u/Will_Tomos_Edwards

I would say it was tremendously good luck that Lee Marvin turned down that role. Marvin is just too sophisticated and polished or something. I honestly see him as more of a man in a white hat as well. What I have come to realize about life is that sometimes you will encounter these "best decisions I never made." Marvin turning down that role was one of the best decisions Sam Peckinpah never made. Not sure if I can imagine a better guy than Holden for Pike.

Hollywood seems to be filled with these "great accidental casting decisions."

In The Wild Bunch when they leave Crazy Lee to guard the hostages are we to see this as basically betraying or taking advantage of Crazy Lee, where there was no hope of him surviving? Or did the Bunch have some idea in mind of how he could survive and escape?

At my school, you have the option to take a 4th-year project-based course to complete your undergraduate degree. You could also take 4th-year electives like Topology or Combinatorics instead. What do you think would look better for getting into a good master's program?

Edit: I have had the chance to work as an RA on a pretty hardcore math research project, so not bereft of research experience.

I recently rewatched The Magnificent 7 for the second time in my life. "Magnificent" is very fitting. It is indeed a magnificent and beautiful movie.

However, something jumped out at me that I'm not quite sure how I feel about: Calvera let them go.

Given my own system of ethics, I would see that as pretty weak and dishonourable that the seven took advantage of his magnanimity. Frankly speaking, a bad hombre like Calvera is liable to say, "just kidding," after marching them out of town, "we're not giving you your weapons back," and then make sure those guys never pose a problem for them again.

What made Calvera do that, I think, is a mixture of pragmatism in that he doesn't want those farmers to see him as a complete monster. He wants them to be willing to "do business" with him. But also, Calvera genuinely seems to be a man of faith and principles. I think he genuinely would have felt bad about executing the seven.

So this does something incredibly bold from a storytelling perspective. The seven cannot be seen as pure paladin "knight in shining armour" heroes in that final battle. They have gone back on their word and taken advantage of Calvera's kindness.

It's a "bad look" for the heroes.

One of them makes no bones about the fact that all he cares about is money, and Chris lies through his teeth that he came that close to making it big, so he can feel some satisfaction as he lies dying.

And all of them except for two die in that final battle, and some of Calvera's men get away, and who knows what they will do in the future.

What a beautiful movie that de-glorifies violence.

So obviously, the Neolithic Inhabitants of the British Isles don't contribute much DNA to the modern populations, but with that being said, I am wondering about the differential impact on different parts of the British Isles. If there is any recent work (both accademic and from many of you citizen scientists) I would love to see that. Is there any case for isolated areas like the Scottish Highlands, North Wales, Orkney, having more pre-Bronze Age British DNA?

I believe Ancestry has a lot at this point, but I am wondering how diverse they are? Are many First Nations across the continent included in their database?

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A) Since you have n = 80,000 it shouldn't be a problem to control for between 50 and 100 dummy variables in your regression analysis. Don't worry about trying to map your categorical variables to something quantitative (e.g., a pre-existing score for each category). You have enough sample size to justify this. You should be able to use 100 control variables without any issue.

B) Even though we have n = 80,000 we should still adhere to the principle of parsimony as much as possible and try to limit the number of dummy variables by collapsing the number of categories or mapping to quantitative predictors as much as possible. After all, there could be certain partitions of the dataset with very few observations.

It has come to my attention that many economists think you can put a ton of predictors in a model and not worry about multicollinearity or VIF diagnostics, because really, we just care about a single outcome/coefficient. I have heard the argument that with VIF diagnostics being out of whack, while it's true that we can no longer trust the predictions of the regression model, we can indeed trust the coefficient that we are interested in (i.e., the coefficient is a valid estimate of the population coefficient as long as there is enough sample size etc.,).

But I have serious concerns about this argument. Predictions being inaccurate => coefficients are inaccurate. I don't see how I can still trust the coefficient I'm interested in if the model as a whole has problems.

