Messages

What is the ultimate goal here? Depression of badger populations, or elimination of badgers? If the former, I can get behind it, though if you really want to get rid of the problem vaccination is a much better method. If the latter, it seems no different than the attitude towards wolves in USA.

Apple Smack: We all Deserved It.

The Butthurt Bandwagon

Drug Thread Denouement

Drama Cycle Blues

What is an MRA? 

Male/Men's Rights Activist. Yes, they are exactly what they sound like.

Ohhh, those guys. Yeah I can see why people would take issue with them.

I'm curious how they link a-theism to male rights. Does it involve lots of "evolutionary psychology" ?

Always. Prime material for Pick-Up Artists (PUAs) as well.

http://www.youtube.com/watch?v=5XzMWL1Cgk4

It's right near the end. Kind of crappy video, but you can see it splatter.

In this post: I deliver: http://www.freerepublic.com/focus/f-news/1139825/posts

Members of the fathers' rights group Fathers 4 Justice stunned the United Kingdom Wednesday by pelting Tony Blair with condoms filled with colored flour while he spoke at the House of Commons. Fathers 4 Justice fights primarily for greater contact between fathers and children following parents' separations and divorce but holds interest in a broader range of institutionalized injustices against divorced fathers and children. Their attack prompted the immediate suspension of the session and was reported by television and newspaper journalists throughout the world.

Belief specifically in neptune might be dumb.

Why?

If he is understood to be some guy swimming around in the mediterranean causing earthquakes them that is a rather strange belief. Just as strange as the idea of jehovah having a literal cease and cloud throne.

I'll concede that a literal reading of, let's say, Homer probably isn't very representative of reality.  However, isn't it possible that Neptune does exist even if he doesn't have a beard and sea throne just like Jehovah not having a beard and cloud throne doesn't automatically discount the existence of God?  And ultimately isn't the idea of multiple gods just as possible as a single God?

I don't mean to single you out, Twid, but I've noticed that most people who believe in some form of deity (or a variation thereof) but don't subscribe to an established religion tend to believe in a monotheistic deity (or consciousness, spirit, being, etc).  I'm curious why that is. Is the idea that a single God created the universe, set it in motion, and then stepped back any more or less possible than a group of deities doing the same?  Is the idea that the universe as a whole is one massive organism any more or less possible than the idea that each individual galaxy is an organism, and the universe as a whole is simply a school of organisms swimming through the cosmic sea?

A lot of people throughout history, at least European and Near Eastern history, tend to gravitate towards monotheism.  I wonder why that is.  I wonder what about our human nature leads us towards the idea that a single deity is more logical or more possible than multiple deities.   But isn't there the same amount of evidence for polytheism as there is for monotheism?  I accept that God might exist because there's no proof to the contrary.  But couldn't the same be said for multiple gods?  Or maybe some kind of infinite number of animistic spirits?  For all we know the Big Bang could be what happens when a celestial Mike fires up the misaligned cosmic ball mill.

Or maybe it just seems like our nature drives us towards monotheism because I live in a culture/hemisphere that has had a lot of contact with monotheism throughout history?

It was pretty much just one sun baked desert tribe that made the leap from "Our god is better than your god" to "Our god is perfect in ways we can't even describe. Your god just plain doesn't exist." The practice of telling people that their god(s) don't exist became extremely popular over the next couple millennia, to the point where people would seek out new territories on the off chance they could discover people and tell them their god(s) don't exist. Then said people got really good at sailing to new territories, and now the various empires of "Knock, knock, your god is fake" control most of Europe, Africa, the Americas, and dryer and colder parts of Asia.

The surviving major power bases of polytheism, pantheism, and functional atheism ("Gods are very real, but they play no part in salvation/enlightenment) are all in Asia. India traditionally hasn't been very evangelical, except for Buddhism. China recently went through a phase where it decided to disbelieve in gods, agriculture, and economics all at the same time, and it's taking some time for them and their neighbors to recover from the entirely predictable results of that.

Follow-up to add:
The new wave atheists who do nothing but go around telling people they're stupid for believing in g/God(s) can thus be thought of as the 4th Abrahamic religion, taking the seed idea of "{God} doesn't exist" from monotheism and extending it to its logical conclusion of no god existing.

Small a atheism: I hold no beliefs in deities.
Large A Atheism: I hold no beliefs in deities and that's the no-God's honest Truth.

Kai's Atheism: I hold no beliefs in deities, and discovered that there were more important things to care about after making that choice, namely the well being of other humans. And anyone who doesn't like my use of the word can wank off. That's the no-God's honest Truth.

