Statistical Software Snobbery

Today I was scanning the results of a Google search on something statistical and I happened to click on the site of one of my competitors, another statistical consultant. I landed on one of his website pages that was promoting his expertise with statistical software, and was annoyed by reading his characterization of SPSS as just a “simple statistical package”, compared to “world class” packages like “SAS or R” that offer “high powered statistical analysis“. His implication was that SPSS is little more than a toy. Stata and Minitab are apparently unmentionable in this person’s view.

I encounter this view from time to time, usually indirectly through students whose professors are compelling them to use R or SAS. This propensity to derogate statistical systems that have been made more accessible to a wide range of potential users, and which are designed to expedite the conduct of lengthy analyses, seems to stem from at least three different motives. One source of such behavior is a weak ego. It is unfortunately not rare to find people who can feel good about themselves only by putting other people down. Since far fewer people make the effort to learn R, or have the resources to acquire access to SAS, a noticeable proportion of the people attracted to these software systems are motivated by the desire to gain some bragging rights over others.

Another source of this “put down” behavior is crass commercialism. If you can convince the public that your relatively rare skill can solve their problems better than a skill that is held more widely or that even could be acquired by the end-user him-/herself, you can charge more for your skill.

Least reprehensible, but no less damaging, is the belief that these harder to acquire software packages (where the barrier to acquisition is either the learning curve or the cost of the package) actually do everything better than the more widely accessible packages.

We can dismiss those driven by the ego-inflation motive as just your garden variety jerk who will always be with us. In my 23 years as an academic I encountered more of them ensconced in university faculties than I care to even think about. More importantly, my purpose here is not to try to change the views and behavior of any of these people who seek to put down more accessible statistical packages. Instead, my purpose is to give the rest of you an accurate understanding of the relative merits of the most widely used statistical packages.

The fact of the matter is that no statistical packages are “world class” in regard to all of the criteria by which such packages can be judged, and practically all of the packages are “world class” in some respects. Let’s consider what these criteria are in relation to widely-used, all-purpose statistical software packages. Here is my list (feel free to write-in to add more):


    1. Ease of use


    1. Learning curve


    1. Depth of menued procedures


    1. Range, quality, and ease of use of statistical procedures offered


    1. Modifiability of analytical output specifications


    1. Ease of transforming table output to formatting conventions (e.g., APA)


    1. Range of graphical output offered


    1. Speed of handling large data sets


    1. Ease and flexibility of data importation


    1. Ease of results exportation


    1. Thoroughness and interpretability of results output


    1. Ease and flexibility of data set manipulation


    1. Pricing for individuals


    1. Thoroughness and informativeness of documentation


I have written a review of the top 5 statistical software systems (i.e., SPSS, SAS, R, Minitab, and Stata) that evaluates these systems against each of the above criteria. It is available as an article in the Articles section of this website (A Review of the Top Five Statistical Software Systems).