Script that generates the c++ simulation file and R script files, which is then compiled and run.

run.sh

#!/bin/bash

cat << EOF > sim.cpp
#include <random>
#include <vector>
#include <fstream>
#include <algorithm>

int main()
{
	std::default_random_engine random_engine(std::random_device{}());
	double median = 50;
	double std_dev = 35;
	std::normal_distribution<double> distribution(median, std_dev);
	//lambda returns a normally distributed random variable
	auto normal_dist = [&random_engine,&distribution](){return distribution(random_engine);};

	const size_t num_tuts = 10;
	const size_t simulation_runs = 1000000;

	//simulation for healthy students
	std::ofstream healthy_students("healthy_students.txt");
	for(size_t i = 0; i!=simulation_runs; ++i)
	{
		std::vector<double> student(num_tuts);//all 10 marks for a student
		generate(student.begin(), student.end(), normal_dist);//gnerate 10 normally distributed scores with median 50% and std_dev 30
		student.erase(std::min_element(student.begin(),student.end()));//discard the lowest score, so that 9/10 marks count
		double sum = std::accumulate(student.begin(), student.end(), 0.0);
		double average = sum/student.size();
		healthy_students << average << std::endl;		
	}

	//simulation for sick students that missed 1 tut
	std::ofstream sick_students("sick_students.txt");
	for(size_t i = 0; i!=simulation_runs; ++i)
	{
		std::vector<double> student(num_tuts-1);//student was sick, only does 9
		generate(student.begin(), student.end(), normal_dist);//generate only 9
		//student.erase(std::min_element(student.begin(),student.end()));//dont discard the lowest score since only 9 tuts have been written
		double sum = std::accumulate(student.begin(), student.end(), 0.0);
		double average = sum/student.size();
		sick_students << average << std::endl;		
	}
}
EOF

cat << EOF > generate_stats.R
healthy_student = scan("healthy_students.txt")
sick_student = scan("sick_students.txt")
png(filename="healthy_student.png")
plot(main="Best 9/10 scoring policy for healthy vs sick students",density(healthy_student),col="green",xlab="Final Score%",ylab="Density")
lines(density(sick_student),col="red")
legend("topright",c("Healthy student","Sick student"), col=c('green','red'),lty=1)
dev.off()

print("Summary statistics for healthy students")
summary(healthy_student)
print("Summary statistics for sick students")
summary(sick_student)
EOF

g++-5 -std=c++14 sim.cpp -o sim
./sim
Rscript generate_stats.R