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.

Representativeness—Samples

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  • Sampling’s goal?
  • Close enough
  • Resources rule

Sampling is a statistical response to limited resources, an efficient way of estimating values (i.e., making educated guesses) for large groups. Several families of sampling techniques exist; each is designed differently to handle varying conditions for optimizing resource use. A few general rules apply across the various sampling designs:

  • More representative samples yield better results.
  • All else being equal, larger samples yield better results.
  • Larger samples cannot make up for a poor sampling plan or for poorly executing a good plan.

For example, there is the story of the U.S. Census conducted in one major city that had a “corner problem” with undercounts as a result. The door-to-door interviewers were paid by the number of streets covered. Buildings that were on the corner ...

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