A strong course in applied statistics should cover basic hypothesis testing, regression, statistical power calculation, model selection, and a statistical programming language like R. Or at the least, the course should mention that these concepts exist—perhaps a full mathematical explanation of statistical power won’t fit in the curriculum, but students should be aware of power and should know to ask for power calculations when they need them. Sadly, whenever I read the syllabus for an applied statistics course, I notice it fails to cover all of these topics. Many textbooks cover them only
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