Advanced Statistics - Biology 6030
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Bowling Green State University, Fall 2019
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"The real voyage of discovery consists not
in seeking new landscapes, but in having new eyes." --
Marcel Proust
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
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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.
- 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.
- 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
Discussions, Examples, and Explanations on the use of R are at:
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
last modified: 8/23/17
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