that's pretty interesting. And no, it's not on Google books, but I read the NY Times review.
http://www.nytimes.com/2012/02/12/books/review/charles-murray-examines-the-white-working-class-in-coming-apart.html?pagewanted=1&_r=1 On Wed, Feb 15, 2012 at 7:15 PM, Dana <[email protected]> wrote: > Maybe? I'd have to look at it to know whether I could. Is this something > that's on google books? NM I'll look myself. > > > On Wed, Feb 15, 2012 at 7:11 PM, Larry C. Lyons <[email protected]>wrote: > >> >> Forgot to mention the really difficult part is correctly figuring out the >> range of those results. A good well controlled study will have a very >> narrow range. A study that has problems with reliability, sample size, >> etc, >> will have a very wide range. Another way to look at it is if the range of >> differences encompasses 0 by any substantial amount, most likely it means >> that the differences are not meaningful. >> >> Speaking of such, I'm prepping a statistical criticism of the latest book >> byCharles Murray, author of the Bell Curve. Want to join in? >> >> >> On Wednesday, February 15, 2012, Larry C. Lyons <[email protected]> >> wrote: >> > You are not the only one. On my desk at home is a notebook with all my >> notes for the next version of my meta-analysis application. 150 pages and >> counting - most of which are botched formulae for calculating statistical >> power effect sizes and converting obtained probability values to effect >> sizes. Makes me wish at times I stayed with single case designs. >> > >> > 10 word or less that is really difficult. Can I go for 30? >> > >> > But you've essentially got the idea. I left out a lot, range estimation >> and correction for error andthat sort of thing, but yes. >> > >> > On Wednesday, February 15, 2012, Dana <[email protected]> wrote: >> >> >> >> what not really -- the meaning of standard deviations? If so yeah you >> are >> >> right, I think but what Maureen and I said is an .... ok 10 words or >> less >> >> version. >> >> >> >> In this case p=0.011 so theoretically if they did everything else >> right, >> >> these results should replicate 99% of the time. And not, 1%. >> >> >> >> I realize that's it's not a given that the 1% is random or that it >> won't >> >> occur the next time you repeat the experiment, but I think that is a >> rather >> >> fine distinction for our purposes. Kinda like the difference between >> >> Springfield and Tyson's Corner, as seen from California, yanno? If I >> don't >> >> have that right then fine, tell me, but if you're going to crank up >> your >> >> statistical powers I'd rather hear an explanation of that leave one out >> >> thing they did a thousand times, because that part I do not understand >> at >> >> ALL. >> >> >> >> On Wed, Feb 15, 2012 at 6:21 PM, Larry C. Lyons <[email protected] >> >wrote: >> >> >> >>> >> >>> Not really. It depends on the stats that are used. When looking at >> >>> statistical results, the way to interpret statistical significance is >> as >> >>> follows. Let's say the researchers found the two groups showed a >> >>> significant difference of p < 0.05 . This means that if you >> replicated >> >>> the study an infinite number of times, 95% of these results would fall >> very >> >>> close to the difference found in the first study. How meaningful that >> >>> spread is depends on the standard error of the studies, and other >> factors. >> >>> It also mean that in order to show a significant difference with a >> smaller >> >>> sample you'd need a much larger difference to achieve statistical >> >>> significance. >> >>> >> >>> So you can make very accurate predictions based on fairly small >> samples. It >> >>> all depends on the statistical power of your experiment. I'm too >> burned >> out >> >>> to really discuss it now, but if interested Wikipedia has a pretty >> good >> >>> explanation of it - http://en.wikipedia.org/wiki/Statistical_power >> >>> >> >>> On Wednesday, February 15, 2012, LRS Scout <[email protected]> >> wrote: >> >>> > >> >>> > The sampling of 90 people is really really small. >> >>> > >> >>> > On Wed, Feb 15, 2012 at 7:29 PM, Dana <[email protected]> >> wrote: >> >>> > >> >>> >> >> >>> >> feel free to run away, Sam, but you still haven't showed me any >> basis at >> >>> >> all for the crap you've been talking. >> >>> >> >> >>> >> On Wed, Feb 15, 2012 at 4:18 PM, Sam <[email protected]> wrote: >> >>> >> >> >>> >> > >> >>> >> > I give up and feel the fool for not heeding this advice sooner: >> >>> >> > >> >>> >> > Dont argue with idiots. They drag you down to their level and >> beat >> >>> >> > you with experience >> >>> >> > >> >>> >> > . >> >>> >> > >> >>> >> > On Wed, Feb 15, 2012 at 7:07 PM, Dana <[email protected]> >> wrote: >> >>> >> > > >> >>> >> > >> >> >>> >> > >> Yes it is. It's the same study done three times. Two people, >> 90 >> >>> people >> >>> >> > >> and 28 people. >> >>> >> > >> >> >>> >> > > >> >>> >> > > Ah, here's the heart of the problem. No, Sam, it isn't. It's -- >> I'd >> >>> >> call >> >>> >> > it >> >>> >> > > two studies and an experiment I guess -- that tested the same >> >>> >> hypothesis. >> >>> >> > > According to your nomenclature here, all trials for the same >> drug >> >>> are a >> >>> >> > > single study. And mutually responsible for one another's >> >>> methodology. >> >>> >> > And, >> >>> >> > > according to you, everything anyone remotely affiliated with >> them >> >>> may >> >>> >> > have >> >>> >>> >> > > >> with >> >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~| Order the Adobe Coldfusion Anthology now! http://www.amazon.com/Adobe-Coldfusion-Anthology/dp/1430272155/?tag=houseoffusion Archive: http://www.houseoffusion.com/groups/cf-community/message.cfm/messageid:346969 Subscription: http://www.houseoffusion.com/groups/cf-community/subscribe.cfm Unsubscribe: http://www.houseoffusion.com/groups/cf-community/unsubscribe.cfm
