## Software

In this course you will be calculating many complex values and this will require that you have some specific software installed on your computer. I have selected to use the following software in this class for several reason. All software packages are available for any computer operating system (Windows, Linux or Mac OS).

R -- The R Project for Statistical Computing (http://www.r-project.org/) -- the R statistical package is being developed by some of the top statisticians in the world and new packages are being added all the time. This software can provide publication quality graphics for your reports and future papers. Another nice feature is the software is free.

Some students like to use RStudio (http://www.rstudio.com/) which is install in addition to R to improve the file system and editor interface.

R takes a little time to learn well, but it is well worth the effort. To start see the resources on the R webpage side bar under documentation. Particularly start with the manual An Introduction to R, as you need more detail check out the other manuals. Also note the R wiki and the Books sections. the Books section list over 100 books that describe the use of R in various kinds of statistical analysis. One book to particularly note is Forest Analytics with R by Andrew Robinson and Jeff Hamann. This book presents many similar topics to those present here but approaches the problems from a different perspective. Here is a copy of Andrew Robinson's icebreakeR R document.

Word processor and spreadsheet -- (Word and Excel (commercial available on many computers) or Openoffice (http://www.openoffice.org/). Either of these tools will be necessary for producing the required reports and reformatting data.

A programming language -- (optional but very helpful) I suggest either Python (http://www.python.org/) is a structured object-oriented language which can be very helpful in reformatting data or performing calculations. This software is very robust, with lots of useful quantitative packages. It is a bit slower that other languages, because it is interpreted at run time not compiled but this makes finding your error much easier.

Another resource if you interest in learning other computer languages. Forestry Functions, which provide a number of functions that calculate values of interest to foresters in 4 computer langauges including R and python.