  We investigate the random eigenvalues coming from the beta-Laguerre ensemble
with parameter p, which is a generalization of the real, complex and quaternion
Wishart matrices of parameter (n,p). In the case that the sample size n is much
smaller than the dimension of the population distribution p, a common situation
in modern data, we approximate the beta-Laguerre ensemble by a beta-Hermite
ensemble which is a generalization of the real, complex and quaternion Wigner
matrices. As corollaries, when n is much smaller than p, we show that the
largest and smallest eigenvalues of the complex Wishart matrix are
asymptotically independent; we obtain the limiting distribution of the
condition numbers as a sum of two i.i.d. random variables with a Tracy-Widom
distribution, which is much different from the exact square case that n=p by
Edelman (1988); we propose a test procedure for a spherical hypothesis test. By
the same approximation tool, we obtain the asymptotic distribution of the
smallest eigenvalue of the beta-Laguerre ensemble. In the second part of the
paper, under the assumption that n is much smaller than p in a certain scale,
we prove the large deviation principles for three basic statistics: the largest
eigenvalue, the smallest eigenvalue and the empirical distribution of
eigenvalues, where the last large deviation is derived by using a non-standard
method.
