Given your intention, it might be better to look at 'Analyze > Fit Y By X'.
This script:
dt = Open("$SAMPLE_DATA/Big Class.jmp");
biv = dt << Bivariate(
Y( :height ),
X( :weight ),
GroupBy( :sex ),
FitLine(),
FitPolynomial(2)
)
will produce output like this:
![Screenshot 2020-05-22 at 16.59.24.png Screenshot 2020-05-22 at 16.59.24.png](https://community.jmp.com/t5/image/serverpage/image-id/24132i968FD2AE97213F6F/image-size/large?v=v2&px=999)
and there are lots of additional customizations you could use.