Also remember, placebos aren't just for patients, they are for clinicians, too. Placebos play a central role in the pivotal concept in modern day trials, randomization. I'm sure you realize there needs to be *some* sort of control group. In double-blind trials, the doctors won't know what the patient has been given, placebo or treatment, so biases are reduced compared to if they did know (who gets into the trial, for instance?). There are many biases, including subconscious ones, that can come out when the observer (doctor) knows the assigned treatment.
Three books? Wait a minute. Hold it. Nobody said anything about three books. Like... like what am I supposed to do? Take-Take one book... or all books... or... or what? Three books? Nobody said anything about three books...
I have to say that after college, medical school, graduate school, and over 12 years of virology and immunology research, I've read a lot of stuff (including popular science that was meant to be educational) that was ridiculous. But the above post ranks in my top 5 examples of manic garbage. It's a collection of bits and pieces of something you've overheard, put together somewhat like a neanderthal would try to piece together the space shuttle. It may contain a couple of the correct parts, but the result does not only fail to take off, but is not identifiable as the correct object, no matter from what angle you look at it.
You just simply can't compare raw event numbers when estimating relative risk. Your statement about "twice as deadly" is very likely not true, and certainly not justified from the data you reference. You fail to take into account any sort of denominator when just using the raw events. What if only 27 kids rode school busses each year? What if 2 million did? What if only 43 kids were exposed to H1N1, and they all died? What if everyone was exposed to H1N1, and 43 died? You need to take into account the population, not just events. After all, every(?) child who died last year used toothpaste.
There has never been a *randomized* control clinical trial showing smoking causes cancer in humans. If you believe smoking causes cancer in humans, then you are somehow making an exception of your own rule. So, do you?
Your points are valid for managing data with SAS. But that's not what a lot of statistics is about of course. Try coding a cubic spline regression algorithm in SAS vs. R and see which you like better. I know that doesn't take away your point about large data. But what happens is that SAS is still taught in many graduate stats departments to manage small (dozens or hundreds of cases) datasets and run regressions on them. This is where using SAS seems pointless to me. Even clinical trial data only number in the thousands for both subjects and variables. This is not "large scale", and free R is perfectly capable on data like these.
I will beg to differ on your "not so bad" conclusion on the SAS language design. R's object-oriented functional model is far superior for designing statistical functions, packages, and systems, including graphical functions. I don't think anyone will deny that. R's evaluation model is based in Scheme semantics, and I think if you're coming to stats from a CompSci background, as many are these days, you're not going to like anything SAS has to offer.
While I agree with your points, the fact is that SAS has such a stranglehold on some industries, specifically the pharma industry, that they haven't had to improve their product much in recent years. I mean, I think in the last few years, the one major feature that their survival models package (proc phreg) got was the ability to include categorical variables with more than 2 categories (i.e., a class statement).
R, which is a GNU project, has taken over completely when it comes to new statistical methods being implemented, and has also taken over everything in graphical research and methods. I think it is only a matter of time before it is the standard, but it will take awhile since there is a lot of money invested in legacy SAS macros and programmers. But they certainly aren't teaching too much SAS at universities these days, it won't be long before students come out knowing a lot more R. R is definitely the future of statistical computing, and SAS is the past. They have recently been trying to concentrate on being a business platform, like an SAP competitor, more than statistical software. I suppose that's a smart move on their part, we'll see how it plays out.
Completely agree with the comments about ugly syntax though, ugh, I would not wish it on anyone.
That's begging the question. By definition, whatever humans do as a species is ipso facto *normal*. What is considered normal will change over time though.
Da Da-Da-Da Da Da Da, Da Da, Da Da, Da Da Da, Dah-Dah-Dah, Duh,Duh,Duh, Da-Da-Da, Dah Dah, Dum Doo, Dee Dee, Dah Do De Doo. Dahhh Dahh, Dahhhh Dahhh, Dahhh Dahhh, Dahhhhhh Dahhh Dahh, Dooooo Dahhhh, Dum Do Deeee Dahhhhhhh, Repeat!
