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.


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  • A suspect was captured
  • His conviction assured
  • While safely at home
  • The real thief sipped tea

How often have we read findings from one research project, only to find exactly the opposite in print only a few weeks or months later? The reason often is confounds. Confounds are variables that might really be responsible for variation in the data that interests us but whose effect has not been accommodated. That is to say, a confound is a variable that is related to both the dependent variable and the independent variable of interest but whose influence has not been ruled out, or accommodated.

Three ways exist to accommodate potential confounds. The first and best is through the research design, where a good design all but precludes plausible confounds. ...

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