I'm frankly blown away by this. First of all, the show arguably focuses in on the Empire more, simply because an absolute monarchy is a source of better melodrama and storytelling. There is more possibility for exciting adventure in such a setting, I guess? My takeaway from the show is that the Empire is simply a terrible, disgusting place. FPA has its problems... but there is no comparison with the Empire. And finally, the most egregious thing here is that the Empire's elite and their entire military appear to be 100% white, and the author isn't white!!!! So are you guys alleging that the author is a self-loathing Japanese? Honestly, the people thinking LOGH is pro-Empire need to think this through a bit more.

Wondering what other people think of Barbarians on Netflix? For me, it's the most historically accurate show or movie depicting that era that I have ever seen. I felt like it's the closest you could get to going back to that era in a time machine and watching things play out.

The title is self-explanatory. Not many official ways to play this game these days. On iOS it is like $4 last I checked. I guess it's got to be worth it at that price?

This course is preceded by its reputation. We all know the lore about how difficult this course is. I completed it over the winter semester, and I want to give a debriefing that I think will be helpful.

I've heard a pure math major say it is the hardest math course below the 3000 level. I've heard applied math, physics, and comp sci majors say it is the hardest math course they've ever taken. Period.

The lore surrounding this course is terrifying, and I went in appropriately scared.

In the end, I did well in the course, and I actually don't think it was the toughest course below the 3000 level, but... it was the toughest exam below the 3000 level. That's just my take, and here are my four main takeaways:

1. Just be prepared: Much of the lore surrounding how brutal this course is comes from people who did MATH 1025 (Applied Linear Algebra I) instead of MATH 1021 (Linear Algebra I), and otherwise were not prepared for this course. You want to make sure you have the solid foundations related to proofs and linear algebra before doing this. That will make a world of difference.
2. The tests aren't that bad: I was relieved to find that the tests weren't that bad. Keep in mind, I'm a pure math major, and you are not getting the opinion of the median student in that class from me; nonetheless, I felt like the tests were very manageable, and I did not have to work overly hard in order to do well on them. This is because the tests cover narrow subject matter that a person can feasibly learn in a few weeks.
3. The final exam is brutal: I spent anywhere from 1 week to 1.5 weeks studying for the final exam non-stop. I knew I had to do this because the final covers so much disparate material that is all really quite varied. Taking the tests a few chapters at a time is fine; combining them all together at the end is something else entirely. It was so intense studying for that thing, and it took a physical toll on me. Before going into the final exam, I listened to the war chant from the new trailer for Dune pt 3. That song honestly came to mind. That was the mood. It was so intense.
4. The concepts are the hardest part: I spent a week, maybe more, getting my mind around the change of basis and the "magic rectangle."

So one strategic takeaway is to prepare for tests at all costs, and don't miss tests at all costs. If your prof does assignments, be grateful for that. You do not want the weight on the final exam for this course.

edit: if I really had to choose, I would give a hot take for the hardest math course below 3000 level as MATH 2030!! It is conceptually straightforward, and conceptually it differs little from first-year stats or even something like AP stats, which high schoolers take. But alas, the problem-solving is brutal. We are talking brutal brain teaser-style word problems.

Honestly, the vast majority don't support the regime. I feel like shipping some serious guns and ammo into Iran is the best way to overthrow this regime.

In this study from 2013, they used strontium and oxygen isotope analysis to look at medieval skeletons from Wales. Clearly, this was before ancient DNA analysis took off. Has anyone looked at these samples again using DNA analysis?

https://www.sciencedirect.com/science/article/pii/S030544031300023X

I heard that the CLT will kick in for a massive sample size and so it doesn't matter so much for a regression model if the Q-Q plot deviates from normality. Is this true?

The distance from Russia to Alaska is only a couple of kilometers, how come North America was not colonized by Asian Empires long before Europeans got there?