Why: To find the Maximum Likelihood parameters of a statistical model if the equations cannot be solved directly. Typically these models involve latent variables (apart from unknown parameters and known observations).

Why latent variables?

• Missing data values.
• Model can be formulated more simply by assuming the existence of further unobserved data points. Eg: Mixture models can be represented more simply by assuming that each observed data point has a corresponding latent variable corresponding to its mixture component.