerable to criticism? Okay, so you can think of an argument as an attempt to persuade

someone of something. Now, that persuasion has to be based on reasons. The thing that someone's

trying to persuade us to believe, that's called a conclusion. And the reasons offered for why we

should believe it, that's called premises. So that's an argument. Now, an argument can be

vulnerable to criticism when the premises do a terrible job of persuading us that the conclusion

is true. Okay, so let's apply that. Let's see what the driver is saying and identify first what he's

trying to convince us of. That's the conclusion. And second, the reason or reasons offered in

support, which would be the premise or premises. All right, so first, my friends say I will one

the driver's own argument, yet the driver is just telling us what his friends are saying.

Right, from this statement, we learn that the driver apparently drives a sports car and does

so in a dangerous way. Okay, let's keep going. But I have done some research, and apparently

minivans and larger sedans have very low accident rates compared to sports cars. Okay, yeah, I mean,

that makes sense, right? Minivans, larger sedans have lower accident rates in comparison to sports

cars. So trading my sports car in for a minivan will lower my risk of having an accident. Hmm,

that's interesting. Now the driver is making a prediction. Right, if he gives up his sports car,

right, trading my sports car in, and starts using a minivan instead, right, for a minivan,

that will lower his chances of getting into an accident. Now, I want you to pay attention to

this word, so. Right, this word so at the beginning of the statement is telling us that the driver

believes this last statement is proven by the statement before it. He's trying to persuade us

that switching from a sports car to a minivan would lower his accident risk. So that's his

conclusion. And he argues to this conclusion on the fact that minivans have lower accident rates

than sports cars. So that's the premise. Okay, so this is his argument. Okay, great, so argument

done. Now let's think about in what sense this argument might be vulnerable to criticism. To do

that, we really have to think about why the premises do not support. Right, in other words,

do not do a good job of proving that the conclusion is true. Okay, so from the driver's

research, that is to say the premises, we know that minivans have a lower accident rate. Okay,

so now does that prove that we can just take someone who drives a sports car, put them in a

minivan, and expect to reduce their risk of getting into an accident? I mean, that's certainly the

position that this driver is taking. And you know what? If you're new to the LSAT or logical reasoning

in general, you might think that it does. Okay, but first I want you to consider some analogous

arguments and see where your intuitions lie. See if it changes your intuition. So first let's

consider this analogous argument. People who eat a lot of seafood are more likely to exercise than

people who eat a lot of red meat. So I can increase the chances that I'll exercise by starting to eat

a lot of seafood. How does this sound? Kind of fishy, right? I mean, yeah, sure, the people who eat a lot of

seafood are more likely to exercise, but the key question is why? Why are they more likely to

exercise? It's not because somehow chowing down on Nemo is going to make you go run a lap, right, or

go lift some weights. It's far more likely that they're just people who care about health. In

general, they care about health, and that's why they're eating more seafood, and that's why

they're exercising. Okay, so if you simply start to eat a lot of seafood, we just can't expect that

it'll make you exercise more, right, because the, you know, the act of eating seafood won't necessarily

change you into the kind of person who cared about a healthy lifestyle to begin with. Okay, so

hopefully that that makes sense. Let's consider another analogous argument. People who memorize

the phone number and address of the local U.S. embassy when traveling to another country are less

likely to lose their passports. So I can reduce the chances of losing my passport when traveling

if I memorize the phone numbers and addresses of U.S. embassy in the country I travel to.

Again, this argument should strike you, your intuition, as kind of bizarre, because how can

memorizing phone number and address, how can that change the chances of you losing your

passport, right? What's really going on here, you know, about people who memorize the phone numbers

being less likely to lose their passport, what's really going on here is that these are just very

careful people. I mean, think about how careful, how conscientious you have to be to like memorize

the phone number and address of a local U.S. embassy. I don't think I've ever done that in

my life, you know, and I have lost my passport. But anyway, the point is, it's my carelessness

that's making me lose my passport, right? So just, you know, making me memorize phone numbers and

addresses of U.S. embassies, it's not gonna, it's not gonna make me less careless. Okay, so now let's

come back to our driver's argument. Yes, minivans do have lower accident rates compared to sports

cars, but does that mean that this driver can reduce accident rate by trading in his sports

car for a minivan? I hope you see that the answer is no, because we have to ask why the minivan has

a lower accident rate as compared to a sports car, right? And the reason is most likely because

it's the kind of person who drives a minivan, right? That kind of person probably drives more

carefully than someone who chooses to drive a sports car, right? Who drives minivans? Probably

parents with small children, right? Think about that kind of driver. You know, they're always

going to use their turn signals. They're going to follow the speed limit. They're going to come to

full stop at a stop sign, okay? No rolling stops. Now, on the other hand, people who drive sports

cars, you know, they're probably not carrying a bunch of toddlers in the back, right? They're

probably not as careful as the parent in the minivan. In fact, they might have purchased a

sports car specifically to drive fast. So you see why simply taking a sports car driver and popping

him into a minivan may not reduce his risk of having an accident, okay? So now at this point,

