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.

Cohesion—Factor Analysis

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Factor analysis reduces the number of variables in an analysis, and it can do so in a wide variety of ways, each of which means something slightly different from the others. To begin, factor analysis can show the extent to which variables might be viable proxies for each other and might thereby be somewhat redundant. Factor analysis can also show an underlying structure by which items on a survey “hang” together as a group. Many types of factor analysis exist; but regardless of the type, factor analysis seeks to reduce the number of variables by extracting what the original variables have in common into the most parsimonious set that is consistent with how theory suggests the underlying ...

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