Introduction Probaility and Statistics
by Muhammad El-Taha
Publisher: University of Southern Maine 2003
Number of pages: 147
Topics: Data Analysis; Probability; Random Variables and Discrete Distributions; Continuous Probability Distributions; Sampling Distributions; Point and Interval Estimation; Large Sample Estimation; Large-Sample Tests of Hypothesis; Inferences From Small Sample; The Analysis of Variance; Simple Linear Regression and Correlation; Multiple Linear Regression.
Download or read it online for free here:
by David Aldous, James Allen Fill - University of California, Berkeley
From the table of contents: General Markov Chains; Reversible Markov Chains; Hitting and Convergence Time, and Flow Rate, Parameters for Reversible Markov Chains; Special Graphs and Trees; Cover Times; Symmetric Graphs and Chains; etc.
by Wolfgang Härdle - Cambridge University Press
Nonparametric regression analysis has become central to economic theory. Hardle, by writing the first comprehensive and accessible book on the subject, contributed enormously to making nonparametric regression equally central to econometric practice.
by Pavel Bleher, Alexander Its - Cambridge University Press
The book covers broad areas such as topologic and combinatorial aspects of random matrix theory; scaling limits, universalities and phase transitions in matrix models; universalities for random polynomials; and applications to integrable systems.
by Prasanna Sahoo - University of Louisville
This book is an introduction to probability and mathematical statistics intended for students already having some elementary mathematical background. It is intended for a one-year junior or senior level undergraduate or beginning graduate course.