Science - a symposium. (Feat. SMBP)

[Kyanbu The Legend]

Originally Posted by Aerozord

its why we need to spread out past the earth. Dont want all your eggs in one basket.


I heard that if jupiter didn't intercept shoemaker-levy that it might have hit earth. Not sure if thats a hypothetical could have, or if there is math there, but still

And also because Earth is starting to become over populated. The developement of space colonies and terraforming planets inn the next century is a must at the rate our population is growing.

[McTahr]

Originally Posted by Kyanbu The Legend

And now I love Jupiter. Best planet in the system. Cause it helps protect us from cosmic annialation.

Jupiter's a pretty cool gal.

This is why fatties need love too.

The sad thing about actually being a scientist is that the day-to-day level of grunt work and tedium never really seems to translate into the glamorized ideal of the scientist that the media likes to play up. Like my research would be an automatic snoozefest, it's that bad.

[Osterbaum]

And also because Earth is starting to become over populated.

Yes, well this is a problem that could also be solved by more efficient use of resources, effective recycling, accepting a lower standard of living (in terms of material anyways) and population control. Just spreading out elswhere seems kind of a cop-out.

e:

Like my research would be an automatic snoozefest, it's that bad.

What's it about?

[Gregness]

Okay, I was planning on making a thread about his eventually, but I suppose since we have a sticky for this sort of thing now this'd be a better place for it.

So, essentially, a psychology research paper got published last week discussing new ways to measure personality differences between genders. Apparantly, it is generally accepted that personality-wise, the two genders are more similar than different and this paper challenges that conclusion on the basis of methodology.

Originally Posted by The Authors

Univariate Versus Multivariate Effect Sizes.

Since personality is a multidimensional construct, the question of how to quantify the overall magnitude of sex differences in personality is far from trivial. A common way of dealing with multiple effect sizes is to simply average them. For Big Five traits, the average absolute effect size across studies is = .16 to .19, corresponding to an overlap of about 87% between the male and female distributions [11], [16]. When narrower traits are measured, average effect sizes increase somewhat. For example, Costa and colleagues [49] analyzed sex differences in FFM facets; their average effect sizes were = .24 (US adults) and = .19 (adults from other countries). As reported above, Booth and Irwing [54] found = .26 for observed scores on the 15 primary factors of the 16PF. Finally, the average effect size in Weisberg and colleagues [53] was = .21 for the Big Five and = .26 for the ten FFM aspects (uncorrected raw scores).

The problem with this approach is that it fails to provide an accurate estimate of overall sex differences; in fact, average effect sizes grossly underestimate the true extent to which the sexes differ. When two groups differ on more than one variable, many comparatively small differences may add up to a large overall effect; in addition, the pattern of correlations between variables can substantially affect the end result. As a simple illustrative example, consider two fictional towns, Lowtown and Hightown. The distance between the two towns can be measured on three (orthogonal) dimensions: longitude, latitude, and altitude. Hightown is 3,000 feet higher than Lowtown, and they are located 3 miles apart in the north-south direction and 3 miles apart in the east-west direction. What is the overall distance between Hightown and Lowtown? The average of the three measures is 2.2 miles, but it is easy to see that this is the wrong answer. The actual distance is the Euclidean distance, i.e., 4.3 miles – almost twice the “average” value.

The same reasoning applies to between-group differences in multidimensional constructs such as personality. When groups differ along many variables at once, the overall between-group difference is not accurately represented by the average of univariate effect sizes; in order to properly aggregate differences across variables while keeping correlation patterns into account, it is necessary to compute a multivariate effect size. The Mahalanobis distance D is the natural metric for such comparisons. Mahalanobis' D is the multivariate generalization of Cohen's d, and has the same substantive meaning. Specifically, D represents the standardized difference between two groups along the discriminant axis; for example, D = 1.00 means that the two group centroids are one standard deviation apart on the discriminant axis. A crucial (and convenient) property of D is that it can be translated to an overlap coefficient in exactly the same way as d: for example, two multivariate normal distributions overlap by 50% when D = .85, just as two univariate normal distributions overlap by 50% when d = .85 [60], [61]. The only difference between d and D is that the latter is an unsigned quantity. The formula for D is



where d is the vector of univariate standardized differences (Cohen's d) and S is the correlation matrix. Confidence intervals on D can be computed analytically [61], [62] or bootstrapped. For more information about D and its applications in sex differences research, see [2], [63], [64].

