How does the recurring structure of introducing a statistical tool and immediately describing its potential errors and misuses shape the reader’s understanding of statistics as both a valuable and a dangerous instrument?

Compare Wheelan’s use of real case studies and imagined hypotheticals. What determines which examples are used to illustrate concepts? How does Wheelan’s interest in the ethical dimension of statistics affects his use of these two categories of examples?

Construct an argument about Wheelan’s definition of statistical malfeasance. Is it primarily a matter of mathematical error, flawed assumptions, or unethical intent?

Beyond teaching statistical techniques, what kind of critical thinking framework does Wheelan aim to build for the reader?

How does Wheelan rhetorically persuade readers of the superior credibility of randomized controlled trials over quasi-experimental methods like regression discontinuity analysis in his hierarchy of evidence?

In what ways does Naked Statistics function as both a post-mortem on the statistical failures that contributed to the 2008 financial crisis and a forward-looking guide to the methods of causal inference that have come to dominate modern social science?

Consider Wheelan’s complex use of the concept of gut instinct, which he often evokes to explain abstract mathematical concepts through easy-to-grasp analogies, but which he is also dismisses as misleading on questions of probability.

In his shift from technical instruction to social commentary, does Wheelan provide a clear ethical framework for resolving the tension between predictive accuracy and social fairness? Why or why not?