Reviews (3)

On balance, this is a great book
Grimmett & Stirzaker's book, *One Thousand Exercises in Probability, 2nd ed.,* contains exercises with answers/solutions to each and every exercise covering a wide range of topics from probability. Although this book is a companion to G & S's 3rd edition of *Probability and Random Processes,* the authors strove to make the *Exercises* book stand on its own.

The 2 previous reviewers took a widely different view of this book. I wanted to have a balanced approach to reviewing this book. I hope this helps.

-- This book has exercises that cover a wide range of topics in probability. It starts from basic issues in probability and eventually covers topics like queueing, Monte Carlo (& Markov Chain Monte Carlo), Ito's lemma & financial option valuation, etc. Any one vaguely interested in probability realizes that the topics covered by Grimmett & Stirzaker are *hot topics* and very useful to those who want to try to get a sense of how important probability theory is in real life. I can't think of a comparable book that is so ambitious and covers so much useful ground in one place. [At least not one with answers to every question.]

-- I am not personally familiar with Grimmett's work (I believe he is at Cambridge University). I am, however, familiar with Strizaker's work (he is at Oxford). I consider him to be one of the finest expositers of probability theory. Stirzaker's views on probability theory (which I read in a different work) is one of the most lucid and sensible I have ever come across. Anyone seriously interested in probability should try to get exposure to Stirzaker's thoughts on the matter.

-- I believe this book is GREAT for self-study. One of the major problems I have with many math, science, engineering, and other technical books is that -- even very good books -- do not provide answers/solutions to the questions they pose. As someone who is very interested in self-study, I find a book like this one -- which has the answers/solutions to ALL of the questons -- to be extremely refreshing and welcomed.

To address the prior criticism that this book does not contain a sufficient amount of detail in the solutions .... I would suggest that such a criticism is unfair. As I pointed out above (and most people know) it is very rare to have technical books like this where there are a great deal of interesting and useful exercises given plus answers/solutions to all of the questions posed. For 2 emminent Oxbridge dons to write such a book is even more exciting.

In all fairness, Grimmett & Stirzaker wrote this book with the intent that it be used along with an appropriate probability textbook(s). Any one willing to take the time to look at the solutions given along with a companion text should be able to work out what went wrong (or right) with any question that the reader attempts to work out.

In closing, I highly recommend this book to anyone who is interested in going from a novice level at probability to a point where you can approach and solve useful problems in probability.

Well worth the effort
I appreciate the other reviewer's oppinion as it is indeed true
that some of the problems' solutions are succinct.

However it is clearly not the point of the set of books to provide
the reader with fully worked solutions to every problem. It is
often like this in maths, you just got to go for it, no matter.

If you kick off from the first chapter and attempt the problems
in increasing order of diffculty keeping the course book by your
side, you should be fine, really.

This course is very rewarding.

Reviews (12)

Great book
Probably one of the most elegantly written book that I have ever read. I am not sure probability and statistics can be introduced with a greater degree of clarity while mainitaining mathematical rigor. Absolutely beautiful flow and crisp results.

Terrible book
As a starter, coming from a non-mathematics background, I will recommend something else. The book goes to advanced topics pretty quickly, leaving a lot to comprehend.

Cannot follow the logic --2nd Ed.
First of all I don't know how the 3rd and 2nd Edition differ.

I am trying to learn Probability and Statistics on my own, and I find it very difficult with this book.

The book does do somethings well.It does explain concepts better than what I have read so far (Schaum's).However, in the sections on combinatorics, especially, and thereafter I cannot follow the logic.I read an example problem, the solution is given immediately with little explanation as to how.The author says the bare minimum e.g. here n=52 and k=13.I have seen the combinatoric calculations, that are the solutions, in a multitude of ways, with sums in the numerator, products in the numerator, and it is not at all obvious as to why.There is insufficient discussion in the solution.

Then in working the exercises, there is nonuniform quality with the even-number solutions.Some answers just have a number, others have the formula, and some have numbers with factorials so you can kind of guess what the author did.But in the case where there is just a number, you can't.

Reviews (19)

A Good Book
Overall, this book is a solid introduction to mathematical statistics. Exposition is clear and it fully motivates all concepts. I really only have one complaint: this book omits a few topics. A relatively minor example is the absence of the cumulant generating function. More disturbingly is that it does not have a full discussion of the multi-normal distribution (possibly to avoid some non-trivial linear algebra?). However, being that the book is otherwise quite complete and these topics can be found elsewhere these are rather annoyances than fatal flaws.

good textbook for intro grad
This is a good textbook designed for introductory stat or econ phd classes. This book assume a decent knowledge in calculus which ought to be expected by those taking the course. Advanced calculus, eg real analysis, is not really required. Some questions are somewhat long and tedious, but the difficulty ought to be expected.

