For ice cream sales --> number of drowning deaths: Ice cream is exclusively sold on ice cream boats that only operate on the water, and people have to swim out quite far to get it.
a serial arsonist sends letters to fire departments telling them how many firefighters to send depending on the size of the fire they are going to start
@MacyHolcomb i think its usually [the argument is most vulnerable to criticism on the grounds that...] or [which of the following most accurately describes a flaw in the argument's reasoning?] or strengthen/weaken questions
@Isabella! The third factor would be the causal phenomenon, and the mechanism would be everything between it and the target phenomenon
For example, the ice cream and drowning statement, the causal phenomenon is warm weather but the mechanism is warm weather =c=> more swimming =c=> more drowning
what if you can't think about the common cause? will we get better over time? with the second example, i personally did not even think about how warm weather could play an impact on ice cream and drownings.
@Summer Someone can correct me if I'm wrong, but I'm thinking that the actual questions will come with a passage that provides us with the context. (At least I hope so.)
#help, as i am moving along these lessons I am seeing everything piece together, but I am not exactly 100% on all the concepts we've learned (ex: determining the correct logical arguement structues, etc). Do u guys advise its better to keep going and brush up on it later or go back and perfect those skills before moving on?
@AlexandraPolidora I think the idea is that when it comes to formal logic i.e. conditionals, then you cannot use outside information. On the other hand, for informal/ logic like causation and correlation, you can? I am assuming that when real practice shows up, then they will provide answer choices in which you have to decide whether they make sense in that particular context.
cheese causes more people to die by bedsheet entanglement because cheese makes tummy hurt and tummy hurt means restless sleep, which increases likelihood of becoming entangled in bedsheets and dying !
Different technical domains use this term differently, but in causal inference, spurious correlations are understood as structural relationships in the data and are distinct from chance (where random error happens to produce an apparent pattern). The correlation between bed sheet deaths and cheese consumption is a great example of a classic and common source of spurious correlations, time series data, where the confounding arises from shared dependence on calendar time. The confounding is mediated by latent (and often unmeasured) variables, but it has precisely the structure of confounding, not chance. One could hypothesize a number of latent variables. Economic conditions and age structure of the population are two possibilities, but whatever they are, they are indexed to time, and occur upstream of both variables of interest. Depending on your lens, you could invoke collider bias in the search for relationships that would sound ridiculous to the casual observer and make for good fodder on a website devoted to them.
Not me just sitting here trying to ponder if an increase in temperature could lead to more cheese consumption, heavy fat caloric intake to keep warm, and also people being in bed under their sheets more for warmth, wondering if C could indeed cause A and B separately lol...
Lots of great theories in this comment section on what could cause a correlation between increased cheese consumption and increased death by entanglement in bedsheets.
I'll throw out another one... What if people who eat cheese tend to drink wine while enjoying their cheese? If drinking wine before heading to bed puts one in a non-sober state, maybe they're more likely to end up tangled in their sheets?
My first thought regarding the cheese and death by bedsheets correlation was that cheese can contribute to sleep disturbances. These disturbances may cause individuals to have more vivid nightmares. Hence, this could explain how A (higher cheese consumption) causes B (# of people who die by becoming entangled in their bedsheets). I thought the "duh it's wrong" attitude was not helpful, as there actually could be an explanation that links the two claims together. Additionally, I think this is wrongfully leading people to give up if the explanation isn't a given (which is exactly how the LSAT wants to trick you). #feedback
About the cheese-bed entanglement correlation, it could be that wealthier populations eat more cheese; wealthier populations also live longer, and the elderly are more likely to get seriously hurt and die by becoming entangled in their bedsheets. So it could be hypothesis 3: C causes A and B.
90 comments
For ice cream sales --> number of drowning deaths: Ice cream is exclusively sold on ice cream boats that only operate on the water, and people have to swim out quite far to get it.
a serial arsonist sends letters to fire departments telling them how many firefighters to send depending on the size of the fire they are going to start
@JosephWendt "The arsonist had oddly shaped feet" - Ron Burgundy
i mourn by eating ice cream
isnt hypothesis 2 b to a invalid though?
Does anyone know what kind of question stem we can anticipate for these types of questions?
@MacyHolcomb i think its usually [the argument is most vulnerable to criticism on the grounds that...] or [which of the following most accurately describes a flaw in the argument's reasoning?] or strengthen/weaken questions
haha someone mentioned on the previous lesson that the examples were depressing.
this lecture: "ice cream sales is positively correlated with the number of drownings"
I'm confused by how Hyp 3: "A third factor" is this third factor the causal mechanism? Or is that just separate?
