The article explores how information geometry can help us understand classical Cramer-Rao type inequalities. By using Eguchi's theory to create geometric structures from a divergence function and then applying Amari-Nagoaka's theory, the researchers derived various CR type inequalities. These include the classical deterministic CR inequality based on Kullback-Leibler divergence, as well as other versions like the $\alpha$-CR inequality and Bayesian CR inequality. The researchers show that these inequalities can be generalized and extended to different scenarios using various divergence functions.