likelihood-based inference

Likelihood-based inference is a statistical method used to make conclusions about a population based on observed data. It involves calculating how likely different possible values of an unknown parameter are, given the data collected. The parameter value that makes the observed data most probable is called the maximum likelihood estimate. This approach helps statisticians identify the most plausible explanations for the data and quantify uncertainty, guiding decisions and predictions with a solid foundation in the observed evidence.