Introducing Statistics: A Graphic Guide is a small book (c. 6″ x 4″) of 176 pages that supplies a compact history of statistics, both people and concepts, up until the first decades of the 20th century. The text covers the contributions of the significant 19th-century statisticians including Florence Nightingale, Bernouilli, Gauss, Galton, finishing with Karl Pearson, Weldon, Gossett and Fisher.
Embedded in the historical account are clear explanations and helpful examples of key statistical concepts including distributions, sampling, summarizing data, variation, correlation, regression, chi-squared, hypothesis testing, the analysis of variance, and a lot more. So it could provide an excellent resource for introductory statistics, if it were clear at whom exactly the book is aimed. There is no preface to indicate the target audience. An accompanying flyer, but not the cover text, suggests that university students will use it. This would be fine, but as there is no table of contents and locating a particular topic is difficult. There is an effective index, but in my experience students have no idea what an index is for. Navigating the text is actually made more difficult by the large number of drawings, which despite their high quality, do not convincingly assist the text substantially.
There are too many disembodied talking heads, and even sketches of the author! Rightly, illustrations are used to support text explanations, but these instances tend to be in the minority. Graphics, humour and text can be combined effectively, as in Gonick & Smith’s The Cartoon Guide to Statistics (HarperCollins), but the combination is much less successful here.
Also, rather strangely, this introduction to the history of statistics ends around 1925, although this is not entirely clear from the cover text. There is a simple reason – the author is a specialist in the work of Karl Pearson. However, the unwary might conclude nothing had occurred since then (which it has). One crucial positive feature is that this volume is extremely cheap, its online price being about that of a cup of coffee and a sandwich in your local cafe. After the distributor’s cut the publishers are almost giving it away.
So, if you require a cheap, pocket-sized volume with clear, accurate explanations of basic statistical concepts, and you don’t object to an excess of illustrations, then buy it now. A bargain.
Not everything in this book is bad: the historical information is very interesting. (The author has a PhD in the history of science.)
Unfortunately, however, the book is riddled with blunders and misconceptions, obfuscations and inaccuracies.
Consider just one topic: the standard deviation — pretty important when it comes to understanding statistics.
We are told that the standard deviation ‘indicates how widely or closely spread the values are in a set of a data’ (fine so far, apart from the typo of an extra ‘a’), and then that it ‘shows how far each of these individual values deviate from the average’. No: as a single summary figure, the standard deviation cannot possibly give information on ‘each of these individual values’. (That is not its purpose, of course; indeed it almost the exact opposite of its purpose.)
The accompanying graphic carries the information that the ‘standard deviation … corresponds to the moment of inertia … of dynamics’. No: it corresponds to the radius of gyration. And we are told that the moment of inertia is ‘a geometrical property of a beam, and a measure of the beam’s ability to resist buckling or bending’. Oh dear! Clearly the author’s grasp of mechanics is no better than her grasp of statistics.
The formula for the standard deviation is then given — but it is typeset incorrectly!
Next, the standard deviation for a set of data (with mean 8) is calculated (correctly!) as 2.82. The accompanying comment is ‘This means that the average amount of deviation in this set of data is 2.82 units away from the mean value of 8 and that, therefore, there is a small amount of variation in this sample’. There appears to be no explanation of the criterion by which the variation is deemed large or small. Certainly it is not a criterion known to this statistician.
Finally, we have ‘Although the standard deviation indicates to what extent the whole group deviates from the mean, it does not show how variable a particular group is.’ I have read that over and over again and I am at a loss to know what it is trying to say.
I wish I could say that the other statistical concepts in the book fared better than the standard deviation — but they don’t. I can’t resist mentioning the coefficient of variation which is said to be useful in comparing the variability of temperatures in two cities, one set of measurements being in in degrees Celsius and the other in Fahrenheit. This, of course, is a perfect example of when it would *not* be appropriate to use the coefficient of variation — because the mean could be zero and the coefficient of variation would then be infinite.
If you understand anything about statistics this book will infuriate you; if you don’t understand much about statistics the book will hinder not help.
Introducing Statistics: A Graphic Guide
by Eileen Magnello
illustrated by Borin Van Loon
Introducing Statistics: A Graphic Guide
reviewed by Glenn Baggott
http://www.significancemagazine.org/details/review/874191/Introducing-Statistics-A-Graphic-Guide-by-Eileen-Magnello-illustrated-by-Borin-V.html
Introducing Statistics: A Graphic Guide is a small book (c. 6″ x 4″) of 176 pages that supplies a compact history of statistics, both people and concepts, up until the first decades of the 20th century. The text covers the contributions of the significant 19th-century statisticians including Florence Nightingale, Bernouilli, Gauss, Galton, finishing with Karl Pearson, Weldon, Gossett and Fisher.
