Comments about oreilly Head First Statistics:

Hate math? Need to turn data into information? Information into answers? This book is near perfect. Easy to read text, easy to follow examples, easy to understand diagrams. I only wish my stats professors made it this clear. Head First Statistics does an excellent job of making the use of statistics applicable to life...not just to actuaries. Whether you are looking for a book to help you get a better foundation of statistics or one that will help you recall what you learned (or should have learned) in college, I highly recommend this one.

Comments about oreilly Head First Statistics:

If you need to understand the basics of statistics and statistical concepts, but are terrified of math, then this is probably the book you need to check out. This book moves slowly through basic statistical concepts, using lots of pictures, graphs, and diagrams to make the explanation more meaningful. Again, if mathematics doesn't scare you, you'll be quickly bored by this book. But for those who are scared of math, this is a perfect book to help navigate the world of statistics.

While this book doesn't cover a huge number of concepts (e.g. ANOVA is not covered at all), those it does cover are done well. When complete, the reader should have a good understanding of data visualization, basic statistics (mean, median, mode), the most common sampling distributions, regression analysis, and common parametric tests (including tests based off the normal and chi-square distribution).

All in all, I think this book will be entertaining for most readers, and the material is presented in a way that is engaging and relevant. Most statistics students are naturally confused when discussing probability distributions, but this book presents it in the context of Las Vegas, which makes it much more understandable for the average reader.

While not for everyone, this is a good introductory statistics book that makes difficult concepts much easier to understand. If you have a degree in statistics or are otherwise well-versed in the subject, you likely won't find what you're looking for here. However, those without math-based college degrees will find a fun read and good introduction to the subject of statistics.

Comments about oreilly Head First Statistics:

I can remember my introduction to statistics--even though it was a long time ago. It was, for me, initially, a difficult subject--despite the fact that I was an engineering student.

The Head First Statistics book uses a "conversational style" and "multiple learning styles" in an attempt to present the material in a more effective manner--compared to traditional texts. The attempt is largely successful, in my judgment.

Particularly helpful is the early introduction of charts and graphs. Not only does this approach help demonstrate the concepts, but it also provides the student with information needed to correctly create visual presentations of the data.

One issue, that I can recall to this day regarding statistics, is that it can be a challenge for those new to the subject to know what analytical technique to use in a given situation. For the mathematically adept, this may not be an issue. For all the rest of us, who need (or want) to apply statistical methods to real-life situations, selecting the right choice can be difficult.

One excellent example of the Head First teaching method that helps the student understand the choices is Chapter 3, Measuring Variability and Spread. Starting with simple tasks, the chapter moves into a discussion of standard deviation and variation in a natural progression.

That progression, from the simple to the complex, characterizes the entire book. Later chapters cover probabilities and probability distributions, sampling, and on to correlation and regression analysis.

The author (and publisher) have a clearly defined market for this book (see page xviii). I expect this book to be successful within that market. In fact, I wish I had had this book when I started studying statistics. It is important, however, to note that for math, engineering and science students, this book is a supplement (a useful one) to the more traditional texts on statistics.

Comments about oreilly Head First Statistics:

All of the Head First series are written in a new style, which is supposed to be more effective at teaching. There are many different kinds of things going on in the book, and for the most part the mix seems to work well. Written in a very friendly style. Not written like a textbook. I disagree that this book will let you master statistics. It will most likely make you competent at reasonably simple stuff. I think some of the detail presented is sloppy in a couple of places. There are a few more mistakes in the book than I would have expected for such a large team involved. It is very much more than a single person writing a book.

Critisms:

Over the years I have seen a number of problems when people choose to work with units of "percent". I think the only good solution is to discourage people from using percent in any description or analysis.

The term "normal distribution" has far too much baggage to be useful to anyone. I think every statistics book should endeavor to get people to avoid the term. Perhaps one incentive to get people to stay away from this term is to point out that distributions of undefined variance exist.

There also exist many problems where the domain of the independent variable is finite, and the use of a Gaussian in those circumstances can lead to problems.

Starting the book off with charting is as good a place to start as any. Axis origins are discussed, axis transformations aren't.

Frequency is used in many places where a count might be better. For example, frequency is often a "rate" of doing something (in my world), which means that a sample histogram is the same as a population histogram (except for noise in the sample).

Some uses of the word variance seem to be describing standard deviation.

I think the goodness of fit testing on the croupiers needs to be expanded.

Some people will think that correlation requires a straight line relation between variables, not any functional relation between variables.

The bivariate example chosen is not a good choice for explaining regression, or at least the simple kind of regression done for this example. This example really calls for showing the difference between Y(X) regression, X(Y) regression and orthogonal regression.

