Analyzing Data

This image is a drawing of a caddisfly larva in its case. Caddisflies are aquatic insects that are used by biologists to monitor the environmental quality of streams.

This page provides access to tools that you can download and use to analyze your data.

The tools provided on this page were developed in different platforms and include a spreadsheet template, a menu-driven statistical package, and programming code. Additional tools will be developed for this page, so please share input on your preferred platform type and suggestions for additional methods.

The tools you select depend on the methods you need and your comfort level with programming. Are you:

Inexperienced with programming? We recommend that you begin by using the tools that do not require programming expertise. CADStat for, example, will allow you to conduct several types of statistical analyses using a menu-driven interface, and the Species Sensitivity Distribution (SSD) Generator provides detailed instructions and macros that may be used to generate an SSD.
Familiar with the R Statistical package? Some of our more complex tools require that you be familiar with command-line statistical programming. Command-line programming provides more flexibility for analyses, including batch processing of data. We have provided programs in R, a freely available statistical program. More information on R and on downloading our programs is provided below.

Tool 1: Species Sensitivity Distribution Generator

Download the SSD_Generator_V1.xlt (2.8MB, .xlt) to calculate and plot the proportion of species affected at different levels of exposure in laboratory toxicity tests. See the SSD methods page for further details on the use of SSD plots in causal analysis. EPA (2005) provides more detail on selecting data for SSDs and the method used in generating them.

This is a Microsoft Excel template that depends on macros for operation, so you must select “enable macros” when you open the template.

Tool 2: CADStat

CADStat is a menu-driven package of several data visualization and statistical methods. It is based on a Java Graphical User Interface to R (JGR ). Methods in this package include: scatter plots, box plots, correlation analysis, linear regression, quantile regression, conditional probability analysis, and tools for predicting environmental conditions from biological observations. Download CADStat installation instructions (PDF) (2 pp, 200K, About PDF) for directions on how to obtain this free program.

Tool 3: Command-line R Scripts

Tools for predicting environmental conditions from biological observations are also provided as R scripts (i.e., programs) for users who want to more closely examine the underlying statistics. These tools require familiarity with the command-line interface in R. The R statistical software package can be obtained from the R home page. Note that these scripts were designed in R, but may run in S-Plus as well.

New users of R may want to look at a short R tutorial.
Background material and statistical programs for predicting environmental conditions from biological observations is available in a separate web module called predicting environmental conditions from biological observations.
Users who are very comfortable with R can directly download a library containing scripts that are useful for predicting environmental conditions from biological observations. This library can be accessed by typing the following command in R:
install.packages("bio.infer")