@dvo1d Thanks so much for the explanation! I think I’m starting to get it, but I’m still a bit unsure about how it relates to the original question.

The example you gave about 'If it’s raining, then it must be cloudy, and if it’s cloudy, then it must be raining' makes perfect sense to me as a biconditional: 'If and only if' one condition holds, the other one must hold as well.

However, when I look at the 'Or ... but not both' phrasing, it still seems more like an exclusive-or situation (XOR) to me. In other words, it’s either A or B, but not both at the same time—which feels more like the opposite of a biconditional.

For example, 'Cloudy or Raining, but not both' would work out to:

• (Cloudy or Raining) and ~(Cloudy and Raining)

Which, when I compare it to the biconditional you used earlier, seems like a different structure entirely. That’s why I’m wondering if there’s something I’m missing about 7Sage’s interpretation of 'Or ... but not both' as a biconditional indicator. Could someone help me clarify this?

Thanks again for the help! I really appreciate it.

@Andrewstine99 You wrote exactly how I feel right now.

The silver lining is that it has revealed that I'm not confident nor capable of recognizing different question types. I obliviously sat there looking for a conclusion. There wasn't one like there is in WSE, but I just kept thinking "I'm learning about WSE... I'm sure this is it." Dumb.

@AutonomousTacticalTheory I think you're right on point with this. If you look back to the fundamental definitions of premises and conclusions, you'll see that a premise is something that provides support to a conclusion.

Premises CAN support other premises, but that's not how it's really defined. So, as you pointed out, the goal of this type of question is to look for something that bolsters support for the conclusion - i.e., ignore the other premises because they don't really matter.

However, I could see a level 5 difficulty question being sneaky where the best answer is one that strengthens support for a premise that supports the conclusion.

Either way, thanks for this - the video was garbage in helping me.

Almost 59 minutes on this problem only to get it wrong. Some might say I'm thriving.

I've tried breaking this down several different ways, and it's not nearly as clear to me as any of the other ones.

My only real takeaway here is that "good evidence for" is comparable to a conditional statement.

I'm not seeing a rigorous, methodical way of preventing a misunderstanding like this happening in the future. Frustrating.

Hey, I'm a bit confused about the classification here and would love some clarification!

I understand that a biconditional statement means 'If A then B, and if B then A'—so we can write it like:

• A → B = ~A or B

• B → A = ~B or A

• A ↔ B = (~A or B) and (~B or A)

But I’m having trouble with how 7Sage classifies 'A or B, but not both' as a biconditional indicator. To me, it looks like 'A or B, but not both' is actually more like an exclusive-or (XOR), where it's one or the other, but not both.

For example, 'A or B, but not both' translates to:

• (A or B) and ~(A and B) = (A or B) and (~A or ~B)

And that doesn't seem to match up with the biconditional logic, which is why I’m a little confused.

Am I missing something here? Or is there a specific context I’m not considering in how 7Sage is approaching this? I’d really appreciate any insight on this!

@mariafreese You are negating the one of the conditions here though.

A or B but not both is not the same as A or not B, but not both.

My mistake in this section was misunderstanding the instructions to ask if a causal relationship could plausibly exist. Which, of course, I can make a plausible causal chain.

But you're asking if the statement itself asserts a causal relationship. The devil is in the details.

@turts Conditional vs Causal also messing me up! The differences can be so subtle, next thing I know I'm trying to apply formal conditional logic to some causal statement and I get completely lost.

My problems are quickly translating them into symbolic logic, and then evaluating them. So pretty much everything.

@Nico_DLC It took me 8:43 (491% over). I'm right there with you.

My struggle is equating rigorous conditionals with quantified statements. In some respects they are treated the same. This is what I've come up with for making the distinction easier:

If the statement is a conditional without quantifiers, use:

🔹 /(A → B) ≡ A and /B

If the statement contains quantifiers (all, some, most), apply:

🔹 Standard quantified negation rules (e.g., "All → Some not", "Some → None")

I feel like these and the examples before this are an exercise in recognizing indicator words. I've only noticed two questions that did not rely on indicator words. One of those is Q2 where the takeaway is that an author can present someone else's premises and conclusions, but not themselves make an argument.

Having returned to this section to improve my ability to identify premises and conclusions, I'd like to see examples less reliant on indicator words and more on identifying the relationships and support.

@LsatFootpad Nope, I immediately noticed I'm wrong and misread. Ok, please delete.

#feedback The written portion below does not discuss the second portion of the stim like the video does it merely stops after reading the sentence "Many animal species, after all, ..." For those who decided to read everything instead, like me, it would be good if you could update this.

The last example could probably be removed from this page as it isn't really helpful.

Hypothesis 1: A causes B. Cheese consumption causes death by entanglement in bedsheets. How? Um, I have no idea.

You not having any idea doesn't explain anything nor does it help me understand. It's you shrugging your shoulders and walking away. You do the same for the other hypotheses except the right answer.

The sort of lazy explanation that goes "That's wrong, duh. That's wrong, duh. That's wrong, duh. And here's the right answer, obviously. Done."

But just as a point, and maybe you can point out the problem with the explanation:

Cheese consumption causes death by entanglement in bed sheets by increasing the likelihood of brain activity associated with "tossing and turning" which, when consumed near bedtime, results in a higher risk of becoming entangled by your bed sheets. Those who consume cheese but do not sleep or lay in bed might have the same brain activity but there is no risk of dying since they're not in bed.