As the title says, my question is can the null hypothesis ($H_0$) be more true than the alternative hypothesis ($H_1$) or vice versa?
For example, if the statistical power is really high (extremely let us say $0.99$) then by the definition of statistical power, the type 2 error is $0.01$, which means that we will reject $H_1$ (false null hypothesis) almost always, i.e., $H_0$ is more likely to be true.
But does it mean that $H_0$ is more true than $H_1$? It sounds a bit odd to me, so I ask this question here (sorry if this question is not a proper question in here).
If we cannot say "$H_0\;/\;H_1$ is more true than $H_1\;/\;H_0$", can you explain why we can't say this?