I’m a beginning experimental linguist currently enrolled in a frequentist statistics course in my PhD program. I need to be able to use statistical methods to show that my experiments are valid and show real effects.
Could I successfully use Bayesian statistical analysis in lieu of ANOVAs and p-levels in real theoretical work? I have other reasons to want to drop this statistics class (like taking a different class that interests me more), so if learning frequentist statistics in this class is really going to be less useful than learning Bayesian methods on my own, I would love to know that.
Any input, particularly from someone with experience in academics, would be greatly appreciated.
Science papers are surprisingly conformist. If you want to get published, you do it the way everybody else does. If you want to push Bayesian analyses, you are probably better off doing it alongside p values, instead of as a replacement for them.
Do bear in mind, though, that p-values and ANOVAs aren’t wrong. They’re specialized tools that researchers tend to misuse. Having a Bayesian background should help you understand what they are and aren’t suitable for.
I’m a beginning experimental linguist currently enrolled in a frequentist statistics course in my PhD program. I need to be able to use statistical methods to show that my experiments are valid and show real effects.
Could I successfully use Bayesian statistical analysis in lieu of ANOVAs and p-levels in real theoretical work? I have other reasons to want to drop this statistics class (like taking a different class that interests me more), so if learning frequentist statistics in this class is really going to be less useful than learning Bayesian methods on my own, I would love to know that.
Any input, particularly from someone with experience in academics, would be greatly appreciated.
Science papers are surprisingly conformist. If you want to get published, you do it the way everybody else does. If you want to push Bayesian analyses, you are probably better off doing it alongside p values, instead of as a replacement for them.
Do bear in mind, though, that p-values and ANOVAs aren’t wrong. They’re specialized tools that researchers tend to misuse. Having a Bayesian background should help you understand what they are and aren’t suitable for.