You might consider saying something to the Atheists who like to bandy the word about as an umbrella that covers their bigotry. I'll explain why sometime. But not tonight, I have a pretty lady to meet for drinks.

I do. They don't like that very much. They like a strict dictionary definition, which is amoral and therefore allows them to be douchecanoes. This is contrary to the PZ Myers school of Atheism, which asks, "Okay, we're on board that there are no gods, now what?" and proceeds to be pretty much humanism from there on out. It's a huge fight right now, between the shitbags and people who want the shitbags to fuck off. I posted a link earlier in this thre...oh, I just realized: were you talking about people on here?

What is an MRA? 

Male/Men's Rights Activist. Yes, they are exactly what they sound like.

I see this thread has returned to it's roots:  hating on Nigel.

Well, you know, it's a fine old tradition, and it's easier than thinking.

I don't see any of the atheists who were hating on Nigel hating on the MRA's in atheism. (were they aware?) It's a pretty much white boys club, is the hardcore subsection. I know Kai hates on these assholes, as we have discussed this previously (especially after Dawkins on Rebecca Watson and Elevatorgate).

The one hardcore atheist guy I know is going down That Path and I had to endure him talking over me and my mate Jeanne at payne's birthday outing (we ate  epic burgers and ham hocks and then failed to get drunk because of the amount of food consumed.) he's an obnoxious knob and I hate gaming with him.

I do indeed hate on those assholes, with a passion. MRAs, PUAs, racists, sexists, bigots, the lot. Often includes followers of Richard Dawkins and the late Christopher Hitchens, who are/were both sexist/racist in that very stick-up-the-ass way that only overstepping academics seem to perfect. Dawkins wrote an excellent text on genetic evolution and his social opinions still ended up stilted, stupid, and odious. Maybe they always were. In any case, I don't praise them.

Belief specifically in neptune might be dumb.

Why?

If he is understood to be some guy swimming around in the mediterranean causing earthquakes them that is a rather strange belief. Just as strange as the idea of jehovah having a literal cease and cloud throne.

I'll concede that a literal reading of, let's say, Homer probably isn't very representative of reality.  However, isn't it possible that Neptune does exist even if he doesn't have a beard and sea throne just like Jehovah not having a beard and cloud throne doesn't automatically discount the existence of God?  And ultimately isn't the idea of multiple gods just as possible as a single God?

I don't mean to single you out, Twid, but I've noticed that most people who believe in some form of deity (or a variation thereof) but don't subscribe to an established religion tend to believe in a monotheistic deity (or consciousness, spirit, being, etc).  I'm curious why that is. Is the idea that a single God created the universe, set it in motion, and then stepped back any more or less possible than a group of deities doing the same?  Is the idea that the universe as a whole is one massive organism any more or less possible than the idea that each individual galaxy is an organism, and the universe as a whole is simply a school of organisms swimming through the cosmic sea?

A lot of people throughout history, at least European and Near Eastern history, tend to gravitate towards monotheism.  I wonder why that is.  I wonder what about our human nature leads us towards the idea that a single deity is more logical or more possible than multiple deities.   But isn't there the same amount of evidence for polytheism as there is for monotheism?  I accept that God might exist because there's no proof to the contrary.  But couldn't the same be said for multiple gods?  Or maybe some kind of infinite number of animistic spirits?  For all we know the Big Bang could be what happens when a celestial Mike fires up the misaligned cosmic ball mill.

Or maybe it just seems like our nature drives us towards monotheism because I live in a culture/hemisphere that has had a lot of contact with monotheism throughout history?

It was pretty much just one sun baked desert tribe that made the leap from "Our god is better than your god" to "Our god is perfect in ways we can't even describe. Your god just plain doesn't exist." The practice of telling people that their god(s) don't exist became extremely popular over the next couple millennia, to the point where people would seek out new territories on the off chance they could discover people and tell them their god(s) don't exist. Then said people got really good at sailing to new territories, and now the various empires of "Knock, knock, your god is fake" control most of Europe, Africa, the Americas, and dryer and colder parts of Asia.

The surviving major power bases of polytheism, pantheism, and functional atheism ("Gods are very real, but they play no part in salvation/enlightenment) are all in Asia. India traditionally hasn't been very evangelical, except for Buddhism. China recently went through a phase where it decided to disbelieve in gods, agriculture, and economics all at the same time, and it's taking some time for them and their neighbors to recover from the entirely predictable results of that.

Follow-up to add:
The new wave atheists who do nothing but go around telling people they're stupid for believing in g/God(s) can thus be thought of as the 4th Abrahamic religion, taking the seed idea of "{God} doesn't exist" from monotheism and extending it to its logical conclusion of no god existing.

