Software

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Contents

Templates

48" x 36" Poster Template in OpenOffice PowerPoint from Prof Nolan's 2010 Fall Stat20 Class: TBP

Free or Discounted Software

Free or Open-source Software

  • MacPorts [1] has a huge collection of open source software and makes the installation and updating these very easy to use. Example programs are like simple drawing program: Dia, Xfig, etc.
  • Statistical Software: R [2], Python [3]

Commercial Software Discounts for Berkeley Students

Berkeley Students can often get discounted license for commercial programs (e.g. SAS, MatLab, Stata) or sometimes free (e.g. TextMate, various Anti-Virus programs) here. http://software-central.berkeley.edu/

Producing Nice Figures and Graphics

Here are a few programs that various people in the department and beyond use and recommend.

  • PSTricks: allows you to draw PostScript pictures directly in your LaTeX code. Pretty neat and not too hard to learn. Great if you know what you want to draw, not so good for just fooling around. Website and user's guide (which is good!).
  • Xfig: free open source vector graphics editor. Has LaTeX support contained within but also potential for messing around. Website.
  • TikZ: free open source. Many people like it, there are a bunch of nice examples to learn from, though apparently there is a steep learning curve. On Sourceforge.
  • Inkscape: free open source vector graphics editor. Many people like it, useful for many things. It has its shortcomings too, e.g. cropping images in Inkscape is a real pain. Website.
  • Dia: free open source diagramming software. Website.
  • OmniGraffle: for Macs only. Also it is not free (though it has a free two week trial). It is pretty good though. Website.
  • Ipe: free vector graphics editor. Especially good if you want to make geometric figures. Website.

Version Control

  • Git: recommended versioning system.
  • Mercurial: another good versioning system.
  • SVN: unlike Git in that the repositories are not local.

You can host your Git repositories here at GitHub or Git and Mercurial repositories at BitBucket.

Document Preparation

  • Lyx: GUI for LaTeX; kind of like merging MS Word and LaTeX into one.
  • LaTeX (For Mac: [4], For PC: [5]
  • OpenOffice: Open-source software comparable to Microsoft Word Suite (Word, Powerpoint, Excel, etc.).

Text Editing

  • Aquamacs: Aquamacs is a GUI for emacs. Also comes installed with ESS (Emacs Speaks Statistics), an interface between emacs and R/S.
  • TextMate: *Not* free, though previously discounts were available for Berkeley students (see above section on Discounts on Commercial Software). Never tried, but another popular text editor within the department.

Paper Organization

  • Papers: Mac program, *not* free, but a student discount is available. This program organizes your paper collection into folders and preserves metadata like author list, title, journal (year, volume, issue, pages) for export as a BibTeX library. You can add papers by importing PDF files; the program also allows you to search Google Scholar, JSTOR, PubMed, etc. within the GUI and import directly this way. Smart "matching" of papers is done so as to minimize the amount of metadata you must enter manually.
  • Mendeley: Free paper organization software. Never tried it, maybe someone else can speak on this?
  • Protip: If you prefer not to use software for managing your papers, but do your file organization and BibTeX reference compilation manually, GoogleScholar enables very facile BibTeX citation import. Go to Google Scholar Preferences and at the bottom of the page, select "Show links to import citations into BibTeX." Now, for any GoogleScholar search, a link saying "Import BibTeX" should appear under each result.

Statistical Computing

  • Enthought Python Distribution: Via the Python bootcamp, this is a preferred distribution of Python because it comes equipped with several modules heavily used in scientific research: numpy, scipy, stats, etc.
  • Protip: Rather than downloading each R package as you come to need it, you may be interested in downloading a collection of packages related to, say, multivariate analysis or machine learning. For this purpose, CRAN has grouped several useful and popular packages by topic here.
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