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3.9 out of 5 stars
Statistics, 4th Edition
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39 of 39 people found the following review helpful
on September 12, 2011
I used the first edition of this book in a class I took at Berkeley back in 1989. I again turned to it for a self-study refresher recently and found it's intuitive style quite refreshing and even kinda fun. This book teaches the concepts without all the noise and distraction of more recent books that try to throw in every new technique and software application they can think of. This book is a classic in the field, on a level with Sylvanus Thompson's Calculus Made Easy. No, it won't be the last stats book you ever buy but it will get you up to speed fast and allow you to work much faster through more advanced texts and with a deeper understanding for the theory.

I do have one complaint. I like math and at a few points I wanted to tell the authors to quit teasing me and just give me the equation already. For example, they take several sections of text to introduce correlation and linear regression before finally introducing the actual linear equation. Maybe it's better to introduce it that way, I'm not a teacher. Others have mentioned the lack of standard nomenclature in this book but I can't see how that would be more than a minor inconvenience moving to a more advanced text. Another reviewer mentioned Statistics Unplugged by Sally Caldwell. I also have that book and though it has more standard nomenclature, I found it to be "wordy" and not as intuitive as the book in this review.
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15 of 15 people found the following review helpful
on April 16, 2011
I'm not a "math person," and was compelled to take an Introductory Statistics course as the final math class toward my BA. I approached the course with preconceptions after hearing horror stories from other humanities folks about failure, shipwreck, plagues of locusts, and thoughts of suicide.

This is one of the top half-dozen texts of my entire college career.

Not only do the authors make statistics accessible and even fun, they do so in a consistently smart style that simultaneously simplifies statistical concepts while not pandering in the quality of language overall, or occasions for clever asides. While many professors will end up using modern calculators for the problems, the text bases its lessons on the use of tables (normal, t, and chi-square). I found myself following both the professor and, electively, the text for a more full understanding of "old school" methods. Each chapter has enough embedded problems (with answers at the end of the text) that the reviews and other materials provided by my professor were often redundant. I wish I had access to the answers for each chapter review questions, but that can hardly be a criticism in my "student" copy of the text.

I'll be revisiting this book long after I've ceased being a student. It has helped me have more informed attitudes about statistical products in general, which I suppose was a point of the course and the text.
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77 of 95 people found the following review helpful
on April 11, 2009
I am not a statistics major, nor do I tend to excel in mathematics, but I am capable of achieving if I put enough energy into a subject...that wasn't the case with my stat class last semester, which used this textbook.

This book takes the role of a friendly teacher who dumbs down the material so we "not-so-mathy" students can understand what's going on. The problem, however, is that this book speaks in riddles, teaches in examples, stories, and fake conversations between mathematicians of the past, and doesn't spell out in any clear way what the method is for solving certain types of questions. Also, after using this text for Stat I, I moved on to take Stat II and was pretty lost. In Stat II, they use "scary" language such as p, q, n, instead of "big number" "small number" and "box" (which is used in this text). I found it was much easier for my mind to grasp the consistency and methodology of statistics when using a different, more "advanced" texbook.

Stat can be a very difficult thing to understand when you're treated like a baby. Even my TAs hated this textbook, which kind of says a lot (mainly that a lot of students are confused, and can't get any help from outside tutors who don't speak the pseudo-stat language of this book)

