This book is intended as a text for a two-quarter or two-semester post-calculus introduction to probability and mathematical statistics for undergraduate students in their junior or senior year, and also for graduate students in the quantitative sciences (e.g., agriculture, computer science, ecology, economics, engineering, epidemiology, genetics, psychology, and many others). The book designed to effectively serve two different audiences (a) majors and minors in mathematics and statistics and (b) students in quantitative disciplines with the appropriate mathematical background and with a…mehr
This book is intended as a text for a two-quarter or two-semester post-calculus introduction to probability and mathematical statistics for undergraduate students in their junior or senior year, and also for graduate students in the quantitative sciences (e.g., agriculture, computer science, ecology, economics, engineering, epidemiology, genetics, psychology, and many others). The book designed to effectively serve two different audiences (a) majors and minors in mathematics and statistics and (b) students in quantitative disciplines with the appropriate mathematical background and with a serious interest of understanding probability and statistics at the foundational level.
F. J. Samaniego has served on the faculty of the University of California, Davis, for four decades, teaching upper division courses on probability and mathematical statistics numerous times. In 2002, he received the UCD Academic Senate Distinguished Teaching Award. He was the 2004 recipient of the Davis Prize for Undergraduate Teaching and Scholarly Achievement.
Inhaltsangabe
The Calculus of Probability. Discrete Probability Models. Continuous Probability Models. Multivariate Models. Limit Theorems and Related Topics. Statistical Estimation: Fixed Sample Size Theory. Statistical Estimation: Asymptotic Theory. Interval Estimation. The Bayesian Approach to Estimation. Hypothesis Testing. Estimation and Testing for Linear Models. Nonparametric Statistical Methods. Tables. Bibliography. Index.
The Calculus of Probability. Discrete Probability Models. Continuous Probability Models. Multivariate Models. Limit Theorems and Related Topics. Statistical Estimation: Fixed Sample Size Theory. Statistical Estimation: Asymptotic Theory. Interval Estimation. The Bayesian Approach to Estimation. Hypothesis Testing. Estimation and Testing for Linear Models. Nonparametric Statistical Methods. Tables. Bibliography. Index.
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