This Second Edition of The Tao of Statistics: A Path to Understanding (With No Math) provides a reader-friendly approach to statistics in plain English. Unlike other statistics books, this text explains what statistics mean and how they are used, rather than how to calculate them. The book walks readers through basic concepts as well as some of the most complex statistical models in use. The Second Edition adds coverage of big data to better address its impact on p-values and other key concepts; material on small data to show readers how to handle data with fewer data points than optimal; and other new topics like missing data and effect sizes. The book’s two characters (a high school principal and a director of public health) return in the revised edition, with their examples expanded and updated with reference to contemporary concerns in the fields of education and health.

Prove—No, Falsify

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Statistics do not prove anything. Statisticians gave up on that idea right from the start, or close to it. Why? Simply put, statistics are based on probability (from data from samples). Being based on probability and probabilities always being above 0% and below 100% (even if by a minuscule amount), statistics offer no absolute guarantees. Billions of supporting examples for absolute truth are outweighed by a single exception. Finding an additional example that proves something is really just finding another supporting case, not proof. So, in statistics, we can only try to disprove or falsify. In a very real sense, we try to find, in some way, the exceptions. When involved with statistics, absolutes tend to have glass ...

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