Small a atheism: I hold no beliefs in deities.
Large A Atheism: I hold no beliefs in deities and that's the no-God's honest Truth.

Kai's Atheism: I hold no beliefs in deities, and discovered that there were more important things to care about after making that choice, namely the well being of other humans. And anyone who doesn't like my use of the word can wank off. That's the no-God's honest Truth.

I see this thread has returned to it's roots:  hating on Nigel.

Well, you know, it's a fine old tradition, and it's easier than thinking.

I would have been a world-famous scientist, but then Nigel.

Funniest thing in this poop of a thread.

Okay. I'm done with the butthurt. Here's some food for Germans.

http://www.economist.com/news/briefing/21588057-scientists-think-science-self-correcting-alarming-degree-it-not-trouble

Academic scientists readily acknowledge that they often get things wrong. But they also hold fast to the idea that these errors get corrected over time as other scientists try to take the work further. Evidence that many more dodgy results are published than are subsequently corrected or withdrawn calls that much-vaunted capacity for self-correction into question. There are errors in a lot more of the scientific papers being published, written about and acted on than anyone would normally suppose, or like to think.

Various factors contribute to the problem. Statistical mistakes are widespread. The peer reviewers who evaluate papers before journals commit to publishing them are much worse at spotting mistakes than they or others appreciate. Professional pressure, competition and ambition push scientists to publish more quickly than would be wise. A career structure which lays great stress on publishing copious papers exacerbates all these problems. "There is no cost to getting things wrong," says Brian Nosek, a psychologist at the University of Virginia who has taken an interest in his discipline's persistent errors. "The cost is not getting them published."

The whole article is on mistakes and falsehoods in scientific publishing, and why replications (which are a kind of post publication peer review) are absolutely necessary and not happening. And you know what? This DOES upset me. I accept completely that peer reviewed journals are going to slip up sometimes, that peer reviewers are going to fail, that mistakes and falsehoods are going to be published. It happens, it's going to continue to happen, there's not a damn thing anyone can do to eliminate it completely. Which is why follow ups are so damn important.

Maybe Science really /is/ broken/short circuit, and if it IS, then the broken part is that it's become like media. The entire point is to pour out stories, with not a bit of thought to questioning whether the stories that just got poured out were any good. THATS the supposed self correcting, and since we've been letting the journalists do it FOR us, the letters are still PR but pronounced "public relations" and not "peer review". This is disturbing. And I don't know fuck all I can do about it.

Also, I've been wondering who the hell that guy in the picture is.

Fantastic article, Kai! One of the questions that's been brought up somewhere around here is why negative findings are so rarely published, even though negative findings can stand to tell us more, more definitively, about a question than positive findings. They aren't sexy, they aren't speculative, but sometimes a solid "Nope!" (if you'll forgive me for the expression) can be more meaningful than a bright and shiny "Maybe".

I find it a bit troublesome that apparently not all scientists are required to take statistics. I admit that I hated statistics; that's no secret. I was bored to tears. But as time goes on I am finding that I am really really glad that I took them because it makes what I'm looking at make so much more sense when I'm trying to interpret and understand the results of a paper, including being able to look at powers and levels of significance and say "hmm, that is far too high an error rate with far too low an n for me to take these findings very seriously without a great deal of further investigation".

To get back to this: yes, negative findings can tell us things. The really important thing is to follow up on both positive and negative results, repeat experiments, and question the authority of the literature. It takes time, but it must be done.

As for statistics...the necessity of statistics is determined by how little variability your data have, and how large your effect size is. If your effect size is huge, and your variability is low, then statistics is pretty much unnecessary. You just /look/ at the thing. A lot of time physicists don't use statistics. But biology, for example, is messy. There's a great deal of variability in biological systems, and the effect sizes are often small and still meaningful. Therefore, statistics is standard. In our PhD program, everyone is required to take at least one statistics course, sometimes multiple.

ETA2: Oh, I think I just repeated what you said, except more complicated, and with more flailing at the end.

Ahhhh OK thanks, my head was spinning a bit there!

Sorry! My head was spinning too, trying to figure out the math. But you have the right of it; these proportions of error are not meant for determining after the fact what the possibility of statistical error is. Alpha, beta, and power are supposed to be used for individual hypothesis tests, not for judging the error rate of a large number of different tests, and are supposed to be computed before the test, not after.

Wait. 100 "true things", 5% error rate...


Ah! Where's the rigor? Shouldn't we be testing more than once, if we have a known error rate?

Something is just not right about the middle part of that figure. It needs some Bayes-jutsu.