Isbn: 0534203884
Sales Rank: 746168
Subjects:  1. Business    2. Business & Economics    3. Business / Economics / Finance    4. Business Statistics    5. Business/Economics    6. Commercial statistics    7. Management    8. Mathematical models    9. Probability & Statistics - General    10. Reference - General    11. Statistical methods    12. Statistics   

Editorial Review

Science is inextricably linked with mathematics. Statistician David Salsburg examines the development of ever-more-powerful statistical methods for determining scientific truth in The Lady Tasting Tea, a series of historical and biographical sketches that illuminate without alienating the mathematically timid. Salsburg, who has worked in academia and industry and has met many of the major players he writes about, shares his subjects' enthusiasm for problem solving and deep thinking. His sense of excitement drives the prose, but never at the expense of the reader; if anything, the author has taken pains to eliminate esoterica and ephemera from his stories. This might frustrate a few number-head readers, but the abundant notes and references should keep them happy in the library for weeks after reading the book.

Reviews (2)

excellent
this book is amazing good. although lack of proofs, the application side of the book is immense. Toones of good real life examples and things are explained in a very clear and simple way. Very easy to understand and in great details.
Must buy if you really interested in the application side of statistical methods which everyone should.

*Excellent* stats book for behavioral researchers
We used this as our primary textbook in a graduate psychology / consumer behavior research methods / data analyis class, and I found it to be an invaluable aid in statistical analysis. From simple measures such as z-scores, t-tests & f-tests, and chi-squares, to more in depth methods such as GLM, ANOVA, and regression, this book is clear and concise. While it can be slightly cursory at times as to the theoretical underpinnings underneath the data analysis methods being used, it is a very helpful book in understanding how to actually make the methods work, and more importantly, knowing which method to apply in which situation.

Reviews (1)

Reviews (10)

A Great Introduction to Advanced Probability
As the previous reviewers mentioned, this book is a concise and clear introduction to measure based probability. In contrast to some other reviewers, I like it a lot. The proofs ARE clear, the appendices ARE well placed and the order of presentation MAKES a lot of sense. One caveat is in order: since this book is EXTREMELY concise, one may have to think about the proofs and definitions for a while to digest it. The author does not chew up the material for you.

One more thing: This book is not just a rehashing of other textbooks on the topic. The order of presentation and proofs in this book is original (as far as I know) and if you find that you like it you are not likely to find it elsewhere.

A more detailed alternative that may serve as an excellent companion to this book is Probability and Measure by Ash.

Combine the book's originality of presentation with its clarity and its low price and the result is a great buy.

A Total Waste of Time
As I have mentioned above, do not under any circumstances read (or even worse buy) this book. The layout is abolutely terrible and does the book no favours whatsoever. As indicated by previous reviews most of the proofs are completely glossed over with little or no mathematical rigour in sight.The appendices for the selected chapters are pretty much void of any use, and I can't see why the contents of these appendices could not have been included in the chapters in the first place (not that it would of made much of a difference). Hardly anything is explained with much clarity here and I don't know about anyone else out there but I would consider a one line example not much help at all. Everything right down to the way the index is presented is substandard in this book and the authors "attempts" at humour constituted the proverbial last straw for me (I find the assumption that all mathematics students like Star Treksomewhat insulting). In short this book is ABSOLUTE RUBBISH.

Reviews (9)

Do the exercises!
If you are taking a course on probability and stochastic process, and are struggling in your course, then look no further.Start working on the problems in this study guide.Like many other reviewers of this study guide, I was one of those "saved" by this book.(My course text was Papoulis.)

Let me outline the pros of this book:
+ Consistent mathematical notations and conventions
+ Systematic and organized (easily identifiable chapters, sections, and subsections that flow logically from one to another)
+ Excellent summary of difficult concepts at the beginning of each chapter
+ Every end-of-chapter problem adds to your understanding (I'm not saying "most of them", I mean "every"!)
+ Every problem solution is concise and well-presented

The only suggestion to the book:
- Add more intermediate/advanced material into this study guide (e.g. more on Markov Process/Markov chain, Martingales, Poisson Process, advanced Queueing Theory, etc.)

If you like this book, you should also consider the other books (study guides) written by Dr. Hsu as well.Most of them are as compact, concise, and clear as this one.

