R Init();
dt = Open( "$SAMPLE_DATA/Big Class.jmp", invisible );
R Send( dt ); // send the opened data table represented by dt to R;
R Submit( "print( dt )" );
R Term();
R Init();
R Submit(
	"
	L3 <- LETTERS[1:3]
	d <- data.frame(cbind(x=1, y=1:15), Group=sample(L3, 15, repl=TRUE))
"
);
R Get( d ) << NewDataView;
R Term();
R Init();
R Submit( "\[plot(function(x) dnorm(x), -5, 5, main = "Normal(0,1) Density") ]\" );
picture = R Get Graphics( "png" );
New Window( "Picture", picture );
Wait( 10 );
R Term();
R Init();
X = J( 2, 2, 1 );
R Send( X );
R Submit(
	"
	X                                     #Prints X to the log
	Y <- matrix(1:4, nrow=2, byrow=TRUE)  #Makes a 2x2 matrix object Y
	Y                                     #Prints Y to the log
	Z <- X + Y                            #Matrix object Z is addition of X and Y
"
);
Z = R Get( Z );
R Term();
Show( Z );
See the file JMPtoR_bootstrap.jsl in the sample scripts folder for an example script.
The boot package in R is used to call the boot() function and the boot.ci() function to calculate the sample statistic for each bootstrap sample and the bootstrap confidence interval.