Not that I am short, but I hope Julie never gets a date. :-) That notwithstanding, if a person was only going to have a single statistics book, this would probably be a very good choice.

http://elug.ca/reviews/head_first_statistics.shtml

Comments about oreilly Head First Statistics:

I find writing reviews of the Head First series of books difficult. Not because they are badly written, or because they do not cover the subject matter well. It is simply that they are so good. So let me set the tone by saying: I challenge anyone to find a better book for learning basic probability and statistics!

Head First Statistics was written by a mathematician for non-mathematicians. The author and editors have obviously put in a great deal of effort to create something out of the ordinary. This book is clearly a labour of love, as it is a low effort and fun way to learn probability and statistics!

I studied Mathematics at University, and statistics was something I had little contact with until a first year introduction to the subject. This clear and simple book will take you painlessly from having absolutely no knowledge of probability and statistics, to a level commensurate with university entrance. It stops short of deriving the central limit theorem from first principles, but it will make you aware of what it is and show you how it can be applied. I gained a clear understanding of concepts I had merely glossed over at university over 20 years ago.

This is an interesting and engaging book, written in the Head First series' hallmark style (tells you how, but also shows you why). Even if you have absolutely no knowledge of statistics, it will not be a barrier to gaining an in-depth understanding of basic statistics from this book. I really enjoyed reading this book. Highly Recommended.

I did find a few spelling mistakes, and a reviewer on Amazon pointed out that there were a few mistakes in the exercises (I must confess I didn't work through every single one!).

Disclosure: a copy of this book was supplied by O'Reilly. I did not let that influence this review.

Comments about oreilly Head First Statistics:

Let me start off by saying that I have used many student aiding books throughout my school year but I have never approached a book like this. I tend to stop reading a book if it is not interesting or just does not make sense. What I like about this book is that it teaches through the methods of interaction by putting you in a situation and having you solve problems that associate with the situation.

Also, I enjoy looking at the book illustrations because it allows me to focus on the situation and because some of them are amusing. I do not do well in statistics but thanks to this book, I actually understand the concepts and I can see the difference through my grades.

The only thing I could say about this book is that it would have been nice if the book included a bit more practice problems to practice with. But, overall I say that this is definitely a book worth buying if you are learning statistics.

Comments about oreilly Head First Statistics:

This is a very readable study book for new university students (or people around that stage) learning statistics and probability for an academic course. It goes to great lengths to be fun and memorable to read for people who probably have a lot of books to get through, and who may find the topic difficult. It uses clip art and photography extensively, as well as breaking up the routine of the text with different styles of content, and lots of exercises. A typical page has a simple graph or algebraic equation with "hand written" annotations emphasising key characteristics, then a photograph of a student (to whom the reader can relate) making some comment, and a few paragraphs of text. It adds up to something covering many pages, but which is easier to digest.

The publishers make a big deal of the "Head First" style, beginning with a whole chapter about it. The repetition works quite well although I sometimes think that I'd rather cram something new in to my fading grey-cells than hear the same story again. My favourite part of the technique was the brief annotations on pictures and in the observations by the photographed people. They often summarised a tricky point very clearly and concisely. Making a formula talk about itself and who it is similar to, is surprisingly good. Sometimes the repetition got the better of me, for example on pages 416, 417 and 418 where a point that was merely about an example was made 4 times.

There are lots of really well designed examples. They are based on plausible scenarios such as a gym that wants to allocate new members to the class with the closest average age, but keeps getting into a muddle because they do their statistics wrongly. In one, a 17 year old man joined a class where the median age was exactly 17, only to find out that it was a mother-and-toddler swimming class and he was not welcome! The exercises build on these examples. Although I found them generally easy, I think that they would be well balanced for a person meeting these topics for the first time.

For myself, I was looking for a reminder about which statistical techniques can be applied to different types of experimental data, but I did not find that; the pinnacle of the book's coverage seemed to be the normal distribution. I was nevertheless pleased to find a page about sources of bias in badly chosen sample sets. Its main topics go from plotting simple data to averages and variance, an introduction to probabilities, the binomial, geometric and poisson distributions, the normal distribution, sampling and making predictions about the larger population, hypothesis tests, then finally the chi-squared test and correlation lines.

There were some over-simplifications, such as that time should always go on the X axis of a line chart, whereas I'd expect to see the controlled variable which isn't necessarily time. Some charts had compressed areas representing large gaps in the data set which is a trick to be used sparingly, and actually worked against the topic at hand. I found a few mistakes, such as a graph axis on p38 labelled "Hours" which should be "Age", and a data set on p61 miscopied from p55. The print quality is not as good as books on artistic topics; most of the photographs are too dark.

In summary, Head First Statistics covers its topic very clearly, and is an excellent study aid for basic probability and statistics. It looks very different from the average book, and almost all of those innovations work really well, especially the one-sentence annotations. The examples and exercises are strong, and the book progresses well through advancing topics.