It’s not deeply rigorous but it’s correct reasoning in principal.
The scientific and statistical standard interpretation of the null hypothesis is that there’s no relationship between the variables in question. It’s up to the researcher to establish an evidence based argument that the null hypothesis should be rejected in favor of some alternative.
When we “fail to reject” the null hypothesis, we haven’t proved it’s true, we just continue to assume it is until someone proves otherwise.
In this case, the alternate hypothesis is that there’s a correlation between incarceration and crime rates and the null is that no such correlation exists.
It’s not deeply rigorous but it’s correct reasoning in principal.
The scientific and statistical standard interpretation of the null hypothesis is that there’s no relationship between the variables in question. It’s up to the researcher to establish an evidence based argument that the null hypothesis should be rejected in favor of some alternative.
When we “fail to reject” the null hypothesis, we haven’t proved it’s true, we just continue to assume it is until someone proves otherwise.
In this case, the alternate hypothesis is that there’s a correlation between incarceration and crime rates and the null is that no such correlation exists.
As of now, the bulk of the research has failed to find such a relationship https://scholar.google.com/scholar?hl=en&as_sdt=0%2C22&q=correlation+incarceration+crime&btnG=