Im contemplating if these lessons are worth it or if I should just be doing practice problems more than watching these lessons? If anyone could let me know what I should focus on more I would appreciate either!
@BrookeRodriguez depends on how much time you're giving yourself before your test date, I feel the more time you give yourself the more time you can devote to comprehensive lessons like this, if you're a few months out it's probably best to take practice questions and go back to fundamentals on topics you're struggling on.
You say in the video that the less you smoke, the less likely it is you get lung cancer. Do all correlations move together if you negate them like this? I'm not certain that makes sense in reality... For example, if Walt quit after 30 years, and now he is a non-smoker, his likelihood of getting lung cancer will not "move together" with how much he smokes---his history of smoking still puts him at a high risk. In sum, can we negate causal relationships on the LSAT? or if it is reasonable to assume that certain causal relationships only move one way...
Another example could be the more algae in the dolphins habitat the more the dolphins are found dead on the shore. But, lets say the algae blooms rapidly drop back to normal levels sufficient for dolphin life. This does not mean that the dolphin population will necessarily rise (or recover) with the drop in algae. Help!
I must admit this is my second time around with the material and I kid you not this stuff is making more sense day by day. Now I just have to be able to see it on my practice test and do it quickly .
On the test, many of the causal arguments will have correlative phenomena. But in real life cause and effect arguments and research do not always have to have a correlation component. I have a degree in experimental psychology and many times when analyzing data there will be instances where there is no correlation found between phenomenon and it would be incorrect to argue that the effect was due to a correlation between them. In this particular lesson, it states that many of the phenomena in life AND on the test will be correlations. But that isn't necessarily guaranteed and the test makers will always try to confuse causation with correlation or effect so you have to pay close attention to the language and chronology of events.
i think (and im not 100% but from what i gather from this and previous education) is that causation is a subset of correlation. not all correlations are causations but all causations are correlations
Hi, I would like to hear some examples about some effects are not correlations...I think it is very tricky that 'correlations' denotes the idea of 'simultaneity' and 'concurrency'
19 comments
So correlations only happen if something can go up or down in numbers or percent?
Correction for 0:22: Walter White never smoked, but he worked with carcinogenic chemicals. This presents an alternative hypothesis to your hypothesis.
Jesse, we have to get 180s on the LSAT!
Im contemplating if these lessons are worth it or if I should just be doing practice problems more than watching these lessons? If anyone could let me know what I should focus on more I would appreciate either!
@BrookeRodriguez depends on how much time you're giving yourself before your test date, I feel the more time you give yourself the more time you can devote to comprehensive lessons like this, if you're a few months out it's probably best to take practice questions and go back to fundamentals on topics you're struggling on.
You say in the video that the less you smoke, the less likely it is you get lung cancer. Do all correlations move together if you negate them like this? I'm not certain that makes sense in reality... For example, if Walt quit after 30 years, and now he is a non-smoker, his likelihood of getting lung cancer will not "move together" with how much he smokes---his history of smoking still puts him at a high risk. In sum, can we negate causal relationships on the LSAT? or if it is reasonable to assume that certain causal relationships only move one way...
Another example could be the more algae in the dolphins habitat the more the dolphins are found dead on the shore. But, lets say the algae blooms rapidly drop back to normal levels sufficient for dolphin life. This does not mean that the dolphin population will necessarily rise (or recover) with the drop in algae. Help!
Thank you AP Psych
Correlation: 2 phenom that happen together; no concrete cause
Is your username a JJK reference? Because if so, GOATED
OMG HI FELLOW JJK FAN I’ve been embracing my inner Gojo while studying 😭
I must admit this is my second time around with the material and I kid you not this stuff is making more sense day by day. Now I just have to be able to see it on my practice test and do it quickly .
time to rewatch breaking bad
Are all causal relationships necessarily correlative as well? Are there any cases in which a causal relationship does not require correlation?
#help (Added by Admin)
On the test, many of the causal arguments will have correlative phenomena. But in real life cause and effect arguments and research do not always have to have a correlation component. I have a degree in experimental psychology and many times when analyzing data there will be instances where there is no correlation found between phenomenon and it would be incorrect to argue that the effect was due to a correlation between them. In this particular lesson, it states that many of the phenomena in life AND on the test will be correlations. But that isn't necessarily guaranteed and the test makers will always try to confuse causation with correlation or effect so you have to pay close attention to the language and chronology of events.
i think (and im not 100% but from what i gather from this and previous education) is that causation is a subset of correlation. not all correlations are causations but all causations are correlations
Hi, I would like to hear some examples about some effects are not correlations...I think it is very tricky that 'correlations' denotes the idea of 'simultaneity' and 'concurrency'
Or "correlation does not imply causation" as the well-known saying goes
This is so interesting! Thank you for your insight