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.

Differences—t Tests and Analysis of Variance

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  • Departures in means
  • Separation in groups
  • The importance?

Much of statistics looks for group differences in means, usually the arithmetic averages. For differences between two measures for one group (paired) or in one measure for two groups (independent), t tests often are used. Robust and available in a surprisingly wide array of software, t tests are a mainstay of action research (i.e., local research on local problems). These tests are also found in some very high-stakes research. Simple and common do not mean unworthy of use in high-profile areas. Simple can be elegant and powerful when properly applied.

When the number of measures or groups increases, tests for differences in means get a bit more complicated and are referred to as ...

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