If you have different grouping variables, you can use
Make combined data table :
![hogi_0-1691148553384.png hogi_0-1691148553384.png](https://community.jmp.com/t5/image/serverpage/image-id/55573iBEDD30CB9F3A7450/image-size/medium?v=v2&px=400)
To get the estimates back to the original data table, you can use Tales/Update.
For the second question: It's a strength of Jmp to start on row/column level - then you can add several levels of complexity and make very complicated analyses. Spreadsheet tools which start on cell level fail to get there
JMP is Not a Spreadsheet
But if you just want to calculate "something" , instead of storing the result in a column you can store it in a variable or matrix.
example: use Summarize instead of Tables/Summary.
Names Default To Here( 1 );
dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
myFit = dt << Fit Model( Y( :weight ), By( :sex ), Effects( :height ), Run() );
fitEstimates = Report( myFit[1] )["Response weight sex=F", "Whole Model",
"Parameter Estimates", Table Box( 1 )] << Make Combined Data Table;
sideBySide = fitEstimates << Summary(
Group( :sex ),
Mean( :Estimate ),
Subgroup( :Term ),
statistics column name format( "column" )
);
dt << Update(
With( sideBySide ),
Match Columns( :sex = :sex ),
Add Columns from Update Table( :"Estimate, height"n, :"Estimate, Intercept"n ),
Replace Columns in Main Table( None )
);