I'm in love with this book and I feel like it was written with me in mind, so if your math background and goals are anything like mine, I can't recommend it enough.

So, here's my deal: I'm a med student and am about to start a bio statistics course. I wanted to brush up on stat ahead of time over spring break, but I knew I'd never bring myself to read a serious stat book on the beach (especially having ADD). I've never taken a stat course, but my math education got as far as calculus many years ago, and I teach SAT math so I'm not too rusty on algebra. I'm also a general-purpose science nerd and feel pretty comfortable with the fundamentals of probability.

Most of the chapters started out reviewing things I already knew - for example, one of the first chapters goes over the definitions of mean and median and how to calculate them - none of which was news to me. (Ironically, even though the author probably ought to include such basic concepts for the sake of completeness, anyone who doesn't already understand how to calculate an average is probably going to find this book too advanced). But the chapter then went on to explain how to calculate standard deviations and other more advanced concepts I'd long since forgotten at a pretty ideal level.

So, at my present math-nerd rank, some of the book was skimmable review, and most of it was exactly what I was hoping to learn presented in a way that was neither dumbed-down nor confusing.

I was afraid that the gimicky nature of a cartoon math text might go along with sloppy pedagogy, but it's exactly the opposite. I feel like a lot of thought was put into presenting the material in the most logical way possible. It's also ideal for visual learners like myself, since every concept is shown as a picture or graph, sometimes in multiple ways. And, of course, the cartoons make it fun to read. Don't expect the jokes to be hilarious, but they're cute enough to keep my attention, and that's HUGE.

Now, here's who I think shouldn't buy this book: I think if you're a serious math geek you're going to find this book too slow. (On the other hand, a serious math geek probably wouldn't buy a cartoon math book anyway...) While it might be useful to a geek who's just forgotten an equation or two, you'd have to wade through a lot of cutesy stuff to find a specific bit of info.

I also think you shouldn't buy this book if you're a total math-a-phobe. The book assumes a fair amount of math background, and uses scary greek letters. If you're up for a challenge, I think almost anyone can get some use from the book, but if your math skills are really lacking, you'll have to be brave when reading it. It's not going to hold your hand. This book plus a patient math-geek friend to fill in the gaps might get you through, though. I hate to discourage anyone from buying this book, since I think it does such a fantastic job - but you should have fair warning that it does go into moderately advanced concepts.

In short, this is a book for nerds who think math is kinda cool, are already comfortable with the basic concepts of probability, and are looking for a serious but fun crash-course in statistics. It's also ideal for visual learners and those who find it difficult to force themselves to read prose-heavy texts.

I personally feel like I'm going to rock my bio stat class thanks to this book, and I seriously enjoyed reading it.

While not perfect (what book is?), this is a worthwhile treatment of statistics. Topics are covered in a accessible and adequate depth, with appropriately entertaining cartoons intermixed between the pages. At some points, it can be difficult to comprehend what the author is trying to relay, but that's coming from this reviewer (who does not possess even a basic calculus background) --if you don't fully comprehend a passage, re-read it until you do (or quickly research the theoretical aspects of the particular subject from other sources and come back to it then). For example, I could not decipher why averages taken from many samples from the same population would always, in theory, eventually form something bell-shaped (regardless of the actual population distribution) --after reading a bit from other sources, and giving it some thought, I determined that the best explanation relates to the fact that the data, as a whole, is not how the sampling distribution is developed; rather, since the sample averages/means make up the sample distribution, and those averages will tend to cluster more and more around the population mean as the sample averages begin to reflect the central tendency of the population, it will, by default, start to resemble the Gaussian/normal distribution. Consider that the mean only represents the central tendency of a data set (and not the totality of the data). That's an obvious deduction, but this was not explained in the book (the book does explain some theory, but some key points have to be thought about --the "why" for the "what").

If you are new to statistics, have taken courses in it and need a refresher, or are interested in understanding (key word there) the essential components of the subject, I highly recommend this book. Wheelan's "Naked Statistics" is also a good read, but I don't think that any one title will make you a "stats expert". I recommend that you read EVERYTHING that you can get your hands on, start working through the free online Khan Academy stats material, and practice. Practice, practice, practice.

I already have a good knowledge of statistics but got this to as a general reference, since it is more succinct than many other stats books.

For actually learning, I think this book is good if you struggle with basic concepts like standard deviations, z-scores and dice roll probabilities. If you are taking your first stats class in college, this book by itself would maybe get you to a B (depending on the teacher). The material ends at linear regression, and doesn't say much more about it that isn't obvious, so I don't think this will teach you any techniques that would actually be useful in the real world. It will however give you part of a foundation for learning those.

I think the book falls into the common trap of similar books that try to make complicated concepts accessible. It spends way too much time overexplaining the easy parts of the subject, which is probably already not hard for most people. The middling material is not given as much attention, so is not that much easier. However I feel that stats textbooks often have a particularly bad habit of overcomplicating simple things, so relative to those this one is quite good. It will only put you to sleep a little bit. When you get to the hardest parts of the subject, the whole accessibility begins to fall apart in the face of irreducible complexity, and the veneer of simplification actually makes it harder to understand. This one ends with regression, and I found that chapter confusing despite already knowing regression. Although then again, most other stats books are even worse. However, usually when I'm looking for a simplified description of a subject, I'm interested in the simplification of the hard parts. I figure that if I need a simplified version for the easy parts, the harder parts will be hopeless anyway, so the problem is that I lack some important foundation rather than how the material is explained. Maybe the assumption is that most people never finish the book so its better if the early chapters are done best, but the early chapters of this would cover maybe your first midterm. And usually that is not the one you need help with.

