In most basic probability theory courses your told moment generating functions (m.g.f) are useful for calculating the moments of a random variable. In particular the expectation and variance. Now in most courses the examples they provide for expectation and variance can be solved analytically using the definitions.
Are there any real life examples of distributions where finding the expectation and variance is hard to do analytically and so the use of m.g.f's was needed? I'm asking because I feel like I don't get to see exactly why they are important in the basic courses.