Probability and Statistical Inference: From Basic Principles to Advanced Models

ISBN-13: 9780367749125 / Angielski / Miękka / 2022 / 424 str.

UK) Penzer Jeremy (London School of Economics

Opis

This text presents key topics in mathematical statistics in a rigorous yet accessible manner. It covers aspects of probability, distribution theory, and random processes that are fundamental to a proper understanding of inference. The book also discusses the properties of estimators constructed from a random sample of ends, with sections on methods for estimating parameters in time series models and computationally intensive inferential techniques. The text challenges the more mathematically inclined students while providing an approachable explanation of advanced statistical concepts for students who struggle with existing texts.

Recenzje

"Learning statistics is one thing; learning to think like a statistician is something else. This book grabs readers by the hand and takes them on a journey through statistics, by the end of which they are well-equipped to think like a statistician. For a book at intermediate level this is no mean feat: ideas are subtle and require a delicate balance of formal mathematics and statistical insight, a balance that is deftly maintained throughout the book. The mathematics is rigorous, but not so much so that underlying intuition is lost. And the statistical concepts themselves are explained with a clarity that is rare in textbooks at a similar level. I wish this book had been available when I was first learning statistics. And I wouldn’t hesitate now to use it as the basis for teaching on any intermediate statistics course. The best compliment I can give is that it was a pleasure to read and gave me new insights, even on material with which I am very familiar. I love this book and congratulate the authors on writing with such clarity and vision. I hope many readers take the opportunity to follow the statistical journey the authors provide."
~Stuart Coles, author of An Introduction to Statistical Modeling of Extreme Values

“Overall, I give Probability and Statistical Inference: From Basic Principles to Advanced Models a solid thumbs up! It’s well suited as a primary introductory probability theory textbook for undergraduates or applied masters students in statistics or data science. It’s also appropriate as a primary textbook for an advanced survey course in probability and statistics. Further, I recommend this textbook to working professionals in any field who seek further insight on probability theory and statistical inference.”

~Gabriel J. Young, The American Statistician

Spis treści

1. Introduction
2. Probability
3. Random Variables and Univariate Distributions
4. Multivariate Distributions
5. Conditional Distributions
6. Statistical Models
7. Sample Moments and Quantiles
8. Estimation, Testing, and Prediction
9. Likelihood-based Inference
10. Inferential Theory
11. Bayesian Inference
12. Simulation Methods