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This book is essentially a summary of the major theoretical topics in statistics, at an introductory level. The focus is on theory, not on data analysis or modeling, but there are more connections to data analysis and modeling than is typical among books on the same topics. The main flaw in this book is not that it does anything poorly, but rather, that it omits a lot.
The book is very balanced in its coverage of different topics, its discussion of the frequentist vs. Bayesian paradigm, etc. It mentions parametric and nonparametric inference, including hypothesis testing, point estimation, Bayesian inference, decision theory, regression, and even two different approaches to causal inference. The book also paints a fairly whole picture of how the different topics relate to each other and fit into a unified theoretical framework. Another huge strength of this book is that it always omits unnecessary technical details, including only streamlined discussions highlighting essential points.
The main weakness of this book is that certain topics are only brushed upon and not adequately explained. The first two chapters are deep enough for students to get a more or less complete understanding of the important ideas (assuming they do the exercises). But, for example, the 4th chapter covering inequalities is simply a collection of equations and formulas: the text explains how to use them, but not where they come from or what their intuitive interpretation is. This problem arises throughout the book but it is most evident in chapter 4. I want to remark, however, that this problem is widespread in statistics textbooks, and this book is still less lacking in this respect than is common among typical texts.
I'm not sure this book makes the best textbook. In my opinion most students would benefit from a text that offers more explanation of the meaning and driving ideas behind theory. However, I like the way this book gets to the main points quickly and omits confusing and tedious details and irrelevant tangents. This book may be good for students who are briefly studying statistics and will never take a future course. This book is useful as a very basic reference, but I think its best use is for self-study--advanced students will find it one of the quickest and best ways to get an overview of most of the fundamental topics in theoretical statistics.
Honestly, I think Wasserman is an outstanding writer, and part of me wishes he would expand this book to the scale of something like Casella and Berger's "Statistical Inference", covering more material and adding more discussion of certain topics, but retaining the style of being to-the-point and omitting tedious details. I think this is one of the best books of its type out there but I refrain from giving 5 stars because I think Statistics is one area where most of the 5 star books have not yet been written.
I find it hard to rate the quality of the book. I am from a non-mathematical background (I got no further than calculus in college), and I've been working for three years now on building math skills, especially statistical analysis and inference. I asked a fellow employee (whom I thought I could trust) for a recommendation on a good book for someone with rusty math skills who is trying to learn statistics. This was his recommendation.
This is NOT the book for that purpose. I realized on my first perusal of the book that he was being snide and sarcastic, as I subsequently learned was his custom. This book is a reference, full of complex mathematical notation, that is excellent (so far as I can determine) for reviewing concepts you have already learned and mastered. It is the worst possible choice for someone who is just starting out on learning statistics.
I can now, finally, begin to dip into this book at least in places, and follow the material. So I'm glad, in the end, that I got it. It will eventually prove useful to me.
I'm taking a first year graduate course in statistical inference at UC Berkeley, for students who lack the presumed advanced undergraduate prep in statistics. I ordered the book in advance and used Part I to brush up on probability (my only prior exposure to probability was auxiliary to quantum mechanics, and during actuarial exam prep, which is at a slightly lower level as it doesn't involve asymptotic theory). Part I plus chapter 6 unified a lot of concepts, and provided me with a solid, big-picture view of probability and statistics. I come from a pure math background, so I sometimes find Wasserman's liberal use of notation a little dizzying. I also wish he would've added significantly more remarks in the appendices about the measure-theoretic underpinnings of the subject. For example he could have merely OUTLINED some proofs (of theorems that are otherwise taken for granted) without compromising the application-oriented tone of the book. Having said all that, this book still seems like a good starting point for those who are interested in USING statistics e.g. actuaries or research scientists, (not for those who plan on doing research in theoretical statistics).
Apenas he terminado la parte de probabilidad (alrededor de la pagina 80), y hasta ahora el contenido me ha parecido muy bueno; lo primero que note que me llamo la atención fue la cantidad de información que el libro contiene en apenas unas paginas, no da rodeos y en mi perspectiva explica las cosas de una manera muy clara, lo que si se tiene que tener en cuenta es que se necesita un conocimiento previo de matemáticas decente , en especial se necesita poder entender calculo, álgebra, formalismo matemático y algo de álgebra lineal.
I'm not finished with the book but find it very readable and helpful. I was a little disappointed to receive the book and notice that there was a problem with its binding. It wasn't enough of a problem for me to want to return the book, but annoying nonetheless.
The book presents an ultimate introduction to statistics with references to the literature for the interested reader. Unfortunately, there are many (typographical) errors in formulae that make the text somewhat hard to read, and the erratum available online does not cover all of the errors still present in the second edition.