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.

Mistakes—Error

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  • Ambiguity and approximation
  • Cornerstones for existence
  • Truth pokes through the middle

Error takes three basic forms in statistics: sampling error, measurement error, and estimation error. Sampling error is the degree to which the parent population is not faithfully represented by the sample. Measurement error is the amount of the observed score that is considered random noise and not part of the measurement. Estimation error is the window surrounding statistical estimates that indicates the likely range for those values, given the data at hand.

Sampling error is reduced with scientific sampling techniques and larger samples. Measurement error is reduced with strategically designed, psychometrically assessed, repeated measures designs. Estimation error is reduced with larger samples and better models.

Errors of measurement tend to cancel with multiple measurements. Although measurement ...

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