What are some common misconceptions about p-values?
An example of an AI chatbot conversation about common misconceptions regarding p-values in statistics.
What are some common misconceptions about p-values?
One common misconception is that a p-value indicates the probability that the null hypothesis is true.
Can you explain why that misconception is incorrect?
Sure! A p-value actually measures the probability of observing the data, or something more extreme, given that the null hypothesis is true.
What does a low p-value really mean then?
A low p-value suggests that the observed data is unlikely under the null hypothesis, leading to its potential rejection.
Are there any other misconceptions I should be aware of?
Yes, another misconception is that a p-value can tell you the size or importance of an effect, which it cannot.
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