Does anyone have a review of Biostats Basics by Gould and Gould. I am thinking of adopting it for an intro stats for biology and medicine. I like their hands-on approach, but would appreciate feedback from people who have used it in the class room.
Thanks, Johanna Kraus On 10/23/06, Jeff Hollister <[EMAIL PROTECTED]> wrote: > > I was going to avoid jumping into the fray, but . . . > > Count me in the camp that appreciates Zar as an introductory text. I have > not > taught a stats class, but Zar is the text assigned for a stats class I had > many > years back. I remember it being good at introducing the concepts and I > continue to use it as a reference today. > > Another book that i like that hasn't been mentioned yet is "The Ecological > Detective" by Hilborn and Mangel. While not a good introductory text, it > might > be good as a supplemental book for discussion of use of statistics in > ecological research. > > And since Stephen mentioned R... I have learned most of what I know about > R > from Dalgaard's Intro text in concert with the more complete "Modern > Applied > Statistcs with S" by Venables and Ripley. > > Cheers, > Jeff Hollister > > p.s. I too have enjoyed reading this thread. I don't know when this > fascination with stats texts developed, but a quick perusal of my > bookshelf and > I count 12 stats related books. I will admit to being a bit disturbed by > that. > > > Quoting "Stephen B. Cox" <[EMAIL PROTECTED]>: > > > Hello Howie - (I am one of the few poor souls who actually enjoys > reading > > "long rambles" about imparting good statistical know-how to future > > scientists :) > > > > I can definitely see your point about the difficulties associated with > > implementing the Q&K text in introductory courses. As much as I do like > it, > > I have yet to adopt it in my courses. However, I do like the fact that > > they avoid a 'cookbook' approach, and present quantitative methods > within > > the broader context of conducting science (and thinking about what your > are > > doing!). This is also a strength of Gotelli and Ellison's book, which I > > also like very much. In fact - although I only require one textbook - I > try > > to emphasize to my students the value of starting their own library, and > > encourage them to at least take a look at all of the texts which have > > previously been mentioned. For anyone wanting to pursue a career in > science > > - good resources (and especially stats resources :) are a worthy > > investment! I will check out the H&H book you mentioned. > > > > And I wholeheartedly agree with your aversion to teaching "point and > click" > > approaches to statistical computing!! In addition to reducing error, > > forcing the use of explicit code creates a reproducable and > well-documented > > history of past analysis (and data management). I have incorporated R > into > > my introductory course, and have had very good success. Once students > get > > over the initial learning curve, they quickly learn to appreciate the > power > > and flexibility of knowing a statistical programming > tool. "Introductory > > Statistics with R" by Peter Dalgaard is a great supplementary text for > this > > purpose. > > > > Cheers > > > > Stephen > > > > > > On 10/20/06, Howie Neufeld <[EMAIL PROTECTED]> wrote: > > > > > > Dear All - the thread about which statistical text to use is > interesting > > > to read, and reflects, I think, the depth and breadth of statistical > > > sophistication among us ecologists. Those of us with a smattering to > > > moderate amount would probably prefer a more introductory book for our > > > incoming graduate students, while those with a lot of training in > > > statistics would prefer a higher powered book. > > > For years I used Zar - it does have depth and breadth, and plenty > of > > > examples worked out. It's a great reference book too. Others seem to > > > prefer Quinn and Keough. And I'm sure there are yet others who have > > > their own favorite texts. Based on my sampling, I think the only true > > > conclusion is that medical statisticians write the absolutely worst > > > texts and ecologists the best ones! > > > However, this year I switched texts to one by Hampton and Havel > > > (H&H) because I realized that in my intro biometrics course (that's > what > > > we call it here historically) I never got to at least half of the > > > chapters in Zar, not to mention that the Zar book is expensive. Much > > > the same material I covered in past years is included in the H&H book. > > > But because its paperback, it has a greatly reduced price > (~$25). It's > > > also geared for those students with essentially no a priori background > > > in statistics, and my students like it so far. > > > I found the Quinn and Keough book way too advanced for the > > > introductory student. From a pedagogical point of view, I thought it > > > was poorly developed. It had its moments, but as a teaching tool for > > > students just starting out, it would have been way to much for my > > > students. It too contains much more material than I could ever cover > in > > > my intro course. > > > Not wanting my students to have too much disposable income, I > > > supplement the H&H text with Gotelli and Ellison's new Primer on > > > Ecological Statistics, because I like their philosophy and approach to > > > statistics. However, they provide no work study problems, but again, > > > and as Aaron Ellison has told me, that was not their goal. But their > > > discussions of why we do statistics, the history involved, and their > > > section on experimental design are all highly readable, so I assign > this > > > as an auxiliary text for them. I especially like their discussion of > > > what Bayesian statistics are, and how they can be used. That is not > > > something most of even mention in intro courses. > > > Finally, we conduct a SAS lab each week. Yes, I'm one of the > dodos > > > of the statistical world that still finds SAS programming useful, and > so > > > I inflict this on my students (If I had to do it.....! - no that's not > > > the reason!). For this we use Cody and Smith's "Applied Statistics > and > > > the SAS Programming Language". I'm sure there are those who find this > > > type of training anachronistic, but simply using point and click > > > programs often leads to errors in experimental design and then > analysis, > > > which are less likely if you are writing the programming yourself. By > > > the end of their first semester, they can move on to point and click > > > programs, so they end up with several skills here. > > > The main problem we have at Appalachian State is a follow-up > > > experimental design course for our graduate students. I would be > most > > > happy if someone who is teaching a second semester course in this area > > > would send me their syllabus. We want to set up such a course here, > and > > > I would appreciate feedback as to what we should include in such > > > a course. > > > Thanks for listening to this long ramble. > > > Howie Neufeld > > > > > > -- > > > Dr. Howard S. Neufeld, Professor > > > Department of Biology > > > 572 Rivers Street > > > Appalachian State University > > > Boone, NC 28608 > > > > > > email: [EMAIL PROTECTED] > > > departmental webpage: > > > http://www.biology.appstate.edu/faculty/neufeldhs.htm > > > personal webpage: http://www.appstate.edu/~neufeldhs/index.html > > > > > > Tel: 828-262-2683 > > > Fax: 828-262-2127 > > > > > >
