  In a recent paper we have studied the redshift power spectrum $P^S(k,\mu)$ in
three CDM models with the help of high resolution simulations. Here we apply
the method to the largest available redshift survey, the Las Campanas Redshift
Survey (LCRS). The basic model is to express $P^S(k,\mu)$ as a product of three
factors P^S(k,\mu)=P^R(k)(1+\beta\mu^2)^2 D(k,\mu). Here $\mu$ is the cosine of
the angle between the wave vector and the line of sight. The damping function
$D$ for the range of scales accessible to an accurate analysis of the LCRS is
well approximated by the Lorentz factor D=[1+{1\over
2}(k\mu\sigma_{12})^2]^{-1}. We have investigated different values for $\beta$
($\beta=0.4$, 0.5, 0.6), and measured $P^R(k)$ and $\sigma_{12}(k)$ from
$P^S(k,\mu)$ for different values of $\mu$. The velocity dispersion
$\sigma_{12}(k)$ is nearly a constant from $k=0.5$ to 3 $\mpci$. The average
value for this range is $510\pm 70 \kms$. The power spectrum $P^R(k)$ decreases
with $k$ approximately with $k^{-1.7}$ for $k$ between 0.1 and 4 $\mpci$. The
statistical significance of the results, and the error bars, are found with the
help of mock samples constructed from a large set of high resolution
simulations. A flat, low-density ($\Omega_0=0.2$) CDM model can give a good fit
to the data, if a scale-dependent special bias scheme is used which we have
called the cluster-under-weighted bias (Jing et al.).
