Cartoon Guide to Statistics | Larry Gonick, Woollcott Smith

Cartoon Guide to Statistics | Larry Gonick, Woollcott Smith | Cool

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Cartoon Guide to S...

	Cartoon Guide to Statistics Larry Gonick, Woollcott Smith Collins, 1994 - 230 pages average customer review:based on 53 reviews view larger image
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highly recommended

If you have ever looked for P-values by shopping at P mart, tried to watch the Bernoulli Trails on "People's Court," or think that the standard deviation is a criminal offense in six states, then you need The Cartoon Guide to Statistics to put you on the road to statistical literacy.

The Cartoon Guide to Statistics covers all the central ideas of modern statistics: the summary and display of data, probability in gambling and medicine, random variables, Bernoulli Trails, the Central Limit Theorem, hypothesis testing, confidence interval estimation, and much more--all explained in simple, clear, and yes, funny illustrations. Never again will you order the Poisson Distribution in a French restaurant!

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excellent.

this is great as a refresher and a road map of what to study in-depth.

Cool

This book is so cool! It makes the topic clear and fun at the same time.

statistics made simple through cartoons

I wrote a short review of this book previously for Amazon and my opinions have not changed very much. However, Gonick deserves credit for coauthoring his cartoon books with experts in the field. This way he avoids mistakes and brings out the important messages that, in the case of this book, a statistician would want to teach his students.
Recently, I used the cartoons on p-values to help another statistician with a presentation on p-values for an audience of medical researchers. I found the relevant cartoons to be humorous and very instructive.

Also, I discovered that in addition to the standard topics of estimation, hypothesis testing, regression, correlation and analysis of variance, Chapter 12, simply titled "Conclusion" has a brief description of many advanced topics, particularly in multivariate analysis.

Multivariate topics include Chernoff faces, cluster analysis, factor analysis and discriminant analysis. Other advanced topics mentioned are random walks, time series analysis, image analysis and even resampling (bootstrap, jackknife and randomization).

Each is described with a single cartoon. This reminds me to again warn that these cartoons alone cannot do justice to the various topics being taught. However, careful selection and placement into the context of a course can bring home important points to students better than just conventional teaching methods. I wouldn't hesitate to use this material to supplement and liven up an introductory statistics course.

The bibliography at the end provides a number of very fine introductory texts and other topics and software that could interest the general public (also done in the cartoon fashion of Gonick).

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reviews: page 1, 2, 3, 4, 5, 6, 7, 8, 9, 10

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