Final answer:
Maximum likelihood allows us to estimate the model parameters that make the data the most likely relative to other parameter values. It assumes no prior information on the parameters and provides the most probable values of the distribution.
Step-by-step explanation:
Maximum likelihood allows us to take into account the probability of observing the data given a specific model or hypothesis. It is an optimization process that estimates the model parameters that make the data the most likely relative to other parameter values.
Maximum likelihood assumes no prior information on the parameters and provides the most probable values of the distribution. For example, in ecology research, likelihood-based models can be used to estimate the probability of observing certain ecological data based on expected frequencies.