Embedded in the historical account are clear explanations and helpful examples of key statistical concepts including distributions, sampling, summarizing data, variation, correlation, regression, chi-squared, hypothesis testing, the analysis of variance, and a lot more. So it could provide an excellent resource for introductory statistics, if it were clear at whom exactly the book is aimed. There is no preface to indicate the target audience. An accompanying flyer, but not the cover text, suggests that university students will use it. This would be fine, but as there is no table of contents and locating a particular topic is difficult. There is an effective index, but in my experience students have no idea what an index is for. Navigating the text is actually made more difficult by the large number of drawings, which despite their high quality, do not convincingly assist the text substantially.
There are too many disembodied talking heads, and even sketches of the author! Rightly, illustrations are used to support text explanations, but these instances tend to be in the minority. Graphics, humour and text can be combined effectively, as in Gonick & Smith’s The Cartoon Guide to Statistics (HarperCollins), but the combination is much less successful here.
Also, rather strangely, this introduction to the history of statistics ends around 1925, although this is not entirely clear from the cover text. There is a simple reason – the author is a specialist in the work of Karl Pearson. However, the unwary might conclude nothing had occurred since then (which it has). One crucial positive feature is that this volume is extremely cheap, its online price being about that of a cup of coffee and a sandwich in your local cafe. After the distributor’s cut the publishers are almost giving it away.
So, if you require a cheap, pocket-sized volume with clear, accurate explanations of basic statistical concepts, and you don’t object to an excess of illustrations, then buy it now. A bargain.
Avoid this book! 2011/12/14
by Eldon Nash
http://www.amazon.co.jp/dp/1848310560/ref=as_sl_pd_tf_lc?tag=buckeyethetra-22&camp=243&creative=1615&linkCode=as1&creativeASIN=1848310560&adid=13Y76K6D9Z1QC00BQTNV&&ref-refURL=http%3A%2F%2Fbuckeye.way-nifty.com%2Ftranslator%2F2010%2F04%2Fpost-0089.html
Not everything in this book is bad: the historical information is very interesting. (The author has a PhD in the history of science.)
Unfortunately, however, the book is riddled with blunders and misconceptions, obfuscations and inaccuracies.
Consider just one topic: the standard deviation — pretty important when it comes to understanding statistics.
We are told that the standard deviation ‘indicates how widely or closely spread the values are in a set of a data’ (fine so far, apart from the typo of an extra ‘a’), and then that it ‘shows how far each of these individual values deviate from the average’. No: as a single summary figure, the standard deviation cannot possibly give information on ‘each of these individual values’. (That is not its purpose, of course; indeed it almost the exact opposite of its purpose.)
The accompanying graphic carries the information that the ‘standard deviation … corresponds to the moment of inertia … of dynamics’. No: it corresponds to the radius of gyration. And we are told that the moment of inertia is ‘a geometrical property of a beam, and a measure of the beam’s ability to resist buckling or bending’. Oh dear! Clearly the author’s grasp of mechanics is no better than her grasp of statistics.
The formula for the standard deviation is then given — but it is typeset incorrectly!
Next, the standard deviation for a set of data (with mean 8) is calculated (correctly!) as 2.82. The accompanying comment is ‘This means that the average amount of deviation in this set of data is 2.82 units away from the mean value of 8 and that, therefore, there is a small amount of variation in this sample’. There appears to be no explanation of the criterion by which the variation is deemed large or small. Certainly it is not a criterion known to this statistician.
Finally, we have ‘Although the standard deviation indicates to what extent the whole group deviates from the mean, it does not show how variable a particular group is.’ I have read that over and over again and I am at a loss to know what it is trying to say.
I wish I could say that the other statistical concepts in the book fared better than the standard deviation — but they don’t. I can’t resist mentioning the coefficient of variation which is said to be useful in comparing the variability of temperatures in two cities, one set of measurements being in in degrees Celsius and the other in Fahrenheit. This, of course, is a perfect example of when it would *not* be appropriate to use the coefficient of variation — because the mean could be zero and the coefficient of variation would then be infinite.
If you understand anything about statistics this book will infuriate you; if you don’t understand much about statistics the book will hinder not help.
Avoid!
マンガ 統計学入門―学びたい人のための最短コース
by アイリーン・マグネロ
edited by 神永正博
illustrated by ボリン．ファン・ルーン
translated by 井口耕二