Lectures: Mon,Wed, 14:30-15:20 LSC 204

Lab: Fri, 14:30-16:20 LSC 204

Instructor:

Dr. Robert Huber LSC 227 Office Hours: Mon, Wed 13:30-14:20 or by appointment Phone: (419) 378-4253

Software

Tools for manipulating TEXT files

You also need to become familiar with a proper TEXT editor. Essential features include the ability to handle text files written on different computer platforms (Mac, Windows, UNIX), unlimited filesize, and GREP searching. A great freeware, cross-platform option is jEdit. There are alternative options to it for different platforms.

1. You already have a number of applications that allow you to open/manipulate/save files in plain text format. Even your standard office package (e.g., MS Office; free, open source LibreOffice, etc.) will do that. However, you might want to look around and acquaint yourself with something a bit more powerful, something that allows you to control line endings, GREP, good search and replace.
2. jEdit - or TextWrangler (Mac), NotePad++, TED Notepad or Windows GREP (Windows)

Tools for Statistical Analysis

You should use this course to become familiar with the statistics package of your choice. Several programs are available via the University keyserver, including Statview v 5.0.1 and Minitab v 10.5 or JMP from SAS Institute. Do not use the Stats Package in Excel, here is why. I assume you already have some programs that you use for your daily statistical analysis. I encourage you to continue using them unless you find them inadequate for whatever task you are asked to complete. My personal preference for statistics and data exploration software is the comprehensive R Package - a public domain, freeware framework for statistical analysis that runs on a wide variety of UNIX platforms, Windows and MacOS.

Texts

We will piece together elements from various sources. The univariate material in this course is covered well by either of the following texts:

• Biometry: The Principles and Practice of Statistics in Biological Research by Robert R. Sokal, F. James Rohlf W H Freeman & Co.; ISBN: 0716724111
• Biostatistical Analysis by Jerrold H. Zar, Prentice Hall; ISBN: 013081542X
• A good primer for using R is Beckerman AP & OL Petchey. 2012. Getting Started with R: An introduction for biologists. Oxford University Press, USA. ISBN-10: 0199601623

The multivariate material is discussed in good detail in:

• Reading and Understanding Multivariate Statistics by Laurence G. Grimm, Paul R. Yarnold (2000), American Psychological Association (APA); ISBN: 1557982732

• Quick-R
• Wiki Books: R-Programming
  

Goals:

• Gain familiarity with the stats program of your choice
• Develop an intuitive understanding of multivariate and other statistical techniques in the biological sciences
• Implement algorithms for any custom analysis as a Java Program

Suggestions

• use your own data sets whenever possible

Resources

• Webpage at http://caspar.bgsu.edu/~courses/stats/