# How to interpret p-value during performing any t-tests in R? [duplicate]

What is the meaning of p < 0.05 and p>0.05? How does it effect our choice of hypothesis?

I am new to R world. This p-valve outcome during performing t-tests.. What does it really mean?

• Can you please give some more context and an example? The question is hard to understand without more information. Commented Oct 26, 2022 at 21:29
• @AllanCameron That's kind of the classically wrong explanation of what a p-value is :) Commented Oct 26, 2022 at 21:31
• @BryanKrause I don't doubt you're right, hence my vote to migrate the question over here, though I think my simplified explanation was like a potted version of the first linked answer. What did I get wrong? Commented Oct 26, 2022 at 21:44
• @AllanCameron A p-value tells you how often you'd expect to see a measurement as extreme or more extreme than what you observed if the null hypothesis is true (with the null hypothesis for a two-sample t-test often being "no difference"). It doesn't tell you how likely a hypothesis is to be right or wrong, just about how unusual your data are if you assume the null. en.wikipedia.org/wiki/Prosecutor%27s_fallacy is an example of an important situation where the correct interpretation and your interpretation are in conflict. Commented Oct 26, 2022 at 21:50
• @BryanKrause thanks. I'm sure that's what I meant to say, but I think I wrongly implied that p was the probability of the null given the data, rather than probability of the data given the null. In any case, thanks for clarifying. Commented Oct 26, 2022 at 22:10