I’m Gene Shackman, an applied sociologist in Albany, NY. A project of mine is the website “Free Resources for Program Evaluation and Social Research Methods.” One tool for researchers is data and data analysis. There are many commercial programs, but for small non profits, especially in these poor economic times, the cost of these packages can be too high. Fortunately, there are many no cost alternatives, which I’ll briefly review in this Tip-A-Day.
Rad Resources: One very popular package is R. R is, “a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques.” According to one review, The Popularity of Data Analysis Software, by Robert A. Muenchen, R is increasing in popularity, and even ranks higher than many commercial packages for use in data mining. However, R is fairly difficult to learn. Recently, a number of graphical interfaces have been developed, listed here, which should, presumably, make it easier to use R. Several of these graphical interfaces are regarded as top or up-and-coming graphical interfaces here, compiled by Ajay Ohri.
Rad Resources: There are many other free to use statistical packages, listed here and here, among other places. One page shows a comparison of which statistical procedures are offered by which packages, with R offering the most, but several others offering many procedures. Most of these packages are menu-driven, and most can import data from Excel or CSV files. One main difference is how different packages treat missing data. Many of the packages, like PSPP or MicrOsiris, can handle blanks as missing, while others, like WinIDAMS, need place holders, like -9. Another difference is that some of the packages, like MicrOsiris, OpenStat and EasyReg, were developed by individuals, while others, like EpiInfo and WinIdams, were developed by organizations. The packages developed by individuals, consequently, may have limited support. A more detailed review of the various packages is in a Citizendium entry, covering these points and more.
I want to make two final points. I reviewed many of the packages and they all gave exactly the same results for at least two procedures (correlation and regression), so any of the programs can be used with a high degree of confidence about the results (see my reviews here). However, when I did try out many of the packages, MicrOsiris did the best job of reading my data set, perhaps because I had an odd data set. So while all will work well, my personal choice is MicrOsiris.
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