Darell Huff’s book “How to lie with statistics’ is a very entertaining book that focuses on situations and examples of everyday American life, and the uses and applications of statistics as well as having a good understanding of their meaning when reading statistically reported data, both in scientific articles and in reports of the media. Although the title of the book seems to suggest a critique of ‘eviction’ to the statistics due to its difficulties, misuse and abuse. The reality is that Huff does nothing but highlight the importance of educating the common citizen so that he/she can learn to ‘read’ what statistics really say when it’s published or reported and conversely, learn how to discriminate statistics that are poorly published, incomplete or manipulated. With his simple and practical examples, Huff warns of common and frequent forms of daily abuse of statistics used with intent of deceiving. I learned is that causality can be a manipulated fallacy, intentions or incompetence, when in fact two related variables are caused by a third factor ( not investigated or reported). Huff closed this chapter eight with warning that we must assume a correlation as false when is not clear from the results, or when the author of the research overemphasized it beyond what the data provides. Hard to believe that, despite its mathematical basis, statistics are both an art and a science, and many misinterpretations are possible with the limits of your jurisdiction (pg. 117).I was frustrated with the lack of complexity (it does not go past confidence intervals) and the illustrations instead of images of the news articles, financial statements, and averages he’s calculating, but the books message and lesson on sampling bias are priceless.. It can be long read because his writing voice is old-school, but if you want to be brilliant at the basics this book is the perfect book.Statistic are extremely attractive to a civilization fascinated by facts and number, these methods are used to cause sensation, distort, confuse the public. The outcome of statistical research are crucial because it provide information on patterns raging from social, economic, opinion polls and censuses; the real problem here is honesty and precision, readers take at face value the information being provided. In the end, the results are nothing more than numbers and without any indication of averages and relationships, it is hard to interpret. Darell Huff presents an entertaining text that give examples, that although they may seem obvious, we usually pass over and take as valid if we are not in critical mode. Many times it is more important to know the distribution, which is almost always more unequal than average. To me it seems an interesting, quick and easy reading book that manages to produce reflection from the accepted point of view of quantification.