I hope this question is sufficiently different from the other requests for book recommendations that it's not repetitious. If not, I apologize in advance. I'm curious what standard reference books working statisticians, or biostatisticians, have within easy reach of their desk. I'm a computer systems administrator, and have a two-foot bookshelf directory under my monitor that contains 13 paperback manuals that I refer to frequently, some once or twice a day. Are there standard reference works for statisticians that are used the same way? From reading this list, I'm guessing that one might be W. N. Venables and B. D. Ripley (2002), "Modern Applied Statistics with S. Fourth Edition", Springer, ISBN 0-387-95457-0. However, I'm not limiting this to books pertaining to R. On the other hand, maybe Google and other on-line sources, as well as interactive programs like R that can spit out numbers previously looked up in tables, have completely replaced the need for reference books. Is this the case today? I'm particularly interested in reference books that may be helpful in my organization's work. We typically deal with datasets from international Demographic and Health Surveys (DHS) similar to those available at http://www.measuredhs.com/aboutsurveys/search/search_survey_main.cfm?Srv yTp=type&listtypes=1. These typically contain 10,000+ respondents and can have up to 800 fields. We currently analyze these datasets using Stata. Thanks for taking the time to think about and respond to this question. I'll summarize the answers in a later post for the archive. -Kevin Kevin Zembower Internet Services Group manager Center for Communication Programs Bloomberg School of Public Health Johns Hopkins University 111 Market Place, Suite 310 Baltimore, Maryland 21202 410-659-6139
Oh, Boy. This might result in a data dump since each of us has a personal
library. Here are the top dozen or so from mine:
1. Agresti, Alan, Categorical Data Analysis, 2nd ed., Wiley, 2002
2. Box, George E. P., William G. Hunter, and J. Stewart Hunter,
Statistics for Experimenters, Wiley, 1978
3. Casella, George and Roger L. Berger, Statistical Inference, Duxbury
Press, 2001
4. Chatfield, C., The Analysis of Time Series, 4th ed., Chapman & Hall,
1989
5. Cressie, Noel A. C., Statistics for Spatial Data, Wiley, 1993
6. Fisher, Ronald A., Statistical Methods for Research Workers. (First
published in 1925; 14th edition was ready for publication in 1962, when
Fisher died, and was published in 1990, by the Oxford University Press,
along with Experimental Design and Scientific Inference, with corrections to
the 1991 edition, in 1993.)
7. Efron, Bradley and Robert J. Tibshirani, An Introduction to the
Bootstrap, Chapman and Hall, 1993
8. Gelman, Andrew, John B. Carlin, Hal S. Stern, Donald B. Rubin,
Bayesian Data Analysis, 2nd ed., Chapman & Hall/CRC, 2003
9. Johnson, Richard A. and Dean W. Wichern, Applied Multivariate
Statistical Analysis, 5th ed., Prentice Hall, 20021988
10. Kutner, Michael, and Christopher J. Nachtsheim, John Neter, William
Li, Applied Linear Statistical Models, 5th ed., McGraw-Hill/Irwin, 2005
11. Lawless, Jerald F., Statistical Models and Methods for Lifetime Data,
Wiley, 1982
12. McCullagh, P. and J.A. Nelder, Generalized Linear Models, Chapman &
Hall, 2nd ed., 1989
13. Meeker and Escobar, Statistical Methods for Reliability Data, Wiley,
1998
14. Robert, Christian P. and George Casella, Monte Carlo Statistical
Methods, Springer, 1999
15. Venables and Ripley, Modern Applied Statistics with S, 4th ed.,
Springer, 2002
Charles Annis, P.E.
Charles.Annis at StatisticalEngineering.com
phone: 561-352-9699
eFax: 614-455-3265
http://www.StatisticalEngineering.com
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Zembower, Kevin
Sent: Thursday, March 01, 2007 10:07 AM
To: r-help at stat.math.ethz.ch
Subject: [R] Another newbie book recommandation question
I hope this question is sufficiently different from the other requests
for book recommendations that it's not repetitious. If not, I apologize
in advance.
I'm curious what standard reference books working statisticians, or
biostatisticians, have within easy reach of their desk. I'm a computer
systems administrator, and have a two-foot bookshelf directory under my
monitor that contains 13 paperback manuals that I refer to frequently,
some once or twice a day. Are there standard reference works for
statisticians that are used the same way? From reading this list, I'm
guessing that one might be W. N. Venables and B. D. Ripley (2002),
"Modern Applied Statistics with S. Fourth Edition", Springer, ISBN
0-387-95457-0. However, I'm not limiting this to books pertaining to R.
On the other hand, maybe Google and other on-line sources, as well as
interactive programs like R that can spit out numbers previously looked
up in tables, have completely replaced the need for reference books. Is
this the case today?
I'm particularly interested in reference books that may be helpful in my
organization's work. We typically deal with datasets from international
Demographic and Health Surveys (DHS) similar to those available at
http://www.measuredhs.com/aboutsurveys/search/search_survey_main.cfm?Srv
yTp=type&listtypes=1. These typically contain 10,000+ respondents and
can have up to 800 fields. We currently analyze these datasets using
Stata.
Thanks for taking the time to think about and respond to this question.
I'll summarize the answers in a later post for the archive.
-Kevin
Kevin Zembower
Internet Services Group manager
Center for Communication Programs
Bloomberg School of Public Health
Johns Hopkins University
111 Market Place, Suite 310
Baltimore, Maryland 21202
410-659-6139
______________________________________________
R-help at stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
for the size of your data file, I think R can handle it. of course, it also depends on your hardware. however, it might not be a good idea to do heavy data manipulation work in R. stata has very good routine for survey analysis. i am not sure if R is as good as stata in terms of survey analysis. S programming by the same authors as MASS might be a good reference good you would like it on your shelf. On 3/1/07, Zembower, Kevin <kzembowe at jhuccp.org> wrote:> I hope this question is sufficiently different from the other requests > for book recommendations that it's not repetitious. If not, I apologize > in advance. > > I'm curious what standard reference books working statisticians, or > biostatisticians, have within easy reach of their desk. I'm a computer > systems administrator, and have a two-foot bookshelf directory under my > monitor that contains 13 paperback manuals that I refer to frequently, > some once or twice a day. Are there standard reference works for > statisticians that are used the same way? From reading this list, I'm > guessing that one might be W. N. Venables and B. D. Ripley (2002), > "Modern Applied Statistics with S. Fourth Edition", Springer, ISBN > 0-387-95457-0. However, I'm not limiting this to books pertaining to R. > > On the other hand, maybe Google and other on-line sources, as well as > interactive programs like R that can spit out numbers previously looked > up in tables, have completely replaced the need for reference books. Is > this the case today? > > I'm particularly interested in reference books that may be helpful in my > organization's work. We typically deal with datasets from international > Demographic and Health Surveys (DHS) similar to those available at > http://www.measuredhs.com/aboutsurveys/search/search_survey_main.cfm?Srv > yTp=type&listtypes=1. These typically contain 10,000+ respondents and > can have up to 800 fields. We currently analyze these datasets using > Stata. > > Thanks for taking the time to think about and respond to this question. > I'll summarize the answers in a later post for the archive. > > -Kevin > > Kevin Zembower > Internet Services Group manager > Center for Communication Programs > Bloomberg School of Public Health > Johns Hopkins University > 111 Market Place, Suite 310 > Baltimore, Maryland 21202 > 410-659-6139 > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- WenSui Liu A lousy statistician who happens to know a little programming (http://spaces.msn.com/statcompute/blog)