But one of those theories is the null hypothesis.
Suppose I have a coin, and am considering the following hypotheses:
H1 It is a fair coin H2 The coin comes up heads 80% of the time H3 The coin comes up head 95% of the time
Suppose I flip the coin and get heads.
*Condition A: I was originally split between H2 and H3 (prior of .50 for both).
The coin coming up heads is consistent with both hypotheses, but it's more consistent with H3, so I will raise my confidence in H3. Since probabilities must add up to 1, I have to lower my confidence in H2. (If I've calculated correctly, P(H2) is now about .46)
*Condition B: I was strongly predisposed towards H1. So, say, .70 for H1, .15 for H2 and H3.
Posterior probabilities: P(H1) = .57, P(H2) = .20, P(H3) = .23.
*Condition C: Priors P(H1) = .70 P(H2) = .25 P(H3) = .05
Posterior probabilities: P(H1) = .59, P(H2) = .33, P(H3) = .08.
So, yes, if the only two hypotheses are CT and FT, and the evidence supports FT more than CT, then it's evidence against CT. But if there are other hypotheses (and surely there are), then a case can be evidence for both CT and FT. And if CT has a higher prior than FT, then CT can end up with a higher posterior.
It appears that you may have a skewed idea of how Bayesian reasoning works. When doing a Bayesian calculation to find out the posterior for a hypothesis, one does not compare the hypothesis against a particular competing hypothesis; one compares the hypothesis against the entirety of alternative hypotheses. It's not the case that the hypothesis that best fits the data gets its probability increased and every other hypothesis has its probability decreased. In fact, optimizing simply for the hypothesis that fits the data best, without any concern for other criteria (such as hypothesis complexity), is generally recognized as a serious problem, and is known as "overfitting".
When doing a Bayesian calculation to find out the posterior for a hypothesis, one does not compare the hypothesis against a particular competing hypothesis; one compares the hypothesis against the entirety of alternative hypotheses.
Yes, but in the case of "the totality of the theories of the mind", this is impossible. You cannot possibly calculate P("poorly conducted, unpublished case studies"| not CT) to get a likelihood ratio. Plus, if you admit more than two competing hypothesis, you lose the additivitiy of log-odds and make the c...
I’m a member of the Bay Area Effective Altruist movement. I wanted to make my first post here to share some concerns I have about Leverage Research.
At parties, I often hear Leverage folks claiming they've pretty much solved psychology. They assign credit to their central research project: Connection Theory.
Amazingly, Connection Theory is never something I find endorsed by even a single conventionally educated person with knowledge of psychology. Yet some of my most intelligent friends end up deciding that Connection Theory seems promising enough to be given the benefit of the doubt. They usually give black-box reasons for supporting it, like, “I don’t feel confident assigning less than a 1% chance that it’s correct — and if it works, it would be super valuable. Therefore it’s very high EV!”. They do this sort of hedging as though psychology were a field that couldn’t be probed by science or understood in any level of detail. I would argue that this approach is too forgiving and charitable in situations when you can instead just analyze the theory using standard scientific reasoning. You could also assess its credibility based on standard quality markers or even the perceived quality of the work going into developing the theory.
To start, here’s some warning signs for Connection Theory:
I don't know about you, but most people get off this crazy train somewhere around stop #1. And given the rest, can you really blame them? The average person who sets themselves up to consider (and possibly believe) ideas this insane, doesn't have long before they end up pumping all their money into get rich quick schemes or drinking bleach to try and improve their health
But maybe you think you’re different? Maybe you’re sufficiently epistemically advanced that you don't have to disregard theories with this many red flags. In that case, there's now an even more fundamental reason to reject Connection Theory: As Alyssa Vance points out, the supposed "advance predictions" attributed to Connection Theory (the predictions being claimed as evidence in its favor in the only publicly available manuscript about it), are just ad hoc predictions made up by the researchers themselves on a case by case basis -- with little to no input from Connection Theory itself. This kind of error is why there has been a distinct field called "Philosophy of Science" for the past 50 years. And it's why people attempting to do science need to learn a little about it before proposing theories with so little content that they can't even be wrong.
I mention all this because I find that people from outside the Bay Area or those with very little contact with Leverage often think that Connection Theory is part of a bold and noble research program that’s attacking a valuable problem with reports of steady progress and even some plausible hope of success. Instead, I would counsel newcomers to the effective altruist movement to be careful how much you trust Leverage and not to put too much faith in Connection Theory.