Customer Reviews

A Modern Introduction to Probability and Statistics: Understanding Why and How (Springer Texts in Statistics)

5 star:		(2)
4 star:		(2)
3 star:		(2)
2 star:		(1)
1 star:		(1)

 

 

This book reads easily because it gives many concrete examples and uses a tutorial approach to teaching. However, you still need to know some math! You don't need a math degree. A good first course in calculus covering derivatives and integrals, including logs and exponentials, and some introductory combinatorics (basic knowledge of sets, permutations and combinations) is enough. Any sophomore or, at the latest, junior majoring in engineering or hard science has the prerequisites.

An understanding of probability is necessary for understanding statistics, so the first half of this book is probability. Without probability, statistics becomes something like "here are some facts, trust me, now here are some formulas, recipes and tables and you will learn when to use each one". For many people this may be enough, especially if they just need to get something done. But if you want to know why hypothesis testing is done the way it is and how it works, buy this book. For example, many statistics books just assume a normal distribution for sampling and the only thing you need to learn is when to use a one-tailed or two-tailed test and which formula to use. This is valid when working with sufficiently large populations or samples. In contrast, the worked example in this book does not use a normal distribution and it walks you through the reasoning and calculation. The reasoning is applicable to any population and distribution. When you change to a normal distribution the principles remain the same, only the formulas change. You learn the principles.

Now to the book's style. This is a tutorial style book that teaches using examples. It doesn't skip many steps and can feel somewhat chatty. It repeats simple calculations along the way so you don't have to page back and find where that number was calculated. This keeps the flow going. Learning by example is actually a good way to learn if you are new to the material. Some however, may not like this style, so read some online first before buying. If you already have probability under your belt and are up on your math then you may find this book slow going. This book is aimed at scientists and engineers, so if you are looking for a rigorous math book with proofs, look elsewhere.

Summary: If you've got the prerequisites then this is a great book for self teaching at a good price. If you are lacking in math and you need to do statistics now, then pick up a "cookbook" statistics book and come back later when you have the math background. If you know your stuff and need a reference, look elsewhere.

I have a strong general background in math, but not in probability and statistics. I use this book for self-study, and I find that it fits that purpose excellently. There are plenty of examples, and problems are adjusted so that they focus more on principles and understanding rather than on grunt-work calculations.

My main objection, and the reason for giving it 4 stars, is English language. I am not a native English speaker, and it's obvious that none of the authors is either. Even worse, I encounter at least one misleading, or hard to understand sentence per chapter (mostly among problems). The book most definitely needs proofreading and language corrections!

We used this book in our Introduction to Probability course at Georgia Tech. This book is written in a not-so-easy to understand matter and is good for someone that has a strong background in math. A few of my friends doing their Ph.D were helping me with this course and they also found this book hard to understand as well. If you read the text you're still gonna have such a hard time doing the exercises because it doesn't explain everything smoothly. I searched through the internet to find a solution manual for this book and simply they don't have it. You only get the solution if you get the teacher version. The book is written and published in Netherlands and it doesn't have any online resource for students. If you have to buy this book for your class make sure you get "Schaum's Outline of Probability, Random Variables, and Random Processes" or a similar book for extra help, otherwise you'll regret like I do.

I thought this a remarkably clear and well written introduction to probability. I've tried to teach myself some probability and statistics over the years with a number of books, but this is the first that really presented the topic in an enjoyable and easily digestible manor. This is not a super formal math text, but all the ideas presented are backed up with nice proofs and arguments.

My background is in physics, and certainly having a reasonable math background smooths the way.

Unfortunately this book severely lacks step by step examples and makes many assumptions about what the reader does and does not know. I know calculus but most of the steps in the example problems are skipped over. Each chapter is divided into four or five sections but each chapter is only around ten pages long. This means that an entire section of knowledge is crammed into two pages. Add in that half of a page is usually used for a picture and you end up with a book full of theorems but lacking in substance. These aren't even formulas per say but instead are chapters filled with starting points. To elaborate about how bad this book is; I bought a study guide which has more full detailed step-by-step answers than this book. In fact the "full answers" in the back generally consist of one sentence answers but there are no graphs or step-by-step guidance.

It is a beautiful book to read, yet, from a student perspective, the number of exercises at the end of the chapters should be tripled.
I think authors managed to achieve a true balance between theoretical perspective and computational aspects of the subject.

I have a computer science degree in college, and studied math and calculus throughout highschool and college, but I never really understood probability fully beyond random variables. I am immensely fascinated by probability and statistics due to my interest in computational linguistics, but the lack of total understanding in these two fields made it difficult to pursue a career in COMPLING.

To regain confidence in math, I have looked for a textbook that teaches and elucidates probability and statistics, but the search has been disappointing. An introductory textbook on this subject either is too esoteric (indulges in using way too much formal math to overwhelm readers in a failed attempt to show the author's superiority) or treats readers like complete idiots, therefore omitting important concepts, theorems and proofs. I have gone through at least a dozen books and finally I found one that is suitable for self-study, as it makes the concepts and formula clear to me without being verbose or esoteric. This book strikes a perfect balance between mathematical rigor and intuition--a balance that I search for and prefer.

In just a short time of reading this book, now at page 60 out of 480, I was able to understand the concepts of conditional probability, the law of total probability, Bayes' rule, and most importantly, random variables, through succinct English description and appropriate examples. Although I have not finished the entire book, the first one sixth of sampling gives a high probability that the rest of the book on probabilistic distributions and statistics will be just as clear.

If there is anything to criticize on the authors' writing, it is the occasional less-than-natural wording of English due to the fact that none of the authors may be native speakers. For example, I think that on page 28, on the topic of "coincidental birthday", the following sentence is somewhat misleading:

The event B3 can be seen as the intersection of the event B2, "the first two have different birthdays," with event A3 "the third person has a birthday that does not coincide with that of one of the first two persons."

The combination of the negative ("does not coincide...") and "one" in "one of the..." is problematic as far as English grammar is concerned, because it is misleading. Does the authors mean (a) the third person does not share the same birthday with at least one of the first two persons, or (b) the third person does not share the same birthday with either of the first two persons?

After studying the ensuing equations, I determine that the correct meaning of the sentence is (b). So, to be grammatically correct, it should be re-written as: ... with event A3, "the third person has a birthday that does not coincide wither that of EITHER of the first two persons." Or, in more natural English: The third person shares his/her birthday with NEITHER of the first two people.

I really don't feel qualified to rate this book because it quickly went over my head. The first chapters were an easy read and left me wanting to read more of the subject. After that, however the equations quickly progressed to where you may have to have a degree in mathematics to understand it. Not all the variables in the equations were defined, even in the index. This may be a very good text book if taught by someone knowledgeable in the subject, however I could not understand it by reading the book.