Lessons in Statistical Thinking by Daniel Kaplan

One of the oft-stated goals of education is the development of “critical thinking” skills. Although it is rare to see a careful definition of critical thinking, widely accepted elements include framing and recognizing coherent arguments, the application of logic patterns such as deduction, the skeptical evaluation of evidence, consideration of alternative explanations, and a disinclination to accept unsubstantiated claims.

“Statistical thinking” is a variety of critical thinking involving data and inductive reasoning directed to draw reasonable and useful conclusions that can guide decision-making and action.

Surprisingly, many university statistics courses are not primarily about statistical reasoning. They do cover some technical methods used in statistical reasoning, but they have replaced notions of “useful,” “decision-making,” and “action” with doctrines such as “null hypothesis significance testing” and “correlation is not causation.” For example, a core method for drawing responsible conclusions about causal relationships by adjusting for “covariates” is hardly ever even mentioned in conventional statistics courses.

These Lessons in Statistical Thinking present the statistical ideas and methods behind decision-making to guide action.

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