Monthly Archives: November 2013

Understanding p-values via simulations

As I mentioned in an earlier post, p-values in psychological research are often misunderstood. Ask students (and academics!) what the definition of the p-value is and you will likely get many different responses. To jog your memory, the definition of the p-value is the probability of observing a test statistic as extreme—or more extreme—than the one you have observed, assuming the null is true. But, even with this definition in hand, many struggle to conceptualise what the p-value reflects. In this blog post, I take inspiration from a lovely paper I have recently read that advocates using computer simulation to understand the p-value. Continue reading

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