I watched this video on Fisher Information and it is mentioned that in Taylor series expansion of the likelihood function the second derivative is parabola which is not a good approximation and a better approximation is second derivative of log of likelihood function which is gaussian.
Question: Why gaussian (second derivative of log of likelihood) is a better approximation then parabola (second derivative of likelihood)?