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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Straight ANOVA is used when there are more than two groups and no “side” conditions needed to “adjust” the results so that the groups can be justifiably compared. In other words, the groups start off sufficiently equivalent to justify a later comparison on that once-equal trait. Remember, side conditions generally are statistical accommodations of plausible confounds needed to justify a fair comparison across groups when they are not initially equivalent. When possible, it is worth your while to work harder to set up the project so that statistical adjustments are not needed, or at least fewer of them are needed.

One way to think of straight ANOVA, as mentioned earlier, is as a multiple group t test. The reason ...

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