Comparison of
PC-ORD and R

Although many of the same tools are available in PC-ORD and R, the user experience differs radically.  To conduct the necessary and appropriate analyses for community data in R, you must learn the R programming language, manually identify, hunt down, and download 'vegan' and various other 'packages', and modify the code as necessary to achieve your analysis objectives and obtain suitable graphics.  PC-ORD offers ease of use, expert-driven analysis preference options, the convenience of a point-and-click graphical user interface, the power and flexibility of interactive graphics, a built-in context-sensitive help system, and free dedicated technical support; none of which is available in R.  While R encourages user development of scripts, PC-ORD also allows advanced users to develop scripts through its "Batch" facility (introduced in v.6), as well as the ability to incorporate user-developed modules into the menu system.   PC-ORD thus enables you to quickly and confidently select, run, and interpret appropriate analyses and produce tailored, publication quality graphics with virtually no preparatory effort.

No other software makes the process of community analysis fast and easy enough that the beginner is actually likely to do it all—and do it right.  Not only does PC-ORD put most of the tools you need in one place, but because the programming has been done for you already, you can spend your time on what really matters—exploring your data, answering your questions, and testing your hypotheses.  PC-ORD helps you ensure that you can clearly see the options for your dataset and objectives, and helps you interpret your outcomes with powerful graphics and detailed explanatory listings of results.  MjM Software answers questions and provides other support, while R packages do not have dedicated support.

PC-ORD Features not Found in R

* Integrated Fast and easy Windows menu-driven analysis and graphing integrated into a single program
* Supported Free one-day email technical feedback for both software and analysis questions
* Flexible Menu-driven parameter setup options allowing appropriately tailored analyses
* Comprehensive Includes major analysis tools plus unique tools for community analyses
* Help System Extensive context-sensitive help system
* NMS (NMDS) features Built-in randomization test, real-time stress plots
* Ordination graphics Hilltop plots for multiple nonlinear overlays, kernel smoother contouring with optimized or user-controlled smoothing parameter, successional vectors overlay
* Species traits Integrated trait matrix operations and overlays for traits
* Advisor Wizard Helps you decide how to transform and analyze your data
* Decision Tree Poster Helps you understand the Advisor Wizard logic
* Step-by-Step Book 10 step PC-ORD guide, authored by our training specialist
* Analysis Book Methods for analysis, authored by one of our principal programmers


by Dr Winfried Voigt
University of Jena, Germany

Thank you for the wonderful news that v. 7 has now been released.  Even though practically every multivariate statistical technique/method could alternatively be done using R language, I still prefer using PC-ORD for teaching ecology students multivariate statistics.  PC-ORD is very user-friendly and offers, in just one self-contained package, many powerful methods and a great toolbox (“Modify Data”) that ecology students really need and can quickly utilize in their research.  An excellent feature is the textbook-like, built-in documentation explaining theoretical background in detail.

We also offer courses on how to use R efficiently, but there are always students without experience or who have not attended such a course, or regardless, still have problems with R and so in a classroom setting, they hold back progress.  Hence, in practical, hands-on courses that are also quite limited in time, students using PC-ORD can focus much more on the statistical and ecological background rather than by spending too much time with programming.  The objective of my courses is the understanding of the process of multivariate data analysis and not so much on the technical part, even the latter results in a more thorough understanding of the procedures applied.  When students understand why and how to effectively do multivariate statistical analyses of their data, they can then use, with little effort, other programs or packages as well.

by Dr. Peter R. Nelson
University of Maine at Fort Kent

In the world of increasing use of open-sourced statistical platforms like R, some might wonder if there is a need for proprietary stats programs.  Despite this trend, I find myself still going back to PC-ORD, even though I also use R, Python and other scripting platforms.  The reason I keep using PC-ORD is simple: PC-ORD is clearly superior to trying to code the same functionality in R or other popular open-source analytical platforms.  Another reason I keep using PC-ORD is the great documentation that is almost like a course in multivariate stats built in to the software.  You can find answers to many of the common questions or even detailed descriptions regarding most of the algorithms used in the software, all of which has citations to primary literature for the even more curious user.