Here are 3 ways to do this
Names Default To Here( 1 );
dt =
// Open Data Table: Big Class.jmp
// → Data Table( "Big Class" )
Open( "$SAMPLE_DATA/Big Class.jmp" );
nw = New Window( "The Output",
dis = dt << Distribution(
Stack( 1 ),
Continuous Distribution(
Column( :height ),
Horizontal Layout( 1 ),
Vertical( 0 ),
Process Capability( 0 )
),
Continuous Distribution(
Column( :weight ),
Horizontal Layout( 1 ),
Vertical( 0 ),
Process Capability( 0 )
)
);
biv = dt << Bivariate( Y( :weight ), X( :height ), Fit Line( {Line Color( {212, 73, 88} )} ) );
);
Names Default To Here( 1 );
dt =
// Open Data Table: Big Class.jmp
// → Data Table( "Big Class" )
Open( "$SAMPLE_DATA/Big Class.jmp" );
dis = dt << Distribution(
Stack( 1 ),
Continuous Distribution(
Column( :height ),
Horizontal Layout( 1 ),
Vertical( 0 ),
Process Capability( 0 )
),
Continuous Distribution(
Column( :weight ),
Horizontal Layout( 1 ),
Vertical( 0 ),
Process Capability( 0 )
)
);
biv = dt << Bivariate( Y( :weight ), X( :height ), Fit Line( {Line Color( {212, 73, 88} )} ) );
nw = New Window( "The Output" );
Names Default To Here( 1 );
dt =
// Open Data Table: Big Class.jmp
// → Data Table( "Big Class" )
Open( "$SAMPLE_DATA/Big Class.jmp" );
dis = dt << Distribution(
Stack( 1 ),
Continuous Distribution(
Column( :height ),
Horizontal Layout( 1 ),
Vertical( 0 ),
Process Capability( 0 )
),
Continuous Distribution(
Column( :weight ),
Horizontal Layout( 1 ),
Vertical( 0 ),
Process Capability( 0 )
)
);
biv = dt << Bivariate( Y( :weight ), X( :height ), Fit Line( {Line Color( {212, 73, 88} )} ) );
report(dis) << journal;
report(biv) << journal;
Jim