Introduction to Probability and Statistics Using R
by G. Jay Kerns
Number of pages: 412
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
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by Marcus Kracht - UCLA
Contents: Basic Probability Theory (Conditional Probability, Random Variables, Limit Theorems); Elements of Statistics (Estimators, Tests, Distributions, Correlation and Covariance, Linear Regression, Markov Chains); Probabilistic Linguistics.
by Brenda Meery - CK-12.org
CK-12 Foundation's Basic Probability and Statistics– A Short Course is an introduction to theoretical probability and data organization. Students learn about events, conditions, random variables, and graphs and tables that allow them to manage data.
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.
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This book introduces students to probability, statistics, and stochastic processes. It can be used by both students and practitioners in engineering, sciences, finance, and other fields. It provides a clear and intuitive approach to these topics.