\begin{table}%t3
\caption{Results of the Principal Component Analysis.
The first three principal components out of a total of 8 are given in
order of their contribution to the total variance.  The first row
gives the variances of the data along the direction of the
corresponding principal component.  The sum of all the variances is
equal to 8, the number of variables considered in the analysis.  The
variance of each principal component is given as "proportion'' in the
second row and as "the cumulative proportion'' in the third one.  
The rest of the table gives the correlation coefficients between the
original variables and the principal components.  Significant 
correlations are boldfaced, i.e. those ones with
coefficients whose absolute values are $>$$1/ \sqrt 8$ = 0.3536.}\label{table:pca}
%\centering
\par
\begin{tabular}{lrrr}
\hline \hline
 & PC1 & PC2 & PC3 \\
\hline 
Eigenvalue & 2.63 & 1.92 & 1.27 \\
Proportion & 32.9 & 24.1 & 15.9 \\
Cumulative & 32.9 & 57.0 & 72.9 \\
[0.10in]
Variable &  PC1 & PC2 & PC3 \\
\hline 
$p_0$ & $-$0.1771 & {\bf 0.4795} & $-${\bf 0.4297} \\
BI & $-${\bf 0.5065} & 0.2048 & $-$0.1247 \\
DI & $-$0.2440 & $-${\bf 0.5507} & $-$0.1789 \\
$\alpha_{\rm B}$& $-${\bf 0.3867} & 0.0654 & 0.1423 \\ 
\civ ~ ${\srm HREW}$ & $-$0.0014 & {\bf 0.5660} & $-$0.1301 \\
\civ ~ ${\srm HWHM}$ & $-$0.1509 & 0.2636 & {\bf 0.7218} \\
\feii ~ 2400 & $-${\bf 0.4865} & $-$0.1403 & $-$0.3062 \\
$v_{\rm max}$ & $-${\bf 0.4935} & $-$0.1053 & 0.3406 \\
\hline 
\end{tabular}
\end{table}