Ordinarily I love concrete examples and vignettes for explaining stats because I think it's not really a complicated subject, it's just easy to get lost when you don't have the right intuition. However the cartoons and stories in this book don't really add much, they have a lot of filler that just tells a story to tell a story, and doesn't actually help explain the concept at hand. Maybe if the material was new to me they would help ward off boredom. The humor is pretty dated but to the point of being quaint, so I can't really fault it, having indeed been amused if not in the intended way. It might have been better to include humor *about* statistics, rather than barely relevant jokes that sort of tangentially reference statistics.

Statistics is the kind of subject where just learning 10% of it gives you some useful tools for understanding a few common real-world situations (including those studied by other subjects) and learning about 30% will equip you to deal with most situations you face when not deliberately looking for tough problems, ie. doing statistics research. This book gives you about 5% which is to say it teaches you enough to solve toy problems, but falls short of teaching you to apply it to real ones. For example it teaches the t-test for comparing normally distributed variables, which is indeed a very useful test. But often variables are not actually normal. There's usually some tricks you can do to fix that (eg. taking the log), but the book doesn't go into it. Or it doesn't cover the chi-square test, which is closely related and arguably comes up more often in life (and almost as often in stats exams).

As I said, if you read this book very carefully it will give you okay understanding. If you want a good understanding the best thing is probably to find someone to show it to you with realistic examples. As far as learning from books, I would consider this one a warm up before you start on the real thing.

I've owned this book for a long time and I regularly use it to learn new concepts I need to understand. I also use it as a reference for things I've learned previously but have forgotten a bit. It works for me, but I could see how it may not work for others.

If you're looking for a text book with lots of examples, then this is not your book. If you need someone else to guide you and explain things to you, then this is not your book. This book is about explaining the concepts concisely & simply with real life examples. But just because it's concise, it doesn't mean it's simple. You will need to study.

This book is all about explaining the ideas of stats simply, and it's done with cartoon figures and down to earth examples. Nothing abstract here. Each section is concise and brief. Everything you need for each step is clearly explained and with a little study, graspable. Each section is carefully built on top of the previous one, so because of this grading learning there is never a large leap to a new concept.

I would recommend the book for someone who has previously studied Stats, but needs a quick review.

I would recommend it for use as a quick reference tool. It's easy to find what you want, and since the explanations are brief, you don't need to spend a lot of time in research.

Pleased

This book is a good introductory level look at Statistics. The authors cover what the subject of Statistics is, the history of Statistics, some of the theories and terms, and also shows some applications of the subject.

The weakness of the book is that there are a lot of formulas given and not enough discussion of how those formulas are derived, so one would need to use other statistics texts to supplement the material. Thus this book cannot stand alone. On the other hand, if one is just trying to get an overview of the subject, then there is a lot to skip over. The authors do make a humorous presentation of the material, so those that are looking for an overview may find this a more enjoyable introduction to the subject.

There is also a lot to do with Statistics that the book does not mention. It does cover probabilities, but when it comes to distributions it focuses only on Standard Normal distributions. I don't believe it ever mentions Uniform, Poisson, or other types of distributions which most Statistics courses cover.

The best part of the book is the examples, some of which are carried through for several chapters to help the reader better understand the subject. Although, even with the examples they are a bit inconsistent in their presentation. For example, in one case they started to discuss the use of statistics to compare the salaries of male and female employees in the same job, but they never complete the discussion. The examples of racial bias in jury selection, and the gas mileage comparison of two different types of gas are much more complete.

This is a decent book, but not up to the level of Gonick's excellent "Cartoon History of the Universe" series, and not strong enough to give it more than three stars.

Good general purpose book for classroom library. This is a great set of books in cartoon form. Easy to understand. Good condition. Arrived quickly.

Ok, "Better than my college textbooks" isn't that difficult; but, it's important to know. I used this book in school, and constantly use it (and recommend it) at work.

If you're confused by statistics, or even if you're not; this book explains in a few pages what other books spend 50 pages on. And, it explains it more clearly.

Given its low price, and incredibly useful content, I'd say this is a "must" for just about everyone. If you ever go to the casino, buy a lottery ticket, or do anything else with an element of risk, this is a worthwhile read.

Oh, and if you're going to take a statistics class, reading this book *before* the first class is highly recommended.

Libro molto divertente, informativo (ovviamente NON è un libro di testo di statistica!) e utile per ripassare e fissare le idee. Assolutamente consigliato!

Buen libro para entender conceptos complicados. Me gusta que incluye conceptos complejos y aunque es un acercamiento sencillo y breve me ha ayudado a explicar a clientes no técnicos temas complejos como diseño de experimentos.

Muy buen libro!aunque ha legado un poco dañado(

Muito bom para entender de estatística

An excellent introduction to all the core concepts of statistics. Better than my MBA statistics class. I heartily recommend Cartoon Guide to Statistics.

Actually, however, the reader needs some background in a number of areas to really appreciate and fully understand the concepts introduced.

Cartoon Guide to Statistics--already super excellent--could be 100% improved with more examples for each units and also actual problems to solve. The problems should have solutions with the approach--specific steps used and explained--to get to the solutions.

Again, as is, an excellent introduction to the core concepts of statistics.