What are some common misconceptions about p-values?

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's misleading?

Sure! A p-value actually measures the probability of observing the data, or something more extreme, given that the null hypothesis is true.

What about the idea that a p-value below 0.05 means the results are practically significant?

That's another misconception! A p-value below 0.05 indicates statistical significance, but it doesn't imply practical significance or importance.

How should researchers interpret p-values then?

Researchers should consider p-values in the context of the study, including effect sizes and confidence intervals, rather than relying solely on a threshold.