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The book is a brief, breezy illustrated volume outlining the misuse of statistics and errors in the interpretation of statistics, and how errors create incorrect conclusions. In the 1960s and 1970s, it became a standard textbook introduction to the subject of statistics for many college students.
Huff is credited with introducing statistics to a generation of college and high-school students through clear writing and amusing anecdotes, even though he had no formal training in statistics. His most famous book, How to Lie with Statistics , was "possibly the most popular book on statistics ever published". [ 2 ]
The source is a subject matter expert, not a statistics expert. [6] The source may incorrectly use a method or interpret a result. The source is a statistician, not a subject matter expert. [7] An expert should know when the numbers being compared describe different things.
As AI has made fake content much easier to produce, a growing number of American teenagers say they are being misled by AI-generated photos, videos or other content on the internet, a new study shows.
In statistics, a misleading graph, also known as a distorted graph, is a graph that misrepresents data, constituting a misuse of statistics and with the result that an incorrect conclusion may be derived from it. Graphs may be misleading by being excessively complex or poorly constructed.
How Not to Be Wrong explains the mathematics behind some of simplest day-to-day thinking. [4] It then goes into more complex decisions people make. [5] [6] For example, Ellenberg explains many misconceptions about lotteries and whether or not they can be mathematically beaten.
The origin of the phrase "Lies, damned lies, and statistics" is unclear, but Mark Twain attributed it to Benjamin Disraeli [1] "Lies, damned lies, and statistics" is a phrase describing the persuasive power of statistics to bolster weak arguments, "one of the best, and best-known" critiques of applied statistics. [2]
The Signal and the Noise: Why So Many Predictions Fail – but Some Don't is a 2012 book by Nate Silver detailing the art of using probability and statistics as applied to real-world circumstances. The book includes case studies from baseball, elections, climate change, the 2008 financial crash , poker, and weather forecasting.