4 ms·
> So you have 7 photos, only 4 of them clearly confirm what you want to say, 1 likely contradicting it, and you're happy to take this as a universal? I also thi
by mlyle 4y ago
> So you have 7 photos, only 4 of them clearly confirm what you want to say, 1 likely contradicting it, and you're happy to take this as a universal? I also think your analogy doesn't hold for another reason
I'm sorry; I disagree and I don't think you understand the statistics.
> Look at the last study.
This is another new goalpost. I am not willing to discuss further.
- somenameforme 4y agoImagine for a moment that this study was trying to demonstrate that e.g. climate change was primarily caused by solar variation a la Willie Wei-Hock Soon [1]. And he provided the exact same quality of evidence, and the exact same "issues." There is zero chance you would now be claiming this to be a "universal" in spite of the exact same quality, or lack thereof, of evidence. I was not shifting any goalposts, but simply referencing more evidence on the fundamental issue: that this study was intentionally biased and misleading with the goal of "proving", by any means necessary, a conclusion of which the authors had 0 interest in genuinely testing. As I suspect we'll be wrapping up, I simply want to thank you for the interesting and lively discussion on this issue. It's rare two people can disagree on the internet for more than a few posts without things devolving into 'You're a poopy face.' 'No, you!' [1] - https://en.wikipedia.org/wiki/Willie_Soon https://en.wikipedia.org/wiki/Willie_Soon
- mlyle 4y ago> Imagine for a moment that this study was trying to demonstrate that e.g. climate change was primarily caused by solar variation a la Willie Wei-Hock Soon [1]. And he provided the exact same quality of evidence, and the exact same "issues." I suspect we don't agree on what the "exact same quality of evidence" would be. But the prior probability matters, too. A trial where a die looks slightly-biased-towards-6 (with weak significance) after 3 prior trials where it looked strongly-biased-towards-1 (with high significance) doesn't do much to change our mind about the previous findings. Base rate fallacy, yada yada yada.