It's an interesting read but it's concepts are now 40 years old and he makes assumptions that have since been proven to be invalid and extrapolates the function of the gene to moralistic qualities in humans, which is a little silly to be honest. More than that, I'm not sure he's really made any significant contributions to science; he is more of a philosopher, and his work should be read as such, with all its attendant reservations. It is a good read as a work of fiction or philosophy, however you might consider it.
Turns out that this topic has already generally been recognized as a subject ripe for research: How do the statistics of pro athletes change before and after dating a Kardashian/Jenner? Perhaps someone with an Ivy League degree will put their considerable intellect to good work on this important question.
I don't think it ever really left the quagmire. There's not been a single piece of insight in this entire mess.
LMAO. Impossible to believe that some of you function in the real world -- like, among other humans. Christ.
I just use it as a basis, I read other books and go back to that one. I like reading about Nassim Taleb a lot, and a lot of rare occurrences in financial market, the economy before/after/during wars, and negotiation books. I think Selfish Gene is a good book to stimulate you a bit, but it's not the best or greatest book I just consider it a foundation book.
I guess it's really predictive analytics that has no business in this game. There's a huge movement for this, and whether it's ESPN hiring that bimbo from Northwestern with a Ms. in predictive analytics, ESPN spewing out extremely obscure stats(like 17 pts, 5 rebs, 4 assists, and 1 steal), there's no really place for it. Morey does have access to the data, but it's not seasoned. You need this data, with the same perfect in and around it, for it to actually be something you formulate a thought or motion with. You can't take this data raw and apply it, and for the "advanced stats" people they take the data raw, refine it a bit, maybe another bit more, and apply it. There's just no purpose of that. It's just like history in relevance to how sports play out. The truth is there's nothing linear. Like people say oh the Panthers can't win it out, only the dolphins have done that before. Impossible happens because no variable is predictable in sports. No one can continue this shooting, or this or that. Like how many variables, predictable one's, would've told you Kobe Bryant would 81 points in a single game? The next thing to happen is the 0-3 comeback, just because it's never done doesn't mean it won't happen. This is a great question, let me get back to it. I mean the only formidable data we have is Kris Humpries and Lamar. Did they not have their best years with the Kardashians? I do not know what other athletes these whores have dated so this would help a bit. Listen, if you date a Kardashian. The Kardashian doesn't want some sucker, if Harden keeps playing like a pansy boy, Khloe will dump him.
alright, I've bitten my tongue long enough. I'll deny it. The Selfish Gene is a terrible book. Stephen Jay Gould destroyed Dawkins in the 80s, and Philip Kitcher's Vaulting Ambition explains where Dawkins and the sociobiologists went wrong. now can we get back to the crappy discussion of crappy statistics?? :grin: thank you.
Obviously what one considers foundation varies from person to person but I think the impact of that book on the scientific field was minimal, though it was a cultural phenomenon. I'm not sure there's much of value you can take away from his work, but to each their own.
you still have no thesis statement. also it seems like you are under the impression that 'statisticians say no team will ever come back from down 0-3' and 'statisticians said kobe would never score 81 points in that game.' for your information no intelligent statistician would say such things
Ha, sure. Fair point. My thesis is really Ludic fallacy. Structured randomness isn't a measuring stick or a benchmark.
Ludic Fallacy: -It is impossible to be in possession of the entirety of available information -Small unknown variations in the data could have a huge impact. -Theories/models based on empirical data are claimed to be flawed as they may not be able predict events which are previously unobserved, but have tremendous impact(injuries, unexpected trades, the Josh smith yolo effect at 3s in the WCF, the Warriors going injury free) That's my argument against using stats to simulate/model. It's always the UNKNOWN that takes advantage, the best things to do is control which variables you can. Like even for GSW, what is the likelihood that a rookie head coach wins the championship? What's the likelihood TWO rookie coaches up in the championship series? Stuff like that, it's just too difficult to determine. Just like history. Right now, I think everyone would be AGAINST hiring a rookie coach for Houston and mid-season, I agree, but you can't use HISTORY as a relevant factor too in such decisions. It's too tough to use, and it is not relevant.
