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J**R
A history of statistics
This book is mostly a brief history of statistics. It gives a high overview of where some statistical methods came from. It doesn’t go into detail about them. Notably, one of the most important topics in statistics, population estimation, if given only about two pages of discussion.
F**S
I Strongly Disagree With the Previous Reviewers
This book is exactly what it says it is, an introduction to statistics. It is meant to attract people to the field rather than drive them away. It is a great review of the history, philosophy, and purpose of statistics, the development of the various statistical concepts and how they relate to real-life problems. I loved the historical parts dealing with the women and men behind the science Given how pervasive and ubiquitous statistics have become in fields of study, work and even play, this book should be a required reading to any novice statistician or anyone whose life and/or work are touched by this very important field. A next great stop would be a book called "The Lady Tasting Tea" by David Salsburg and "The Unfinished Game" by Devlin. If you want to read more I recommend "The Theory that Wouldn't Die" by McGrayne.
A**A
More of a history than a text
Would have appreciated more explanation and practical application notes than histories. Must of the illustrations are comic historical than explanatory.
I**L
Statistic evidence
A great review of the history behind Statistics. Info used in my stats classes.
A**R
Four Stars
Good read and quick delivery for Australia.
D**G
This was a really good book.
As a person with very little background in statistics I found this book to be very informative, mathematically educational, and enjoyable.
L**O
Five Stars
Amazing book
E**H
Avoid this book!
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!
A**R
statistics for the non-statistician
Loved this book - was a clear guide to the history and development of statistics as we know it today . It also explained in simple terms the differences and mathematical underpinnings of the different types of statistical analysis which are available today, and their uses and limitations .Thank you Eileen !
M**M
Rubbish
Rubbish. Utter waste of time.
F**S
Legal para conhecer uma parte interessante da história da estatística
I finished reading today. Liked it. I had higher expectations, but I liked it in the end.Nothing too old, but nothing new either.I also expected a more structured table of contents and something from the more modern part of statistics, especially the development of the last 30+ years with increasing computing power.
V**J
Bad for beginners
Statistics is tough for those who aren’t inclined towards mathematics. This book wasn’t much help to me for understanding the basics of statistics. It feels like my time is wasted.
J**Z
Stories that lead to understanding
Very amusing introduction to the historical and mathematical development of statistics. Full of examples and nicely illustrated. Useful for presentations for medical students (my purpose). Would be perfect if it covered some more topics.
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