Difference between revisions of "Booklist: probability and statistics"
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# D. Huff, ''How to Lie with Statistics''. | # D. Huff, ''How to Lie with Statistics''. | ||
# Mood, Graybill, and Boes, ''Introduction to the Theory of Statistics'', 3rd ed., 1974. | # Mood, Graybill, and Boes, ''Introduction to the Theory of Statistics'', 3rd ed., 1974. | ||
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* Original author: [[User:Datacraftsnet]] | * Original author: [[User:Datacraftsnet]] | ||
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| + | == External links == | ||
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| + | * A related [http://stats.stackexchange.com/questions/6538/mathematician-wants-the-equivalent-knowledge-to-a-quality-stats-degree stats.stackexchange.com thread]. | ||
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[[Category:BookList]] | [[Category:BookList]] | ||
Latest revision as of 09:02, 7 June 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
- 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.
Metadata
- Original author: User:Datacraftsnet
External links
- A related stats.stackexchange.com thread.
