Difference between revisions of "Booklist: probability and statistics"
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Revision as of 19:04, 13 March 2014
- D. Huff, *How to Lie with Statistics*.
- Mood, Graybill, and Boes, *Introduction to the Theory of Statistics*, 3rd ed., 1974.
- Seber & Lee, *Linear Regression Analysis*, 2nd ed.
- Hastie, Tibshirani, and Friedman, *Elements of Statistical Learning*, 2nd ed., 2009.
- A. Agresti, *Categorical Data Analysis*, 2nd ed.
- Boyd & Vandenberghe, *Convex Optimization*.
- Efron & Tibshirani, *An Introduction to the Bootstrap*.
- J. Liu, *Monte Carlo Strategies in Scientific Computing* or P. Glasserman, *Monte Carlo Methods in Financial Engineering*.
- E. Tufte, *The Visual Display of Quantitative Information*.
- J. Tukey, *Exploratory Data Analysis*.
- F. A. Graybill, *Theory and Application of the Linear Model*.
- F. A. Graybill, *Matrices with Applications in Statistics*.
- Devroye, Gyorfi, and Lugosi, *A Probabilistic Theory of Pattern Recognition*.
- Brockwell & Davis, *Time Series: Theory and Methods*.
- Motwani and Raghavan, *Randomized Algorithms*.
- D. Williams, *Probability and Martingales* and/or R. Durrett, *Probability: Theory and Examples*.
- F. Harrell, *Regression Modeling Strategies*.
- Lehman and Casella, *Theory of Point Estimation*.
- Lehmann and Romano, *Testing Statistical Hypotheses*.
- A. van der Vaart, *Asymptotic Statistics*.