Are you really that short-sighted? The point is that finding 20 people to play football with in mid-January on a moment's notice is not very easy. Growing up, I used to play pickup games all the time with friends. As we age, I almost never get to do that. All my current sporting activity is organized. This gives me a way to play something exactly when I want, without the extra hours of setting it up and traveling. Oh, and the games are usually a bit more whimsical than the real thing. It's a lot more fun playing Wii tennis with someone who has never played tennis before than it is playing real tennis with them (and doubly so in January in the Midwest).
This means that more programmers are using Python and Ruby on the weekend for their personal projects, showing that these languages are more fun to use.
You forgot the word "could". None of your conclusions follow from this analysis.
I have a book called How to Solve It: Modern Heuristics. (This is not the classic problem-solving book "How to Solve It"). The book is about machine learning, statistics, genetic algorithms, and describes how coming up with approximate solutions to the right problem is often times much easier and faster than the exact solution.
At any rate, the book starts off with a study done where random questions from a 5th grade math text book that were given a group of people, but not in the context of the chapter, just by themselves. The book gives the problems and then says "If you can solve these in less than an hour(!), you will belong to the elite one percent of the people we tested who managed to get the right answer in that time. What's more, everyone we tested had at least an undergraduate degree in mathematics, engineering, or computer science." The point? When questions are given out of context, e.g., not at the end of a chapter about the quadratic equation, they can be hard to solve, even for qualified people. You have to THINK!
Also, wasn't there a study that found 20% of Americans think Joan of Arc was Noah's wife? And what percent of USians can't find the Pacific Ocean on a map? 21!
Slashdot Mirror
what might be seen as romantic vs. what might be seen as lame or generic, ... , "Ask Slashdot" isn't really a good place for an answer.
You think?!
It's funny enough that as of my posting, the menu immediately to the right of your linked picture contains an image of Jobs holding an iPad.
Also remember, placebos aren't just for patients, they are for clinicians, too. Placebos play a central role in the pivotal concept in modern day trials, randomization. I'm sure you realize there needs to be *some* sort of control group. In double-blind trials, the doctors won't know what the patient has been given, placebo or treatment, so biases are reduced compared to if they did know (who gets into the trial, for instance?). There are many biases, including subconscious ones, that can come out when the observer (doctor) knows the assigned treatment.
I second org-mode. Basic emacs is worth learning just so you can use it, honestly.
That's not my bag baby, honest!
Humans... so easy, a caveman can do them.
Three books? Wait a minute. Hold it. Nobody said anything about three books. Like... like what am I supposed to do? Take-Take one book... or all books... or... or what? Three books? Nobody said anything about three books...
14 days of bed rest untreated or two weeks of bedrest treated
That's an incredible treatment effect, I will need to see some evidence!
I have to say that after college, medical school, graduate school, and over 12 years of virology and immunology research, I've read a lot of stuff (including popular science that was meant to be educational) that was ridiculous. But the above post ranks in my top 5 examples of manic garbage. It's a collection of bits and pieces of something you've overheard, put together somewhat like a neanderthal would try to piece together the space shuttle. It may contain a couple of the correct parts, but the result does not only fail to take off, but is not identifiable as the correct object, no matter from what angle you look at it.
Welcome to Slashdot!
You just simply can't compare raw event numbers when estimating relative risk. Your statement about "twice as deadly" is very likely not true, and certainly not justified from the data you reference. You fail to take into account any sort of denominator when just using the raw events. What if only 27 kids rode school busses each year? What if 2 million did? What if only 43 kids were exposed to H1N1, and they all died? What if everyone was exposed to H1N1, and 43 died? You need to take into account the population, not just events. After all, every(?) child who died last year used toothpaste.
..., and vice-versa.
Dude, go back school.
I think I am going to have a t-shirt made of that...
There has never been a *randomized* control clinical trial showing smoking causes cancer in humans. If you believe smoking causes cancer in humans, then you are somehow making an exception of your own rule. So, do you?
Your points are valid for managing data with SAS. But that's not what a lot of statistics is about of course. Try coding a cubic spline regression algorithm in SAS vs. R and see which you like better. I know that doesn't take away your point about large data. But what happens is that SAS is still taught in many graduate stats departments to manage small (dozens or hundreds of cases) datasets and run regressions on them. This is where using SAS seems pointless to me. Even clinical trial data only number in the thousands for both subjects and variables. This is not "large scale", and free R is perfectly capable on data like these.