@Isabella! The third factor would be the causal phenomenon, and the mechanism would be everything between it and the target phenomenon
For example, the ice cream and drowning statement, the causal phenomenon is warm weather but the mechanism is warm weather =c=> more swimming =c=> more drowning
@SavanahHoffstein This makes so much sense! Thank you!
what if you can't think about the common cause? will we get better over time? with the second example, i personally did not even think about how warm weather could play an impact on ice cream and drownings.
@Summer Someone can correct me if I'm wrong, but I'm thinking that the actual questions will come with a passage that provides us with the context. (At least I hope so.)
#help, as i am moving along these lessons I am seeing everything piece together, but I am not exactly 100% on all the concepts we've learned (ex: determining the correct logical arguement structues, etc). Do u guys advise its better to keep going and brush up on it later or go back and perfect those skills before moving on?
#help I am so confused how this would apply to a real LSAT question... would love an example of some sort
You stop supporting Big Cheese™, soon you find yourself sleeping with the dust bunnies...
@AlexB33 Read Thomas Pynchon's new book Shadow Ticket lol
I still don't understand why we've been trained this whole time not to use outside knowledge and now this lesson is undoing all of that...
@AlexandraPolidora I think the idea is that when it comes to formal logic i.e. conditionals, then you cannot use outside information. On the other hand, for informal/ logic like causation and correlation, you can? I am assuming that when real practice shows up, then they will provide answer choices in which you have to decide whether they make sense in that particular context.
cheese causes more people to die by bedsheet entanglement because cheese makes tummy hurt and tummy hurt means restless sleep, which increases likelihood of becoming entangled in bedsheets and dying !
ice cream causes drownings because you're supposed to wait to go swimming after you eat
Different technical domains use this term differently, but in causal inference, spurious correlations are understood as structural relationships in the data and are distinct from chance (where random error happens to produce an apparent pattern). The correlation between bed sheet deaths and cheese consumption is a great example of a classic and common source of spurious correlations, time series data, where the confounding arises from shared dependence on calendar time. The confounding is mediated by latent (and often unmeasured) variables, but it has precisely the structure of confounding, not chance. One could hypothesize a number of latent variables. Economic conditions and age structure of the population are two possibilities, but whatever they are, they are indexed to time, and occur upstream of both variables of interest. Depending on your lens, you could invoke collider bias in the search for relationships that would sound ridiculous to the casual observer and make for good fodder on a website devoted to them.
Not me just sitting here trying to ponder if an increase in temperature could lead to more cheese consumption, heavy fat caloric intake to keep warm, and also people being in bed under their sheets more for warmth, wondering if C could indeed cause A and B separately lol...
Can we all appreciate how funny and well-understanding the examples are?
The last example about bedsheets and cheese consumption was just too good to forget
Lots of great theories in this comment section on what could cause a correlation between increased cheese consumption and increased death by entanglement in bedsheets.
I'll throw out another one... What if people who eat cheese tend to drink wine while enjoying their cheese? If drinking wine before heading to bed puts one in a non-sober state, maybe they're more likely to end up tangled in their sheets?
I geeked out over this lesson. Everything clicked!!!
what if the fire station was on fire #law
The third scenario is the source or signal for the fire in the first place. C the sound of the alarm -> Fire Fighters -> size of fire
The third hypothesis in the first example is perception. You perceive there to be a lot of firefighters and you also perceive the fire to be very big.
Maybe i've read too much descartes
My first thought regarding the cheese and death by bedsheets correlation was that cheese can contribute to sleep disturbances. These disturbances may cause individuals to have more vivid nightmares. Hence, this could explain how A (higher cheese consumption) causes B (# of people who die by becoming entangled in their bedsheets). I thought the "duh it's wrong" attitude was not helpful, as there actually could be an explanation that links the two claims together. Additionally, I think this is wrongfully leading people to give up if the explanation isn't a given (which is exactly how the LSAT wants to trick you). #feedback
C, the firefighter's were given an anonymous tip from a pyromaniac who started the large fire as the firefighters arrived.
About the cheese-bed entanglement correlation, it could be that wealthier populations eat more cheese; wealthier populations also live longer, and the elderly are more likely to get seriously hurt and die by becoming entangled in their bedsheets. So it could be hypothesis 3: C causes A and B.