I would not recommend this text to anyone. If you're thinking about taking a Stat class where this text is used, you'd be better off waiting a semester until you can enroll in a class where the teacher values actually learning statistical language.
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12 of 12 people found the following review helpful
on August 26, 2009
This text was used in an Introductory Statistics course I took at Western Michigan University. I found it to be a delightful book that was designed for students with no or little background in statistics. It attempts to take everyday events and show how statistics can be used to make inferences from them. The book does have worked out problems in the back and answers for selected problems in the text.
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17 of 23 people found the following review helpful
on June 19, 2011
I do mathematics tutoring, and I've worked with dozens of students taking introductory statistics courses. A small number of them used this textbook, which I have admitted to them is not very good. The main issue I have with this as a textbook is that it is almost entirely incompatible with how most other courses and textbooks explain the material. If you only need to take a class for some sort of requirement, and this is the textbook used, then it's barely passable. However if you actually want to learn statistics, and especially if you will ever take ANY other statistics class in the future, then this is not a good preparation. This textbook eschews all of the conventional terminology and symbols, which would leave a student confused and ill-equipped to enter any other statistics class.
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3 of 3 people found the following review helpful
on April 15, 2010
The book is a classic. It is well written and explains basics of statistics very well -The language is very simple and the concepts explained are easy to grasp. I would recommend this book strongly for anyone interested in learning from scratch or as a refresher. You can use this book for self learning too.
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6 of 8 people found the following review helpful
on May 30, 2009
The nice thing is the authors know how boring their subject is, address it, and actually try to explain Statistics in "layman's terms". The authors portray a sense of humor in their approach that definitely eases a little bit of the tension associated with this kind of learning. I can't stand Statistics but this book really tries hard to make it as painless as possible.
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3 of 4 people found the following review helpful
on January 7, 2012
You can use this book for self learning tooThis is not an advanced book but it is still very helpful. .The book is a classic. It is well written and explains basics of statistics very well -The language is very simple and the concepts explained are easy to grasp. I would recommend this book strongly for anyone interested in learning from scratch or as a refresher.
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on February 10, 2015
This is one of the very best non-major statistics books around. For people who do not find math easy but still want to wrap their brains around how statistics work this and Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking, 3rd edition are the best books. They both avoid statistical jargon and explain everything beautifully. If you hate algebra there are relatively few formulas here and more importantly the algebra is worked out for you in this book. So, you can see exactly what you are supposed to do. The little math which is here is better explained than what is in Intuitive Biostatistics. For better or worse there are no appendices with the technical details, which is, in my opinion, a loss given how well the authors cover the concepts. The book is full of examples, all of which are interesting. The explanations and examples are flawlessly integrated with very little "fluff".

Unfortunately the book is clearly showing its age. The coverage on graphics is painfully out of date and the lack of support for SAS and R is now unacceptable. A great alternative for people who want to know how to code in SAS or R as well as understand the statistics is OpenIntro Statistics: Second Edition. OpenIntro is so inexpensive, you can easily pick it up to complement this. Another option for people who want clear writing without much math is Biostatistics: The Bare Essentials. It has a bit of fluff but I like its rude and irrelevant style. For better or worse it has SPSS support.

At the end of the day this is in my opinion the very best Intro to Statistics ever written. I just wish it could be updated and given technical appendices with formulas for those who want to go deeper into the math.
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on May 15, 2011
I’ve taught from this book for over 20 years, and I really love it, in spite of its flaws.

First, to address the flaws. Many critical reviewers seem to bemoan the lack of formulas and mathematical notation in this book, but I haven’t found this to be a problem at all. If you want this to be a part of your course, simply type up a formula sheet with the formulas in both English and mathematical symbolism, and — voila! — problem solved. As long as I also do problems on the board and on the test and quiz keys using both English and symbols, my students have not found this to be an issue at all.

A much more serious problem is the non-standard usage of the term “standard error.” In most textbooks, SDs (standard deviations) are for formulas using the parameter σ (or p), and SEs (standard errors) are for formulas using the statistic s (or ˆp ). This is the dominant convention.

However, in the Freedman book, SDs are for lists of numbers, and SEs are for random variables. (He even has an illustration underlining this point on p. 291). Although I do see pedagogical value in this non-standard convention (it makes the students mindful of whether they’re dealing with a list of numbers, or with a chance process) I have to agree with the critics that this could be very confusing to students who go on to more advanced courses. I deal with this issue by making it clear to the students that this usage is non-standard.

The reason that I love this book — in spite of it’s flaws — is two-fold. First the quality of the problem-sets is at a deeper level than is typical in most introductory statistics books. Secondly, I love the wonderful use of box-models to derive all of the statistical techniques. It’s akin to teaching students how to solve quadratic equations by completing the square; when they finally do learn the quadratic formula, they understand immediately where the formula came from. It’s just a formalization of what they’ve already been doing.

In so many statistics books, it’s just one big mess of magical formulas that the students need to learn to use, but why they work and where they come from remains a mystery. Moses might have brought them down from the top of Mt. Sinai, for all they know. (Yes, yes, I know that you can derive them on the board in class, but — let’s face it — it will mostly go in one ear and out the other.) The Freedman book promotes understanding at a deeper level. Indeed, by using box models, a talented student can derive the formulas for herself.
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