I will beg to differ on your "not so bad" conclusion on the SAS language design. R's object-oriented functional model is far superior for designing statistical functions, packages, and systems, including graphical functions. I don't think anyone will deny that. R's evaluation model is based in Scheme semantics, and I think if you're coming to stats from a CompSci background, as many are these days, you're not going to like anything SAS has to offer.
While I agree with your points, the fact is that SAS has such a stranglehold on some industries, specifically the pharma industry, that they haven't had to improve their product much in recent years. I mean, I think in the last few years, the one major feature that their survival models package (proc phreg) got was the ability to include categorical variables with more than 2 categories (i.e., a class statement).
R, which is a GNU project, has taken over completely when it comes to new statistical methods being implemented, and has also taken over everything in graphical research and methods. I think it is only a matter of time before it is the standard, but it will take awhile since there is a lot of money invested in legacy SAS macros and programmers. But they certainly aren't teaching too much SAS at universities these days, it won't be long before students come out knowing a lot more R. R is definitely the future of statistical computing, and SAS is the past. They have recently been trying to concentrate on being a business platform, like an SAP competitor, more than statistical software. I suppose that's a smart move on their part, we'll see how it plays out.
Completely agree with the comments about ugly syntax though, ugh, I would not wish it on anyone.
That's begging the question. By definition, whatever humans do as a species is ipso facto *normal*. What is considered normal will change over time though.
Da Da-Da-Da Da Da Da, Da Da, Da Da, Da Da Da, Dah-Dah-Dah,
Duh,Duh,Duh, Da-Da-Da, Dah Dah, Dum Doo, Dee Dee, Dah Do De Doo.
Dahhh Dahh, Dahhhh Dahhh, Dahhh Dahhh, Dahhhhhh
Dahhh Dahh, Dooooo Dahhhh, Dum Do Deeee Dahhhhhhh,
Repeat!
That was a "joke" I think. TFA does not mention naps...very lame attempt at being witty.
Expensive for whom, you? What about a large political party or the intelligence unit of a foreign country? Practically free for them.
This reminds me of where I went to high school. They sent you through a metal detector, and if you didn't have a gun, they gave you one.
Are you really that short-sighted? The point is that finding 20 people to play football with in mid-January on a moment's notice is not very easy. Growing up, I used to play pickup games all the time with friends. As we age, I almost never get to do that. All my current sporting activity is organized. This gives me a way to play something exactly when I want, without the extra hours of setting it up and traveling. Oh, and the games are usually a bit more whimsical than the real thing. It's a lot more fun playing Wii tennis with someone who has never played tennis before than it is playing real tennis with them (and doubly so in January in the Midwest).
Here is a link to the actual publication.
http://www3.interscience.wiley.com/cgi-bin/fulltext/122539667/HTMLSTART
It always bothers me that these aren't provided, we can read the the actual results and not the news version!
On my Samsung NC10, Windows gives me about 6.5 to 7 hours of battery life, Ubuntu about 4.5 to 5.
This means that more programmers are using Python and Ruby on the weekend for their personal projects, showing that these languages are more fun to use.
You forgot the word "could". None of your conclusions follow from this analysis.
I have a book called How to Solve It: Modern Heuristics. (This is not the classic problem-solving book "How to Solve It"). The book is about machine learning, statistics, genetic algorithms, and describes how coming up with approximate solutions to the right problem is often times much easier and faster than the exact solution.
At any rate, the book starts off with a study done where random questions from a 5th grade math text book that were given a group of people, but not in the context of the chapter, just by themselves. The book gives the problems and then says "If you can solve these in less than an hour(!), you will belong to the elite one percent of the people we tested who managed to get the right answer in that time. What's more, everyone we tested had at least an undergraduate degree in mathematics, engineering, or computer science." The point? When questions are given out of context, e.g., not at the end of a chapter about the quadratic equation, they can be hard to solve, even for qualified people. You have to THINK!
Also, wasn't there a study that found 20% of Americans think Joan of Arc was Noah's wife? And what percent of USians can't find the Pacific Ocean on a map? 21!
http://machinist.salon.com/blog/2007/08/30/upton/