Totally agree. Weren't there even some studies a while back suggesting that changing how you hold/use your mouse from time to time could help avoid repetitive stress injuries? I vaguely remember something like that, but don't quote me on it.

Anyway, if this "improved" mouse ever becomes widespread, your face might be hurting, too, because you will probably be holding the palm of your hand there most of the time.

Okay. Against what, exactly, are you arguing? When, at any point, have I claimed that "the data are the analysis of the data" or any such nonsense?

Let me remind you of one of your original claims:

Do you not understand that "patterns in data" includes correlative statistics? If not, let me make this clear: You originally claimed that neither data, nor the patterns in data, are "evidence". I've tried to explain why, to scientists, patterns in data, including correlative statistics, most certainly are evidence. That is all. For some reason, instead of responding to any of that, you want to keep arguing about the definition of "data", which, as I've also explained, was never in dispute.

Cheap insults aren't necessary. Look -- your original post simply reflected a misunderstanding of how a particular bit of terminology is used by scientists. I thought it might be helpful to explain why. I apologize if I inadvertently offended you somewhere along the way.

No, I don't have a different definition of "data". My point was that your original post repeatedly confuses "evidence" and "proof". As I said, data, and more specifically, the patterns in data (correlative statistics are one example), are used as evidence all of the time in science. That is, in a nutshell, how science works. Data provide evidence, not proof, for or against alternative hypotheses. The strength of the evidence depends on the strength of the data, which encompasses all of the potential data problems you discussed in your original post. None of this has anything to do with disputing the definition of "data". Data are pieces of information (just as your Wikipedia article says), and collectively, they can provide evidence for or against scientific hypotheses. Another way to state it is to say that in science, evidence comes from data.

Your blanket statements that "data isn't evidence" and that "correlative statistics are not evidence" are not supported by the way real scientists actually use data. Scientists frequently use the results of statistical analyses, including correlative statistics, as evidence. Evidence does not imply proof of causality or any other underlying explanation, and that is where your original post seemed to get things mixed up. Evidence for a particular hypothesis simply means that the patterns observed in some data are consistent with the hypothesis.

I think you are confusing "evidence" with "proof". Data, and more specifically, the patterns in data, most certainly are evidence. If that were not true, then there would be no reason to even try doing science.

Any scientist who has spent years obtaining a hard-won dataset would strongly disagree with you. Consider, for example, the ground-breaking data generated a few years ago by the Human Genome Project, or the current explosion of data about exoplanets. These data most certainly do represent substantial intellectual and technical accomplishments. Now, if what you mean is that simply downloading someone else's data from the Web is not an accomplishment, then I agree with you.

I think you will find that, in the hard sciences at least, that's usually how it's done. The researchers who write the papers are usually the same people who were involved in collecting the data. However, for very large-scale studies (e.g., global biodiversity research), there is no way that a single scientist, or even a single research team, could gather all of the necessary data. In these cases, the only way to make the research tractable is to integrate multiple datasets.

Your points about the importance of understanding where the data one uses in a study came from, how they were collected, and any potential biases are all well taken. However, ignoring any of these factors is simply sloppy science, no matter whether the researcher collected the data him or herself, or if someone else collected it.

Nope. Watterson never allowed his characters to be licensed for any merchandise beyond his books and a few calenders. Those stickers you see on trucks are all unlicensed ripoffs: http://en.wikipedia.org/wiki/C....

Watterson could have made a lot more money than that, doing a lot less. All he'd have needed to do was agree to commercial licensing deals for his Calvin and Hobbes characters, but he always refused because he felt doing so would cheapen his creations. Even now, such deals would probably still be lucrative. And he could no doubt make plenty of money off of speaking engagements. For some people (who, I admit, are very rare), accumulating large amounts of money really is less important than their pride in their work or their privacy.

That's a good point, for sure. I can certainly understand why Calvin and Hobbes fans might wish that he were more accessible.

I wish I had mod points to give you. From what I've read, Watterson simply values his privacy and his family's privacy, and he has virtually no interest in publicity for its own sake. Apparently, any former celebrity who doesn't so desperately long for attention that they appear on Dancing With the Stars or jump at every chance for an interview or public appearance is so incomprehensible to most people that the only way to make sense of it is to label them a "recluse".

And that explains your comments quite nicely.

I don't think there is anyone here who would seriously disagree with you that the best possible scenario for the end user is dedicated UI design that is customized, when appropriate, for each target OS. But in the real world, those of us who must develop and maintain cross-OS applications with limited resources and small teams often don't have the luxury of building custom UIs for each target platform. Off-the-shelf cross-platform UI toolkits, such as Qt, are the only realistic way to support multiples OSs in these cases. It's either that, or only develop for one platform, which will usually have to be windows due to the size of the customer base. That is a far worse option, in my opinion.

So no, the "unified GUI look" that toolkits like Qt strive for across platforms is not ideal. Any serious programmer already knows that. But often times, it's the only practical way to support more than one OS, and for that reason, such toolkits are indispensable. Furthermore, those of us who don't use windows or OSX appreciate the benefits of these toolkits even more (GNU/Linux, in my case), because it means that we have far more software options than we might otherwise.

And you've missed my point. Perhaps I didn't explain myself well.

I absolutely do not disagree that plenty of people have an irrational fear of genetic technologies. Nor do I disagree that we have lots of other ways to screw the world up (you mention the example of massive automated surveillance). And I wasn't arguing that we shouldn't try to resurrect a mammoth.

The GP seemed to me to be making the argument that 1) negative reaction to "messing with life" is because of antiquated religious sensibilities; and 2) we're gods now, so we should just do whatever the heck we want. I don't find either part of that argument compelling. As for part 1, casting any and all opposition to unbridled genetic experimentation as nothing but religious or cultural fanatacism is a straw man argument, pure and simple. There are lots of very rational reasons to proceed cautiously with certain kinds of genetic experimentation (and plenty of scientists agree with me). Why part 2 is wrong shouldn't require any further explanation, and other commenters have already addressed it.

Although you seem to think that the debate about genetic experimentation is nothing more than a conflict between science religion, I assure you that is not the case.

"Messing with life", as you call it, has an incredible potential for doing harm if approached carelessly. It doesn't take much imagination to realize this, either: synthetic infectious agents, engineered organisms that displace natural diversity, and so on.

You state, "Humans are the new god on planet earth (and beyond?)." If you really believe that, than surely you must agree that responsibility and caution need to be part of that job description. Science does not, and never should, exist outside of ethical debate.

That is nonsense. For basic statistical tests (e.g., t-tests), statistical significance depends on the sampling distribution of the statistic, which is a function of both sample size and the source population distribution. For example, a difference in means that is less than the standard deviations of the source populations can easily be statistically significant if the sample sizes are large enough. If you don't believe me, I suggest you try running some simple numeric simulations for normally-distributed populations (e.g., in R).

Precisely. If I had mod points, they'd be yours.

Exactly what I was thinking.

There is a general feeling in the U.S. that public schools are failing (regardless of whether that opinion is justified). It seems to me that buying more technology is the lazy administrator's way of "doing something about it." Purchasing technology also provides a convenient measure of progress, however dubious. Administrators can brag about how they are providing every student with an iPad, or putting smart boards in every classroom, or whatever the current fad is, and claim that they are improving the school.

Are these purchases usually made with a clear plan for how to use the technology, or solid research-based evidence that the new technology will actually improve students' learning? I would guess that most of the time, the answer is "no" on both counts. The fact that we're now having Bill Nye ask K-12 students, "So, you've got all of this cool technology in your school... how is it actually useful?" suggests I might not be wrong.