\begin{table}%t6
\caption{\label{tabfitsb1}Fits to the data ($b = 1$).} 
\small%\centerline
 {
\begin{tabular}{lrrrr}         
\hline\hline                  
%&&&& \\[-8pt]
Relationship & Slope & Y intercept & $\chi^2$ & Corr.? \\
\hline
$T$ vs. 1 + 
$z$            &$      -3.20   \pm     0.4             $&$     9.5     \pm 
   0.8     $&      113.9   &Y \\
Log $T$ vs. Log (1 + 
$z$)  &$      -1.90   \pm     0.3             $&$     1.12    \pm     0.07 
  $&      131.5   &Y     \\
$T$ vs. $r$              &$      -3.40   \pm     2.5     \times 10^{-3}$ 
&$      3.1     \pm     0.5     $&      255     &N \\
Log $T$ vs. Log 
$r$      &$      -0.15   \pm     0.12            $&$     1       \pm 
0.3     $&      253.1   &N \\
$E_{\rm T}$ vs. 1 + 
$z$          &$      3.50    \pm     0.6             $&$     -2.7    \pm 
1       $&      113.7   &Y \\
Log $E_{\rm T}$ vs. Log (1 + 
$z$)        &$      1.90    \pm     0.3             $&$     0.11    \pm 
0.07    $&      131.5   &Y \\
$E_{\rm T}$ vs. $r$            &$      1.00    \pm     3       \times 10^{-3}$ 
&$      2.7     \pm     0.4     $&      171.3   &N
\\
Log $E_{\rm T}$ vs. Log 
$r$            &$      0.15    \pm     0.12            $&$     0.3     \pm 
     0.3     $&      253.1   &N     \\
$n_{\rm a}$ vs. $r$           &$      -5.00   \pm     1       \times 10^{-6}$ 
&$      0.002   \pm     0.003   $&
300.9
  &N \\
Log $n_{\rm a}$ vs.  Log 
$r$          &$      -1.38   \pm     0.14            $&$     0.3     \pm 
   0.3     $&      328.3   &Y \\
Log $n_{\rm a}$ vs.  Log (1 + 
$z$)      &$      -1.60   \pm     0.6             $&$     -2.27   \pm 
0.17    $&      760.3   &N \\
$v/c$ vs.        $r$      &$      7.10    \pm     1.1     \times 10^{-4}$ 
&$      0.02    \pm     0.01    $&
572.8
  &N \\
Log $v/c$ vs. Log 
$r$     &$      0.54    \pm     0.12            $&$     -1.9    \pm 
0.3     $&      827.6   &N \\
$v/c$ vs. 1 + 
$z$           &$      0.10    \pm     0.03            $&$     -0.07   \pm 
  0.05    $&      823.7   &N \\
Log $v/c$ vs. Log (1 + 
$z$)         &$      1.80    \pm     0.3             $&$     -1.24   \pm 
0.09    $&      771.5   &N
  \\
$L_j$ vs. 
$r$           &$      0.04    \pm     0.03            $&$     15      \pm 
    5       $&      873.8   &N \\
Log $L_j$ vs. Log 
$r$           &$      0.50    \pm     0.2             $&$     0.4     \pm 
    0.5     $&      2072    &N \\
$L_j$ vs. 1 + 
$z$         &$      44.00   \pm     10              $&$     -50     \pm 
17      $&      690.5   &N \\
Log $L_j$ vs. Log (1 + 
$z$)        &$      4.70    \pm     0.5             $&$     0.44    \pm 
0.13    $&      933.1   &N \\
\hline                                    
\end{tabular}}
\medskip
The best fits to the radio source relationships for $b = 1$. Column~1: the relationship. $v/c$~is the lobe expansion velocity, $r$~is the core-hotspot separation, $L_j$ ($\times 10^{44}$~erg~s\mone) is the beam power, $n_{\rm a}$ ($\times 10^{-3}$~cm \mthree) is the ambient density, $T$~is the source
lifetime, and $E_{\rm T}$~is the total energy.  Column~2: the best fit slope. Column~3: the best fit Y
intercept. Column~4: the $\chi^2$ for 60~points and 58~degrees of freedom. Column~5: is there a correlation? The uncertainty of the best fit parameter is multiplied by $\sqrt{(\chi^2/58)}$ to obtain the normalized uncertainty in the best fit parameter, and this is compared with the value of the best fit parameter to determine whether the correlation is significant.
\end{table}