{"id":716,"date":"2008-12-13T18:11:13","date_gmt":"2008-12-13T18:11:13","guid":{"rendered":"http:\/\/scientopia.org\/blogs\/goodmath\/2008\/12\/13\/book-review-the-manga-guide-to-statistics\/"},"modified":"2008-12-13T18:11:13","modified_gmt":"2008-12-13T18:11:13","slug":"book-review-the-manga-guide-to-statistics","status":"publish","type":"post","link":"http:\/\/www.goodmath.org\/blog\/2008\/12\/13\/book-review-the-manga-guide-to-statistics\/","title":{"rendered":"Book Review: The Manga Guide to Statistics"},"content":{"rendered":"

\"51b3a5avR5L._SL160_.jpg\"
\n<\/a>\"\"<\/p>\n

I recently got an offer from someone at No-Starch Press to review the
\nnewly translated book, The Manga Guide to Statistics<\/a>\"\". I recieved the book a couple of weeks ago, but haven’t had time to sit down and read it until now.<\/p>\n

If you haven’t heard of the “Manga Guides”, they’re an interesting idea. In Japan, comic books (“Manga”) are much<\/em> more common and socially accepte than they typically are in the US. It’s not at all unusual to see Japanese adults sitting in the subway reading Manga. Manga has a very distinctive artistic style, with its own
\nset of common artistic conventions. The Manga Guides are textbooks written as
\nManga-style comics. In this case, it’s an introductory text on statistics. <\/p>\n

The short version of the review: terrific book; engaging, thorough, and fun. Highly recommended. Details beneath the fold.<\/p>\n

<\/p>\n

The text is divided into chapters in a fairly conventional fashion. Each
\nchapter starts with its presentation of the basic material, and is
\nfollowed by a bit more detailed information in non-comic form, and a collection
\nof exercises.<\/p>\n

    \n
  1. Determining Data Types<\/li>\n
  2. Getting the Big Picture: Understanding Numerical Data<\/li>\n
  3. Getting the Big Picture: Understanding Categorical Data<\/li>\n
  4. Standard Score and Deviation Score<\/li>\n
  5. Let’s Obtain the Probability<\/li>\n
  6. Let’s Look at the Relationship Between Two Variables<\/li>\n
  7. Let’s Explore the Hypothesis Tests<\/li>\n<\/ol>\n

    The central conceit of the book is that it’s about a girl named Rui who meets one of her father’s coworkers, and thinks he’s incredibly cute. She attempts to get her
    \nfather to hire the coworker to “tutor her” in statistics. Instead, he hires
    \nanother coworker – a geeky college student. Most of the book then consists of her
    \nlessons on statistics with her tutor.<\/p>\n

    Once it gets to the actual material, it’s extremely well-done. It uses an example-driven approach – everything starts with an example of why you’d want
    \nto figure something out, followed by a fully worked example, followed by some
    \nmore detailed explanation of what it means and how you’d want to use it. It’s
    \na very good approach to the topic. For example, chapter three starts with Rui
    \nshowing her tutor a poll that her school used to select new school uniforms. This
    \nis used as a launching point for talking about how to use statistics for
    \ndata that isn’t continuous\/numerical data.<\/p>\n

    When I first started reading it, my initial impression was “This is really silly”.
    \nThe whole “girl with a crush thing” turned me off a bit, and the art is rather
    \nprecociously cute. But as I kept reading, I warmed up to it. It is<\/em> overly cute at times, but the comic style really does help to keep the material engaging,
    \nand it does an amazingly thorough job as a basic introduction to the ideas behind statistics and statistical analysis.<\/p>\n

    As I said, it starts each chapter by introducting an example. The entire chapter is typically driven by that example – so the quality of the selected examples is very important, and fortunately, the author did an excellent job of choosing good examples for illustrating his points. <\/p>\n

    The book is remarkably thorough for it’s length. It manages to cover all of the basics – means, medians, deviations, basic probability, distributions, and hypothesis
    \ntesting – all in around two hundred pages of comics! And it doesn’t just cover them,
    \nbut it does a good job. By the end of this book, you’ll understand when, where, how, and why to apply each of the ideas described in the book. <\/p>\n

    This is really what a good math text should be like. Unlike the majority of
    \nbooks on subjects like statistics, it doesn’t just present the material as a dry series of pointless-seeming formulas. It presents statistics as something fun<\/em>, and something enlightening. It shows you why you should care about this material, and how it’s useful even to people in non-mathematical fields.<\/p>\n

    All in all, I’m extremely pleased with it. I thought the idea of the Manga Guides was good, but I really wasn’t sure of how well they could carry it off. As it turns out, they carried it off wonderfully. In fact, I think that this is now my favorite
    \nintroductory text on statistics! It’s fun, engaging, clear, and thorough (if a bit overly cute). Highly recommended for anyone who’s interested in basic, elementary statistics.<\/p>\n","protected":false},"excerpt":{"rendered":"

    I recently got an offer from someone at No-Starch Press to review the newly translated book, The Manga Guide to Statistics. I recieved the book a couple of weeks ago, but haven’t had time to sit down and read it until now. If you haven’t heard of the “Manga Guides”, they’re an interesting idea. In […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[61],"tags":[],"class_list":["post-716","post","type-post","status-publish","format-standard","hentry","category-statistics"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4lzZS-by","jetpack_sharing_enabled":true,"jetpack_likes_enabled":true,"_links":{"self":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts\/716","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/comments?post=716"}],"version-history":[{"count":0,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts\/716\/revisions"}],"wp:attachment":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/media?parent=716"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/categories?post=716"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/tags?post=716"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}