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.

Data—Measurement

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  • Perceivable
  • Describable
  • Scores

If you can perceive it, you can measure it. A measurement is an assigned value for a single characteristic. The way a characteristic is captured and, therefore, the way its data should be interpreted determine the measure being used to address the question at hand. Some measures are more accurate than others. Perfect measurement exists only in fantasy; we do the best we can.

Good measurement not only is sufficiently accurate but also places its objects into mutually exclusive categories or scores (or “codes”). Some measures divide people into categories, such as gender. Other measures are more abstract continua, such as perception scales that ask the extent to which a respondent agrees with a statement. Regardless of the type of measurement, sufficient accuracy ...

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