\begin{table}%t4
\caption{\label{table:logitres}Logistic maximum likelihood estimates. }
 \small
 %\centerline
{
 \begin{tabular}{cccc}
 \hline
 \hline 
 Variable & $\hat{\beta}$& t-stat.& ${\cal{P}}$ \\
 \hline
$M_{\star}$  &     0.467 &     0.63 &     0.528  \\
 ${\rm [Fe/H]}$  &      0.415 &     1.39 &     0.164  \\
$T_{\rm eff}$  &     --0.517 &     --0.81 &     0.417  \\
$R_{\star}$  &     0.059 &     0.12 &     0.901  \\
      $P$  &     --0.235 &     --0.32 &     0.746  \\
    $M_{\rm p}$  &      0.329 &     0.35 &     0.726  \\
    $R_{\rm p}$  &      0.305 &     0.90 &     0.370  \\
 $T_{\rm eq}$  &     --0.296 &     --0.46 &     0.648  \\
 $\theta$  &     --0.904 &     --0.58 &     0.563  \\
 \hline 
\end {tabular}}
  Maximum likelihood estimations.\\
 Probability ${\cal{P}}_{\chi^2}= 0.756.$ \\
  $\hat\beta$ is indicative of a correlation with $Y$; ``t-stat'' is the
  the distance in standard deviations from no correlation, and ${\cal{P}}$ represents the probability that the
  model and observations are not significantly different. 
\end{table}