STAT430
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SuggestedReading
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2009Stat430
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Fall2009
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0Suggested Reading
Recommended books:
Probability theory and random variables:
Mathematical Statistics with Applications
by Wackerly, Mendenhall, Scheaffer, Chapters 1-6: lots of routine, practice questions
A First Course in Probability
by Sheldon Ross: some advanced, sophisticated models, trickier problems
Statistical Inference:
Statistical Inference
by Casella and Berger
[specific to CS AI]
Empirical Methods for Artificial Intelligence
by P. R. Cohen
Mathematical Statistics with Applications
by Wackerly, Mendenhall, Scheaffer (used in Stat 341/342 sequence)
Mathematical Statistics and Data Analysis
by John A. Rice
Experimental design:
Design and Analysis of Experiments
by Montgomery
Regression and ANOVA:
The Statistical Sleuth
by Ramsey and Schafer
Applied Linear Statistical Models
by Neter, Wasserman, and Kunter
Linear Models in Statistics
by Alvin C. Rencher
Practical Regression and ANOVA using R
by Julian J. Faraway, modified and published as
Linear Models with R
by Julian J. Faraway
Stochastic Processes / Probability Models:
Introduction to Probability Models
by Sheldon M. Ross
A First Course in Stochastic Processes
by Karlin & Taylor
Computationally Intensive Techniques
Computer-Intensive Methods for Testing Hypotheses: An Introduction
by Eric W. Noreen
Bootstrap Methods and Their Application
by A. C. Davidson and D. V. Hinkley
Monte Carlo Statistical Methods
by C. P. Robert and G. Casella
Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment
by Peter H. Westfall and S. Stanley Young
Recommended online resources:
HyperStat Online Textbook
Engineering Statistics Handbook
Electronic Textbook by StatSoft
Design of Experiments from ReliaSoft
Handbook of Biological Statistics
UCLA Consulting's Data Analysis Examples
Data & Story Library for teaching statistics
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