File Size: 1984 KB
Print Length: 144 pages
Publisher: W. W. Norton & Company; Reissue edition (January 19, 2010)
Publication Date: December 7, 2010
My problem is the book is too simple. Less verbose with more insights on problematic applications would be good. For example, quoted possibilities for medical maladies frequently necessitate Bayesian concepts that are wrongly interpreted, often poor understanding of false positives/negatives. This Bayesian principle would be a good one to make clear in simple language (graphical explanation is elegant). Then there is also the void of correlation and causation... could be treated better. It's bad enough that rigorous trial and error designs are difficult. Not necessarily understanding the impact of (independent, dependent) variables (or which a multivariate analysis correlation with a huge number of variables can be meaningless) is deadly. Granted, the book was written in 1954 however, likelihood and statistics has long been part of the human equation, and there is a definite need for everyone to have an improved understanding (well stated by other reviewers). I suggest this guide drops short, hence 4* (4* only because it is well written, my tendency lower but wish to be objective).
I read editorial book reviews and 5* and 1-2* superstar reviews before buying. In cases like this should have paid more awareness of the low side comments that on rereading had clues. Buried were sentences I wish I'd seen before buying., Pretty basic but clear illustrations that numbers do not rest... people do with their wrong use of them. Especially relevant today with all the fake news and polling results taken from the major news media to los inform the public for political gain., Question everything you think you know!
This guide is short but packed with large quantity of common sense and great insights.
The author outlines a very healthy skeptical mindset to have before pulling conclusions from statistical evaluation. Although an old publication, it has not lost validity in all these years.
Typically the book provides important tips about which inquiries to ask and which standards to consider when checking data, before taking statistical results at face value, in fact it is a great insight how data can be easily manipulated (consciously or unconsciously) to create and reinforce biases.
" We are flooded by information, but craving for knowledge". The principles in this guide are a great tool to assist you in distinguishing reality from noise, in all spheres of life., Huff's little volume is somewhat dated, yet so current in that he identifies the impressive ways in which truth is misrepresented by means of statistics. Hardly any math is required to understand the ideas he presents, and that is a vital for many readers. Never the less, he discusses basic concepts- mean, median, mode- which are conflated in the most popular mind and allow specious states be made that are not theoretically lies, but are deceptive. Presenting an important part as the whole is the basic method in lying by means of data as presented by the author, and our mind is raised by looking over this little paperback. I assist on my state Board of Education and have seen the techniques Huff warns against used many times in make an effort to move support for specific coverage. I observe that the book is somewhat dated, yet even this has a certain charm as the examples stem from the Eisenhower era and show how little our public discourse is promoting., This is an old publication, but still very valuable today. It shows many of the ways that data can be used to mislead. Everyone should read this book., An old book, but the materials is still very relevant to today's world. It must be required reading for every United states.
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