| Package |
Strengths |
Weaknesses |
| R |
Free (Open-Source) so not restricted to site
licenses
Has kept up with the times with regard to methods
appropriate to the academic researcher across a wide range of disciplines
Near-daily updates
Can teach/demonstrate statistical concepts
with it (even has an add-on package devoted specifically to
that)
Graphics capabilities practically unmatched
Extensive documentation, even free complete books on line
Easy to use menu system (as an addon) that
has even advanced methods available |
More difficult to learn than other stat
programs, unless you already do real programming.
No real
viable 'spreadsheet style' maneuverability within the data
(though for analyzing parts of a dataset it is actually much
easier than many gui-oriented products) |
| Summary:
There simply isn't much you can't do with R as an academic
researcher, and while it can be difficult to learn, that will
eventually turn into time saved had you tried to do similar things with other
packages. It is Mike and Rich's package of choice. |
| PASW |
Easy
to use menu system for basic analyses (going beyond the basics
for most research needs will typically require syntax or another
package)
Until v. 16, very easy to move around
within the data
Can get output easily and in easy to read format
|
Not geared specifically to academic research
needs
Prohibitively expensive for students
Consistent
license issues
New versions are not fully backwards
compatible by design
For some disciplines' typical
analyses, no significant updates in years
Not a true programming language
Lacks basic
things like testing of assumptions, computing of some standard effect sizes
etc.
Only a handful of 'official' statistic specifc macros available
and most regarding analyses much better implemented in other
packages (e.g. subset regression)
Typically released
notably buggy
Base install is decades behind the times in most analyses often used such as regression,
ANOVA,
factor analysis
Few base offerings for dealing with problematic data
Terrible graphics
Cost |
| Summary:
We don't feel PASW has academic research needs first and foremost
anymore, and in general it makes doing good, modern data analysis (in
that academic arena) difficult to go along with being cost prohibitive to
students. The RSS groups further feels that release 16 was possibly
their poorest effort ever. Its only advantage over other packages for
years has been ease of use, and that has been dwindling rapidly as the
other packages catch up. |
| SAS |
Powerful out of the box
Includes many modern
techniques
|
Not geared specifically to academic research needs
Painful installation
Even
more expensive than PASW student version
Not a true programming language
Not user friendly
compared to other packages
Cost |
| Summary:
Of the standard popular packages one comes across, it has more to offer
than most, though not very user-friendly. It appears to offer more modern
academic computing than e.g. PASW and is widely used across many disciplines. |
| STATA |
Essentially a stat package geared specifically to the social scientist
Very strong on Generalized Linear Models and Time Series analysis
Straightforward programming language
User add-ons easy to implement
Has its own journal |
Not so easy on the eyes for most people (unless you miss DOS)
Cost |
| Summary:
A nice package, particularly for the political science, economics
crowd, where its offerings are quite advanced. Patrick's chosen
package. |
|
S-Plus |
Gui implementation of the S-language while retaining all the power of that language |
Less flexible than its R counterpart
Cost |
| Summary:
For the academic crowd, it doesn't really offer anything R
doesn't except with an easy to use gui out of the box. If you're
willing to pay for that and not have access to the multitude of
packages in R, feel free. For academics the S-language offers
more than the others available in our opinion. |
