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1.
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In the JMP Home Window, select File > New > Script. This opens a new script window.
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dt = New Table( "Sales Model" );
dt << New Column( "Unit Sales", Values( {1000, 2000} ) );
dt << New Column( "Unit Price", Values( {2, 4} ) );
dt << New Column( "Unit Cost", Values( {2, 2.5} ) );
dt << New Column( "Revenue",
Formula( :Unit Sales * :Unit Price )
);
dt << New Column( "Total Cost",
Formula( :Unit Sales * :Unit Cost + 1200 )
);
dt << New Column( "Profit",
Formula( :Revenue - :Total Cost ),
Set Property( "Spec Limits", {LSL( 0 )} )
);
Profiler(
Y( :Revenue, :Total Cost, :Profit ),
Objective Formula( Profit )
);
to run the script. Alternatively, you can select Ctrl-R.The script creates the data table in Figure 8.24 with some initial scaling data and stores formulas into the output variables. It also launches the Prediction Profiler.
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5.
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–
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Unit Sales is Uniform with Lower limit 1000 and Upper limit 2000.
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–
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Unit Price is Fixed at 3.
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–
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Unit Cost is Normal with mean of 2.25 and standard deviation of 0.1.
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7.
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Click the Simulate button.
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Note: Your numbers might differ from those shown in Figure 8.26 due to the random draws in the simulation.
It appears that the models are unlikely to be profitable. By putting a lower specification limit of zero on Profit, the defect report tells you that the probability of being unprofitable is 62%.
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8.
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Change the fixed value of Unit Price to 3.25.
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9.
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Click the Simulate button.
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