The likelihood school affirms that likelihood ratios are the basic tool of inference. The likelihood is the (conjugate) probability of observed data D, conditional on the hypothesis A being true. Given two hypotheses, A and B, it is meaningless to assess evidence except by comparing the evidence favoring hypothesis A over hypothesis B….
“Classical” statistical inference in medicine is usually synonymous with frequentist inference, the central element of which is the null hypothesis significance testing (NHST). Even though that was not its original intent, NHST is in practice used to evaluate the evidence for or against a hypothesis, due to confusion in mixing Fisher’s approach with that of…
The difference between probability and likelihood is central, among others, to understanding MLE. Randy Gallistel has posted a succinct treatment of this topic: The distinction between probability and likelihood is fundamentally important: Probability attaches to possible results; likelihood attaches to hypotheses [my emphasis]. Explaining this distinction is the purpose of this first column. Possible results…
Welcome to staRt, the introductory R Cookbook. I am Monsieur Gustave H, your concierge. On this corner of the internet I am storing for my own future reference random tidbits, and the occasional whole recipe, about data science and statistics using the programming language R in the R Studio environment. There will be the occasional…