I've had some linear algebra and some statistics classes so on the surface this seems reasonable. Basically (if I'm reading this right) in order to find the 'true' distance between male and female's personality test scores you treat them as coordinates on an axis rather than numbers in a vacuum.

The authors then re-analyze an (apparantly) well known gender study using this new method:

Originally Posted by The Authors

The results were striking: the effect size for global sex differences in personality was D = 2.71, an extremely large effect by any psychological standard, corresponding to a 10% overlap between the male and female distributions (assuming normality). Even removing the variable with the largest univariate effect size (Sensitivity), the multivariate effect was D = 1.71 (24% overlap assuming normality). These effect sizes firmly place personality in the same category of other psychological constructs showing large, robust sex differences, such as aggression and vocational interests. Global sex differences in aggression, computed on observed scores across measurement methods, range from about D = .89 to D = 1.01 [2]; vocational interests show strong sex differentiation along the “people-things” dimension, with observed effect sizes consistently around d = 1.2 [11].

So, seeing as gender issues are kind of a thing on this board I thought you guys might find it interesting. Anecdotally, I don't think I agree that there's this gigantic difference in personalities between sexes but this is data aggregated from over ten thousand people and I guess that counts for more than my own experience.

Or I'm just in that 10% of people who overlap, whatevs.

My Concerns/Thoughts

Psychology isn't my field, so I don't know that I'm really prepared to effectively analyze the article to see if it's valid or whatever, but my general math and science background says the analysis method is reasonable.

Also, The hosting site is the Public Library of Science, which I haven't heard of 'till now. Apparantly it's an open-access online journal that takes submissions from any scientific subject. A quick internet search seems to show it's pretty legit. I'm totally willing to chalk my ignorance of this to the fact that my own readings are in a completely different field.

So anyways, as I said psychology is out of my depth so I'm interested in what you guys think of this.

[Professor Smarmiarty]

Originally Posted by McTahr

This is why fatties need love too.

The sad thing about actually being a scientist is that the day-to-day level of grunt work and tedium never really seems to translate into the glamorized ideal of the scientist that the media likes to play up. Like my research would be an automatic snoozefest, it's that bad.

I smoke cigarettes and yell at people all day. That's pretty glamorous.

as for the psychology article, I've done a little neuropysch (mostly as it relates to evolution) but hardly an expert. The thinking behind the paper seens solid enough though it still reliesupon basic models of personality (being measurable on various axes and tests to do so) which are possibly not valid.
And really it raises more questions- such as the reason for the difference- though I would bet like prettymuch all these things on gender differentiated rearing- whether its culturally/historically/economically specific.

[McTahr]

Originally Posted by Osterbaum

What's it about?

Clean coal research. Specifically the storage of greenhouse gases in various geological formations through various means.

[Professor Smarmiarty]

Just stick them in some tupperware at the back of the fridge.

Or build two coal plants one of them upside down. This one does reactions in reverse and thus turns your gas back into coal.

[Azisien]

We have a lot of nuclear weapons too. Can we somehow use those to blow up the bad gases?

[Arhra]

Originally Posted by Aerozord

its why we need to spread out past the earth. Dont want all your eggs in one basket.

When the false vacuum collapses, its possible that all matter in the universe will instantaneously cease to exist.

[Aerozord]

Originally Posted by McTahr

The sad thing about actually being a scientist is that the day-to-day level of grunt work and tedium never really seems to translate into the glamorized ideal of the scientist that the media likes to play up. Like my research would be an automatic snoozefest, it's that bad.

But what about geologists?