2. A Brief Introduction to R
We will be using the R statistical computing language to facilitate teaching the concepts and methods of formal demography. R provides a convenient environment for manipulating lists of numbers (called vectors) and arrays of numbers (called matrices). While there are many more common applications that will allow you to manipulate lists of numbers (e.g., spreadsheet programs), R also allows for the easy calculation of a number of quantities that are of vital interest to population biologists. R also provides a powerful environment for performing numerical simulations, an important tool in the population biologist's arsenal. What R lacks in apparent user-friendliness, it more than makes up for in power. While there is certainly a learning curve associated with developing the skills you will need to perform analyses in R, this is really true of any software package that you will use. Once you acquire some of the basics, you will find that using R is logical and simple. A couple questions naturally arise: (1) What is R? and (2) Why use it instead of, say, a spreadsheet application which is more typically used in introductory demography courses?
What is R?
* R is numerical software
* R is a "dialect" of the S statistical programming language
* R is free
* R is state-of-the-art in statistical computing.
It is what many (most?) research statisticians use in their work.
Why Use R?
R has a number attractive features that recommend it for a course such as this.
* R is FREE! That, by itself, is almost enough. No complicated licensing. Broad dissemination of research methodologies and results, etc.
* R is available for a variety of computer platforms (e.g., Linux, MacOS, Windows).
* R is widely used by professional statisticians, biologists, demographers, and other scientists. This increases the likelihood that code will exist to do a calculation you might want to do.
* R has a remarkable online presence in the form of help lists, tutorials, etc. which will facilitate solving the problems you inevitably run into in the course of your research. R represents the state-of-the-art in statistical computing.
Why Not a Spreadsheet?
* While a spreadsheet is handy for doing many demographic calculations, it is not ideal for many of the problems we will be tackling.
* For example, for a variety of problems in formal demography and population biology, one must calculate an eigenvalue. This is a simple task in an environment such as R or Matlab, but does not exist (to the best of my knowledge in most common spreadsheet applications.
* For some applications, we will be numerically solving ordinary differential equations. R has a package to do this, spreadsheet applications lack such facilities.
Posted by cengel at August 18, 2005 02:51 PM
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