John Edward Kolassa has written:

'Topics in series approximations to distribution functions'

'Series approximation methods in statistics' -- subject(s): Mathematical statistics, Asymptotic distribution (Probability theory), Edgeworth expansions, Asymptotic theory

The domain of the Normal distribution is the whole of the real line. As a result the horizontal axis is asymptotic to the Normal distribution curve. The curve gets closer and closer to the axis but never, ever reaches it.

Yes.

Think of a function that starts at the origin, increases rapidly at first and then decays gradually to an asymptotic value of 0. It will have attained its asymptotic value at the start.

For example, the Fisher F distribution, which is often used, in statistics, to test the significance of regression coefficients. Follow the link for more on the F distribution.

A. W. van der Vaart has written:

'Asymptotic statistics' -- subject(s): Mathematical statistics, Asymptotic theory

'Weak convergence and empirical processes' -- subject(s): Stochastic processes, Convergence, Distribution (Probability theory), Sampling (Statistics)

Peter D. Miller has written:

'Applied asymptotic analysis' -- subject(s): Asymptotic theory, Differential equations, Integral equations, Approximation theory, Asymptotic expansions