In an increasingly data-driven world, it is more important than ever for students as well as professionals to better understand basic statistical concepts. 100 Questions (and Answers) About Statistics addresses the essential questions that students ask about statistics in a concise and accessible way. It is perfect for instructors, students, and practitioners as a supplement to more comprehensive materials, or as a desk reference with quick answers to the most frequently asked questions.

What Is the Central Limit Theorem, and Why Is It Important?

What Is the Central Limit Theorem, and Why Is It Important?

In question #67, you saw an illustration of what the normal curve looks like, and you will shortly learn how many of the basic concepts underlying descriptive and inferential statistics are based on the shape and the properties of this curve.

But what if the distribution of scores is not normal—whether it be skewed or some other shape? Do these same rules of inference apply? Yes, they do. Because of the central limit theorem, one can apply the rules of inference to almost any distribution of scores.

The central limit theorem proposes that even in a set of scores that is distributed in a non-normal fashion, repeated sampling from the distribution will produce an average ...

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