I am often asked to recommend a "good
statistics text," which is as difficult as recommending a good engineering
text, and for the same reason.
Both disciplines are rich, broad and complex.
Perhaps parts of them might be summarized in a single volume, but individual
topics require dedicated study. Here are a
few books that I refer to often.
- Agresti, Alan, Categorical Data Analysis, 2nd ed., Wiley,
- Box, George E. P., William G. Hunter, and J.
Stewart Hunter, Statistics for Experimenters, Wiley, 1978
- Casella, George and Roger L. Berger,
Statistical Inference, Duxbury Press, 2001
- Chatfield, C., The Analysis of Time Series, 4th ed., Chapman
& Hall, 1989
- Cressie, Noel A. C., Statistics for Spatial Data, Wiley, 1993
- Fisher, Ronald A., Statistical Methods for
(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.)
- Efron, Bradley and Robert J. Tibshirani, An Introduction to the
Bootstrap, Chapman and Hall, 1993
- Gelman, Andrew, John B. Carlin, Hal S. Stern, Donald B. Rubin,
Bayesian Data Analysis, 2nd ed., Chapman & Hall/CRC, 2003
- Johnson, Richard A. and Dean W. Wichern, Applied Multivariate
Statistical Analysis, 5th ed., Prentice Hall, 2002
- Kutner, Michael, and Christopher J.
Nachtsheim, John Neter, William Li, Applied Linear Statistical Models, 5th ed., McGraw-Hill/Irwin, 2005
- Lawless, Jerald F., Statistical Models and
Methods for Lifetime Data, Wiley, 1982
- McCullagh, P. and J.A. Nelder, Generalized Linear Models,
Chapman & Hall, 2nd ed., 1989
- Meeker and Escobar, Statistical Methods for
Reliability Data, Wiley, 1998
- Robert, Christian P. and George Casella, Monte Carlo Statistical
Methods, Springer, 1999
- Venables and Ripley, Modern Applied Statistics with S, 4th
ed., Springer, 2002