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Looking forward to it!

I'd use something like: Sprightly Pedagogue (2018). Kuhn's cycle: Paradigms and Criticism. Retrieved from: th-cam.com/video/Yn8cCDtVd5w/w-d-xo.html . 05/18/2023

I'm so sorry some of the first free educational videos I posted for no gain or compensation weren't up to your standard. I'll work on being retrospectively perfect.

Einstein's gravitational theory is newer and more accurate. Newton's really only works on earth.

I might encourage taking another look at the video. We specifically attack the framing of theory as guess.

@@SprightlyPedagogueIs an educated guess more accurate?

Its not a guess....did u even watch the video? Just out of curiousity ...are u a flat earther?

Yes. It's annoying. But possible. Usually you're dealing with low effect size. Or low power.

It was replaced for the newer videos!

When you're thinking about independent or non-independent events, you're really talking about the possibility of a specific outcome occurring in a one-off event. If I draw marbles from a bag, what result will I get? The answer depends on what marbles are in the bag. The multiple comparisons problem comes into play only when you keep looking for that single specific outcome but you keep drawing many times. It's the repeated drawing, rolling, and flipping that causes the problem. So each dice roll is independent from each other dice roll. But, YOU keep looking for a four to be rolled. You are not dependent or independent. You're just trying to game the system and get a result you prefer.

Great question! The data doesn't change and the actual reality of the true relationships between the variables doesn't change. But, we don't have an exact measurement of these variables. From classical test theory each datum is made up of some proportion of 'true score' and some 'error'. If you look at enough error, you'll eventually see patterns in it. The more you torture your data, the more likely you are to accidentally see patterns in error and misinterpret it as meaning something that it doesn't.

Recommend checking out the book The Signal and the Noise.

Thanks for the encouragement! It's sure tough to get to them. Not really any monetary incentive unfortunately. I'd love to do something more in the future, but don't have nearly as much time for the hobby as I used to. I really appreciate the appreciation though! I hope I can find some time soon/eventually.

@@SprightlyPedagogue Thanks for the reply. I understand your point. Won't mind your explanations in form of blogposts as well. Your lucid explanation in one of the replies to illustrate the difference between Fischerian and Bayesian Statistics was also a joy to read. Glad to come across your channel. Wishing you the best in your future endeavors.

I read this to a colleague. They said: 'that sentence makes no sense. Alterations might make sense. Altercations are fights. ... Along with several other issues with that sentence.

@@SprightlyPedagogue which one of the sentences that don't make sense is it the one with the dog which was a ad hoc or my comment and if I use the word argument instead of altercation will that clarify your confusion

Please start with punctuation so I can get a sense of what you're trying to say. None of this makes sense. Also, 'the ad hoc is the theory' reads like nonsense. You might as well have said, 'the chicken is the seven'

@@SprightlyPedagogue my bad on that see my hand are big and I have a bad habit of not reading over whst I text and this phone is garbage the keypad is very small and the predictability is not that accurate so I will rewrite

edit: your example sucks

Those dice rolls are independent of one another, so they are functionally the same statistical statement.

Rerolling the same die six times and recording the results is no different from rolling six dice and recording the results. In both cases each roll has a probability to result in a 1 of 1/6. The problem of multiple comparisons arises when (implicitly or explicitly) a conclusion about a more general hypothesis is drawn from a number of tests. A "more general hypothesis" could mean a hypothesis like "there are differences between groups somewhere" in a case with more than 2 groups. With every additional group the number of (possible) group comparisons increases. Since each comparison has a chance of resulting in a false rejection of the null hypothesis multiple group comparisons result in an increase of chance to falsely reject the null hypothesis of that "more general hypothesis" (that there are differences somewhere). The type I error rate of such a "more general hypothesis" is sometimes called the family-wise error rate. The more comparisons you look at the higher the chance that you end up with at least one significant comparison just by chance (as a result of random sampling) even though there are no differences in the population. That said, I don't like the analogy of the kid that is rerolling the dice for this either. The kid rolls the dice again if (and only if) it does not like the first result. It does that until it likes the result and then uses that. An equivalent to this exists in data analysis: An analysts performs additional tests until they find one that is significant and then report that one (it is like making up new hypotheses on the go). This behavior is problematic as it leads to spurious results that are essentially worthless. However, this does not describe the problem of multiple comparisons. This behavior is known as fishing (for effects) in the literature. The analogy with the kid that is rerolling the dice suggests that adjusting for multiple comparisons solves the problem of fishing, which it does not. The analogy also suggests that the problem with multiple comparisons only exists when one makes up new hypotheses on the go. This is not the case either. For me the analogy of the kid rerolling the dice is a great analogy for fishing. But aside from the fact that both cases involve multiple comparisons, the multiple comparisons problem that one tries to resolve via a p-value adjustment is independent from fishing. Do you agree?