I want to make sure you're aware that there is a very standard label for the bad reasoning that

the LSAT is using, that this driver is using. And this is something we'll go over later in the

curriculum. In fact, if you are close to taking the LSAT, I think it's very important that you

know this label and can recognize that that's the mode of reasoning. And ideally, not only

could you do that, you could go hunting for the right answer. And maybe I've just described you,

and if I have, great, then you are ahead of the curve, okay? But at this point, I'm going to assume

you're just at the beginning of your studies, and we don't know all the LSAT jargon. Let's just go

through the answers carefully and see if we can stumble upon the right one. All right, so let's

go through the answers. I'm going to address them in the order from least picked to most picked based

on our analytics. And the question for every answer is whether this accurately describes why

the argument is vulnerable to criticism. So B first, B says, relies on a sample that is too

be too narrow? Look, if you conduct a poll to predict the outcome of a presidential election,

but for whatever reason, you only decided to poll your neighborhood, okay, well then, you know,

that sample, your neighborhood, probably not going to be very accurate, right? That sample,

your neighborhood is going to be too narrow. Okay, it's not going to capture the broader

population that's going to vote, because that's what B's talking about. Now, in this argument,

does our driver have this kind of problem? No, right? There isn't even a sample in the first

place, much less a sample that's too narrow. Okay, the driver does bring up statistics, sure,

statistics about, you know, like accident rates and stuff. But there's no indication that these

statistics, look, I mean, we don't know where these statistics came from. There's no indication

that they came from, you know, a poorly conducted too narrow sample. It's not like the author said,

Oh, look, the Honda Odyssey has a lower risk of accident than the Lamborghini. So therefore,

minivans have a lower rate of accident than sports cars, right? Had that been the reasoning,

B would have been right. But here, B is wrong. Next up is E, which says relies on a source that

that's not well informed? Well, look, if for whatever reason, you found yourself in need of

fixing a malfunctioning nuclear reactor, okay, you probably wouldn't ask a random six year old

for advice. And the reason is, she's just a kid, we should possibly know about nuclear reactors,

how to fix them. Right? If you ask her what to do and follow that advice, well, then you'd be

relying on a source and that's probably not well informed. Okay, you'd be guilty of what E is

saying. Now, does the driver do this? Does a driver rely on some source, right? Something a driver

cites as an authority for support? Well, the driver does bring up statistics again about, you

know, minivans and sports cars, but we don't know anything about where these statistics came from.

So we can't just, you know, be really unfair, be totally uncharitable and grossly unfair to say,

oh, you know what, the driver didn't tell us this, but these statistics, they just came from

some random six year old, right? The driver just pulled aside some random six year old and asked

them and said, you know, hey, look, according to, according to her, minivans have a lower risk of

accidents than sports cars do. Okay, so we just have no basis for speculating that that's what

happened. Okay, and if we can't do that, well, then we have no basis to accuse the argument of

having relied on a source that's not well informed. Next up, we have C, which says misinterprets

what the striver has done is it has misinterpreted certain kind of evidence, right, this kind of

evidence, evidence that result is likely, as a different kind of evidence, as evidence that the

result is certain. Now, what's wrong with this? Well, first, what does this mean? Here's a

positive example of what C is getting at. Let's say the local news forecast says that rain is

likely tonight. Okay, now, does that imply that rain is certain? Well, obviously not. If something

is likely to happen, that just means there's greater than 50% chance that it will occur,

okay, where certainty means 100%. So now, if you interpret, you know, likely rain tonight for, oh,

it's definitely going to rain tonight, well, then you'd be guilty of what, you know, C's claiming,

right, C's accusing. Okay, now, does the driver's argument do that? No, it doesn't. In fact, if you

look at the conclusion here, the driver explicitly says, would lower my risk, and that means the

driver understands that there is still a chance that an accident may happen. Okay, so it's not

certain that he's going to avoid accidents. Okay, so that's why C doesn't work. Next up, we have D,

for bringing about that result. Now, I wonder if this rang a bell. If you did the previous question,

the coffee shop problem, I'm going to guess it did. Remember, in that question, I mentioned that

sufficiency, necessity, confusions, right, mistakes, failing to distinguish one from the other. I call

that the oldest mistake in the book. This is part of the reason why I do that. It's because it's

just such a commonly recurring thing, right? What does it mean to confuse or mistake a sufficient

condition with a necessary condition? Well, a sufficient condition is a condition that guarantees

something else to be true, whereas a necessary condition is a condition that must be true in

order for something else to be true. It doesn't guarantee it, it just has to be true. So now, does

the driver's argument interpret a sufficient condition as a necessary condition? No. In fact,

there are no sufficient conditions described in the argument. Look at the premise. It's just a

statistic about minivans and sports cars, right? It is not saying that driving a minivan will

guarantee that you avoid an accident, nor is it saying that if you drive a sports car, it's going

to guarantee that you get into an accident. Okay, so there's just nothing here that can accurately

be described as a quote-unquote sufficient condition. Now, alternatively, D could be right

if we drastically change up the driver's argument. If the driver's argument says something like,

look, if you drive a sports car, you will get into an accident. My friend got into an accident,

therefore I infer my friend must have been driving a sports car. Okay, so that argument is unconvincing

because other kinds of cars can also get into accidents. Or stated differently, that argument

is unconvincing because it mistook a sufficient condition, driving a sports car, for bringing

about a result that is getting into an accident as if it were a necessary condition. So finally,

And this is the, you know, standard label that I mentioned earlier that, you know, I was like,

if you're about to take your actual LSAT, I would hope that you'd be able to recognize this pattern,

right? This very repetitive mode of poor reasoning. But you know, if you haven't heard of this concept

before, A is really hard to pick. And you know what? Even if you have heard of this concept before,

I think this argument still does a great job of disguising the problem. Okay, so before I go into

why A is right, let's first define what cause and correlation mean. Okay, so what's a correlation?

