cluster analysis

What R Commander Can do in R Without Coding–More Than You Would Think

October 19th, 2015 by

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.

Since R commander is a free R package, it can be installed easily through R! Just type install.packages("Rcmdr") in the command line the first time you use it, then type library("Rcmdr") each time you want to launch the menus.

Data Sets and Variables

Import data sets from other software:

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.

Data Analysis

Yes, R Commander does many of the simple statistical tests you’d expect:

What is surprising though, is how many higher-level statistics and models it runs:

In other words–you can use R Commander to run in R most of the analyses that most researchers need.

Graphs

A sample of the types of graphs R Commander creates in R without you having to write any code:

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.

If you’re ready to get started practicing, click here to learn about making scatterplots in R commander, or click here to learn how to use R commander to sample from a uniform distribution.

 


Member Training: Cluster Analysis–Hierarchical and KMeans

May 7th, 2014 by

Cluster analysis classifies individuals into two or more unknown groups based on a set of numerical variables.

It is related to, but distinct from, a few other multivariate techniques including discriminant Function Analysis, (more…)