English | ISBN: 1119243521 | 2017 | 600 Pages | PDF | 4 MB
Probability and Conditional Expectations bridges the gap between books on probability theory and statistics by providing the probabilistic concepts estimated and tested in analysis of variance, regression analysis, factor analysis, structural equation modeling, hierarchical linear models and analysis of qualitative data. The authors emphasize the theory of conditional expectations that is also fundamental to conditional independence and conditional distributions.
Probability and Conditional Expectations
Presents a rigorous and detailed mathematical treatment of probability theory focusing on concepts that are fundamental to understand what we are estimating in applied statistics.
Explores the basics of random variables along with extensive coverage of measurable functions and integration.
Extensively treats conditional expectations also with respect to a conditional probability measure and the concept of conditional effect functions, which are crucial in the analysis of causal effects.
Is illustrated throughout with simple examples, numerous exercises and detailed solutions.
Provides website links to further resources including videos of courses delivered by the authors as well as R code exercises to help illustrate the theory presented throughout the book.
发帖
雷达卡
加好友,备注jr
京公网安备 11010802022788号
论坛法律顾问：王进律师
知识产权保护声明
免责及隐私声明
提升卡
置顶卡
沉默卡
变色卡
抢沙发
千斤顶
显身卡
