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.

# No Difference—The Null Hypothesis

### No Difference—The Null Hypothesis

• “No difference,” I declare
• The starter’s pistol sounds
• Can a difference be found?
• In time?

The null hypothesis puts the question of interest to the statistical test. It is normally a no-difference, declarative statement, such as “The average math scores from two different teaching methods are the same” (i.e., are not different). The alternative hypothesis usually is the opposite: The two teaching methods result in different average test scores. The beauty of this approach is that in the end, only one of two statements is left standing: (1) The sets of measures are not statistically different and are, therefore, the same; or (2) the sets of measures are likely to have come from samples of different populations because they are statistically different. The ...

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