I received a question recently about R Commander, a free R package.
R Commander overlays a menu-based interface to R, so just like SPSS or JMP, you can run analyses using menus. Nice, huh?
The question was whether R Commander does everything R does, or just a small subset.
Unfortunately, R Commander can’t do everything R does. Not even close.
But it does a lot. More than just the basics.
So I thought I would show you some of the things R Commander can do entirely through menus–no programming required, just so you can see just how unbelievably useful it is.
Data Sets and Variables
Import data sets from other software:
- SAS Xport
Define Numerical Variables as categorical and label the values
Open the data sets that come with R packages
Merge Data Sets
Edit and show the data in a data spreadsheet
Personally, I think that if this was all R Commander did, it would be incredibly useful. These are the types of things I just cannot remember all the commands for, since I just don’t use R often enough.
Yes, R Commander does many of the simple statistical tests you’d expect:
- Chi-square tests
- Paired and Independent Samples t-tests
- Tests of Proportions
- Common nonparametrics, like Friedman, Wilcoxon, and Kruskal-Wallis tests
- One-way ANOVA and simple linear regression
What is surprising though, is how many higher-level statistics and models it runs:
- Hierarchical and K-Means Cluster analysis (with 7 linkage methods and 4 options of distance measures)
- Principal Components and Factor Analysis
- Linear Regression (with model selection, influence statistics, and multicollinearity diagnostic options, among others)
- Logistic regression for binary, ordinal, and multinomial responses
- Generalized linear models, including Gamma and Poisson models
In other words–you can use R Commander to run in R most of the analyses that most researchers need.
A sample of the types of graphs R Commander creates in R without you having to write any code:
- QQ Plots
- Scatter plots
- Box Plots
- Bar Charts
The nice part is that it does not only do simple versions of these plots. You can, for example, add regression lines to a scatter plot or run histograms by a grouping factor.