Good Exercise Book
I am lack of knowledge in random variables and stochastic process. Usually, I grab myself a nice text book, like Yates and Goodman. They're very thorough, but too expensive for me. So I grab this book. Even tough it doesn't provide us with deep concept, it comes with so many exercises and I think this is the way to do for me. I learn quicker from doing exercises.

Reviews (14)

I Hate It When Books Lie About Mathematical Requriements
The book says that its only prerequisites are calculus and probability.This is not true.To be able to understand everything that's going on, you'll need to have a very good grasp of subjects like measure-theoretic probability, Hilbert spaces, and functional analysis.I quit reading the book in the early chapters, when Steele starts talking about things like "spans" and "denseness" for function spaces.I don't know where you went to school, but at my school, I didn't learn these subjects in my intro calculus and probability classes.To summarize, don't buy this book if you don't know measure theory.

If you want to learn quant finance at an elementary level, Baxter and Rennie is much, much better.Moreover, if you're comfortable with measure theory,and you want to learn the math that's necessary for option pricing, you'd be better off buying Oksendal's excellent book, which is at least as rigorous as Steele's book but much more clear.

Riskfreeprofit !!
The book is at the interface of three areas, math, statistics, and finance. While connections between the first two have a long history, it was the connection to finance that caught my attention. Coming from math myself, I needed first to take a closer look at the book to orient myself. The mathematical subjects, smooth sailing, include stochastic differential equations (SDE) as they relate to PDEs; and the ideas from probability and statistics include Brownian motion, martingales, stochastic processes, and the Feynman-Kac connection. Browsing the chapters I found them to be a lovely presentation of ideas with which I am familiar. For me, it was chapter 10 that turned out to have stuff that I wasn't familiar with. That is the finance part, and it is based on a model for Option Pricing developed in 1973 by Fischer Black and Myron Scholes. An arbitrage opportunity [simplified] amounts to the simultaneous purchase and sale of related securities which is guaranteed to produce a *riskless* profit. It was after reading more in this chapter I understood why the book is used in a course at the Wharton School at the University of Pennsylvania. I am impressed with the level of math in this course. Part of the motivation in the applications to finance is that arbitrage enforces the price of most derivative securities. And I learned from ch 10 that the SDE of the Black-Scholes model governs the processes which represent the two variables S, the price of a stock, and B the price of a bond, both S and B representing stochastic variables depending of time t, i.e., both stochastic processes. In the model, S is a geometric Brownian motion, and B is a deterministic process with exponential growth. The two are determined as solutions to the SDE of Black-Scholes.

Reviews (10)

The only way to learn probability
Grimmett & Stirzaker develops probabilty theory rigorously and simultaneously develops a good understanding of how to use the theory in practice.Explains important theorems, uses good examples, etc.I was (inexplicably) assigned Casella & Berger to learn probability and, since that was completely useless, I used Grimmett & Stirzaker very effectively to learn it on my own.

Not good at all
Authors have the knack of throwing in suppossedly profound but obscure comments, probably to show the depth of their knowledge. Doesn't make a pleasant reading at all.

Beauty magazine makes you look ugly, if you get my drift.
Beauty magazine makes you look ugly, if you get my drift.

Isbn: 981024598X
Sales Rank: 1428115
Subjects:  1. General    2. Mathematics    3. Probability & Statistics - General    4. Science/Mathematics   

Reviews (1)

This one will be a classic
Doing problems is the best way to study mathematics. The question to most authors is that: How to select problems that are nice to the students. This book did quite well. As I see, the authors gave the exact right pace to offer the students an exicting course, and give the students a thorough understanding.

Reviews (7)

for Quants only
if you're a quant, you might really love this book

if you're a person who wants to have a "basic" understanding how to use MC for consulting or product pricing with examples, you got the wrong book (not mentioning that your maths must be pretty good).

if you're looking for an Excel example on how to price some basic options, i highly recommend Jackson & Staunton or Wilmott.

Good book
This book is pretty good as it covers lots of different areas of Monte Carlo simulation and some of the newer stuffs, such as copulae, etc.The math presentation is brief but to the point as application of the mathematics to Monte Carlo methods is the emphasis.Intuitive ideas behind the formula is explained pretty well as it tells you where certain formula can be used for.It would be helpful to have taken an advanced course in Monte Carlo methods in Finance to appreciate the book.I would personally suggest Glasserman's course at Columbia U.Prof Glasserman is also writing a book on the subject that he uses for lecture notes now.It would turn out to be an even better book to read.