What I currently understand about the P-value is that, if the null hypothesis were true, the P-value is the probability of getting a value of the sample test statistic that is at least as extreme as the one found from my sample data.
What I don't understand is, if I have a two-tailed test and I am assuming my null hypothesis were true (for example hypothesizing that my mean is equal to 2) and my P-value (probability of obtaining extreme values further from 2) is very low, wouldn't that favour my null hypothesis because the probability of obtaining extreme values that are further from the hypothesized mean of 2 is lower?
Why is it that the lower the P-value, the stronger evidence I have to reject my null hypothesis?
Please let me know where I have gone wrong in my understanding.