This is what it is saying:  there are 1000 test cases. 10% are "yes". There are 100 true "yeses" and 900 true "nos". A power of .8 means 80% of the true "yeses" will be captured by the test. That means there will be 20 apparent "nos" that are really "yeses". There is also a .05 false positive rate. That means that out of 900 TRUE "nos", 45 will appear to be "yeses". False positives look exactly like true positives.

However, although their math works out just fine if they are talking about a 5% false positive rate, they seem to have confused confidence level with false positive rate. That is not what a .05 confidence level is. A .05% confidence level is a measure of how likely the test is to have produced data this far or farther from a no-change mean by chance alone. It is not an error rate. Therefore all their numbers are hopelessly borked and meaningless.

Actually, they're right about that. Alpha is not only the p-value needed for significance, it is also the chance of a Type I error. That is, if the null hypothesis is true, it is the fraction of replications you would expect, by chance alone, the estimation of the parameter (usually the mean) to fall outside that interval and be considered significant. And...I think I just explained it.

The problem is, the article words the situation weirdly. Instead, it should be like this.

1. Of 1000 hypotheses, perhaps 100 of these will reject the null hypothesis in favor of the alternative.

2. Given an alpha of 0.5, we expect 1/20th of those tests that should not have rejected the null hypothesis to actually do so. 1/20th of 900 is 45. These are the false positives. Given a power of 0.8 [I'm not sure how they got a Power of 0.8, I just have to take their word for it, since calculating Power by hand is complicated, since calculating beta is complicated, and Power is 1 minus beta.] , our beta is 0.2, which means 20% of the time when we /should have/ rejected the null hypothesis, we will not. This is the type two error, and means that 0.2*80 = 20 negative tests are actually false negatives, they should have rejected the null hypothesis.

3. If researchers only publish positive test results,  that means that by chance alone there will be 9 false positives published for every 16 positives, meaning more than half. The ratio for false negatives to negatives is .02, which means the random chance for a false negative is much lower than false positive, if all tests are equally published.


Now, I have a few problems with this, The first is that people are generally not interested in detecting sameness, they are interested in detecting differences. At least in hypothesis testing And furthermore, those alpha and beta values? They are /tailored/ to a high standard of detecting differences. We could easily design a test where the rate of false negatives is higher, and all we have to do is decrease the alpha value. Make it tiny. Make it small enough, and the false negative level will skyrocket. (ETA: Really why we use 0.05 as our alpha is based around something called the central limit theorem, which has to do with central tendencies of variability and the rareness of extreme values. It assumes data are normally distributed. They aren't always.)

But here's the main problem, and that's the premise of assuming a very uneven ratio of negative to positive results. People do not run around testing hypotheses at random. It is, frankly, a waste of time. When the article assumes a 10 to 1 ratio of negatives and positives, it is exactly that, an assumption. What if we make it 50:50? Well then, 1/20th of 500 is 25, and 0.2 times 500 is 100. Which makes the ratio of false negatives to negatives 25:400 or 0.06, and the ratio of false positives to positives 100 to 475 or 0.2, which is a HELL of a lot lower than more than half.

This means the whole figure is nonsensical, because it is based on an untested assumption which is the ratio of negatives to positives in hypothesis testing. It does the /math/ right, but it starts from a flimsy premise. These post-hoc power tests have been looked down upon for years, this is not how you use power.

What you use power for is to decide on an appropriate sample size for the effect size you are looking for. In other words, if you are going to test a fertilizer, and you only care if the tree growth difference is larger than a foot (this is the effect size), power calculations can help tell you what an appropriate sample size would be to detect that difference between your control and treatment, given the natural variability and the desired alpha (again, the probability of a Type I error, usually 0.5). You can then rest assured that, if you have properly estimated the inherent variability, that the appropriate sample size will give you a significant p-value if and only if the effect size is as large as you would want it.

This is turning into a tangent, but it must be said: a significant p-value is /meaningless/ without knowing the effect size. You could say that the difference between those two tree fertilizers is significant, but if the actual difference is only a change in inches, who gives a shit? When you see a significant p-value in a paper, always always always check what the actual difference is, what the units are, and if the difference even matters.


And I think that's all for now. This message has been brought to you by the statistics software program R and the number 0.05.


ETA2: Oh, I think I just repeated what you said, except more complicated, and with more flailing at the end.

Wait. 100 "true things", 5% error rate...


Ah! Where's the rigor? Shouldn't we be testing more than once, if we have a known error rate?

Something is just not right about the middle part of that figure. It needs some Bayes-jutsu.

It's the false positives. 5% rate of false positives is 5% of those studies that had significant results, not five percent of the total, right?