A correlation is just when two variables tend to move together, either in the same direction or in

the opposite direction. Okay, in the same direction, we call it a positive correlation. In the opposite

direction, we call it an inverse correlation. But anyway, think about, say, in children. Okay,

let's limit this to children. Think about shoe size and intelligence. They tend to move together.

They're positively correlated. Bigger shoe size tend to correlate with higher intelligence and in

the other direction as well, right? Lower intelligence tends to correlate with lower

shoe size. Now, that's correlation. Does that mean there is causation between these two variables?

Now, what is causation? Causation is just when one thing plays a role in bringing about another

thing. Okay, so even though shoe size and intelligence are correlated, neither causes the

other, right? I mean, somehow you get a kid, I don't know how, having surgery, I guess, you make

their foot bigger or smaller. It's not going to change how intelligent they are, right? Likewise,

changing this is not going to change, right? Somehow you could like go in there and change

how intelligent they are. You're not going to change their foot size, right? So then, what

explains this correlation? Just age, right? As children grow up, get older, their shoe size

increases and their intelligence increases. This is just another way of saying older children tend

to have larger shoe sizes and tend to be more intelligent than younger children. Okay, so that's

correlation-causation. Now, what about this argument? Does it infer a cause from a mere

correlation? It does. The statistic here in the premise about minivans and larger sedans having

lower accident rates, that's just a correlation. It's a correlation between the kind of car,

right? The kind or type of car you drive and your chances of getting into an accident, right? There's

some kind of moving together here. You move closer and closer to minivans and larger sedans,

your accidents go down. You move closer and closer to sports cars, your accident rates go up. Now,

the reason why this driver's argument is vulnerable to criticism is because this driver believes that

this correlative statistic allows him to infer a causal explanation. He thinks that there's

something about the minivan that is causally responsible for lower accident rates. That's

why he thinks if he switches to a minivan, he would reduce his chance of getting an accident,

right? As if, like, I don't know, minivans had, like, autonomous driving built in, whereas sports

cars didn't, right? And that autonomous driving would, you know, keep you from getting into an

accident. But that's just not true. In other words, his causal interpretation of this correlation

is unwarranted. As we discussed earlier, the actual explanation for this correlation is far

more likely to be that the kind of person who chooses a minivan is also the kind of person who

would drive carefully, whereas the kind of person who chooses to drive a sports car

is precisely the kind of person that wouldn't drive so carefully. So switching the reckless

driver into a minivan won't improve his odds very much. Okay, so there are so many takeaways

in this one question. First of all, it's just a great example of a common kind of battle reasoning,

which we call inferring causation from correlation. You're going to see at least

one example of this in every single LR section, okay? Usually more than one. Second, eliminating

wrong answers requires a strong understanding of other kinds of bad reasoning. You know,

what does it mean to rely on a sample that's not representative? What does it mean to confuse a

likelihood for certainty? What does it mean to confuse sufficiency for a necessity? What does

it mean to inappropriately appeal to an authority, right? Yeah, these modes of reasoning are all bad

in their own way, and they're the wrong answers for this question, but you know what? They're

going to be the right answer for different questions. And so this brings up the more basic

issues you might not be familiar with. What is an argument? What are premises? What are conclusions?

And when do premises not support conclusions? Now, of course, the core curriculum is going to

cover all of these in extensive detail. I just want to emphasize one other thing that you're

going to get by making your way through the curriculum, the value of which may not be

apparent yet, okay? I wonder if you notice that in explaining this particular problem in the

previous one about the coffee shop, I relied a lot on analogies. I relied a lot on your real-world

intuition. Now, leaning on analogies and appealing to your real-world intuitions can be pedagogically

very useful. It helps to drive the point home. But, you know, each LR section has like about

25 questions, one after another, and you're going to be under intense time pressure. And if you need

to rely on analogies or think about, you know, real-world intuitions, you're just going to run

out of time. And the only reliable path to a high score in logical reasoning is to recognize the

common underlying logical structure. The core curriculum is designed to hone your mind such

that when you see a premise like this, you're going to immediately think, oh, they're just

telling me x is correlated with y. And you see a conclusion like this, you're going to think, oh,

this driver mistakenly inferred a causal explanation from correlative data. Or if we're

doing the coffee shop problem, you're going to want to see immediately the difference between

sufficient condition for something happening versus necessary condition. And that kind of

pattern recognition, that kind of structural understanding, that's what the core curriculum

is designed to deliver.