After going through this module, students should be familiar with basic skills in C++ programming, including the structure of a basic program, variable types, scope, functions (and function overloading), control structures, and the standard template library.

• Hello world
• Variable types
• Strings
• Boolean logic
• Scope of variables
• Introduction to functions
• Arguments to main
• Control structures (if/then/else, while, for loops)
• Functions, pass by value
• Functions, pass by reference
• Overloading functions
• The standard template library: vectors
• Vectors in multi-dimensions
• Parsing data from comma delimited files
• Makefiles
• Introduction to classes and objects

So far in this course we have used R to explore methods related to fitting model parameters to data (in particular, we explored the Simplex method for parameter estimation).  As we’ve shown, parameter estimation can be a very computationally intensive process.

When you use R, it gives you a prompt, and waits for you to input commands, either directly through the command line, or through an R script that you source.  Because R is a non-compiled language, and instead interprets code step-by-step, it does not have the ability to optimize calculations by pre-processing the code.

In contrast, compiled programming languages like C, java, or C++ (to name just a few) use a compiler to process the code, and optimize the computational algorithms.  In fact, most compilers have optional arguments related to the level of optimization you desire (with the downside that the optimization process can be computationally intensive).  Optimized code runs faster than non-optimized code.

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