Ten books on probability and statistics every statistician might want to own
FROM INTERNET SOURCES, IN ALPHABETICAL ORDER, WITH NO CLAIMS OF A COMPLETE LIST
Applied Econometric Time Series, W. Enders, 1995, New York, John Wiley & Sons.
Elements of Statistical Learning, T. Hastie, R. Tibshirami, and J Friedman, 2001, New York, Springer.
Categorical Data Analysis, (2nd ed.), Agresti, A. New York: John Wiley & Sons, 2002.
Methods of Multivariate Analysis, A. Rencher, 2002, New York: John Wiley & Sons.
Modern Regression Methods, Ryan, T.P. 1997. New York: Wiley.
Subjective and Objective Bayesian Statistics: Principles, Models,and Applications, (2nd ed.), Press, S. J. New York: John Wiley & Sons, 2003.
Testing Statistical Hypotheses of Equivalence, Wellek, S. Boca Raton, Fla.: Chapman & Hall/CRC, 2003.
What are the Chances? Voodoo Deaths, Office Gossip, and other Adventures in Probability, Holland, B.K. 2002. Baltimore, Md.: The Johns Hopkins University Press.
If you’re not a quant, you might want to start with the last one, by Holland.
