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Head First Statistics Paperback – Sep 5 2008
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About the Author
Dawn Griffiths started life as a mathematician at a top UK university. She was awarded a First-Class Honours degree in Mathematics, and was offered a university scholarship to undertake a PhD studying particularly rare breeds of differential equations. She moved away from academia when she realized that people would stop talking to her at parties, and went on to pursue a career in software development instead. She currently combines IT consultancy with writing and mathematics.
When Dawn's not working on Head First books, you'll find her honing her Tai Chi skills, making bobbin lace or cooking nice meals. She hasn't yet mastered the art of doing all three at the same time.
She also enjoys traveling, and spending time with her lovely husband, David.
Inside This Book(Learn More)
Most Helpful Customer Reviews on Amazon.com (beta)
(I do have one criticism: it appears that there are some spelling errors and exercise mistakes. They are not overwhelming, and, fortunately, you learn enough to recognize the mistakes, but they should be noted. However, they are so mild, it is not worth spoiling a good review.)
The greatest strength of this book is the progressive way it builds understanding by clearly explaining exactly what each statistical function means, what the results of each function shows about the data, and when it should-- and shouldn't-- be applied. By the end, anyone who reads carefully and does the exercises will have a pretty firm grip on the essentials of statistical analysis.
The book is unusual in its concept and design, too. The concepts are served up in easily digestible bites with lots of graphics, useful sidebars containing supplemental information, and exercises based on practical, real-world cases. No math beyond basic algebra is necessary for doing any of the exercises in the book. Finally, the tone is light and conversational, but it isn't at all condescending or cutsie.
This most certainly is not an advanced textbook or a comprehensive reference manual. However, for anyone who needs an introductory text or a review for a stats exam, this is the book to get. I recommend it most highly.
While I have to commend the creators of this guide for an innovative approach, there are some major problems with the mathematics in the book. The worst example I can think of is that of Bayesian analysis (a very important concept, but a rather difficult one to understand). The example is confusingly presented, and, worse still, the method they give for solving the problem is simply wrong, and is actually solving a much simpler problem that does not even require this technique. Quite simply, I cannot understand how any person well-versed in statistics--let alone multiple people--could make errors of this magnitude; in the end, I couldn't justify spending the money for it.