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Frequentist methods are unintuitive and seemingly arbitrary to a beginner (hypothesis testing, 95% confidence, p=0.05). Bayesian methods are more intuitive, an
by wenc 1y ago
Frequentist methods are unintuitive and seemingly arbitrary to a beginner (hypothesis testing, 95% confidence, p=0.05).
Bayesian methods are more intuitive, and fit how most be reason when they reason probabilistically. Unfortunately Bayesian computational methods are often less practical to use in non-trivial settings (usually involves some MCMC).
I'm a Bayesian reasoner, but happily use frequentist computation methods (max likelihood estimation) because they're just more tractable.
- jampekka 1y agop-value testing is problematic, but frequentist CIs typically map to credible intervals with uninformative priors. In practice in Bayesian analyses tend to use so weak priors that they are essentially uninformative. Maximum likelihood also tends to be equivalent to MAP with uninformative priors. I find a lot of Bayesian analysis is a bit of cargo culting and frequentist/ML formulations are dismissed with tribalism.
- porridgeraisin 1y agoI'm familiar with hypothesis testing, MCMC, and MLE. Can you explain how they are bayesian or frequentist?