**Data and Analysis with R, at Work**, and kindly contributed to R-bloggers)

The task today was to find what variables had significant relations with an important grouping variable in the big dataset I’ve been working with lately. The grouping variable has 3 levels, and represents different behaviours of interest. At first I tried putting the grouping variable as a dependent variable in a multinomial logistic regression, but I didn’t really trust the output, and the goal was really just to construct a bunch of graphs showing significant bivariate nominal relations in the data..

That’s when I turned to my good old friend, the chi squared test. All I had to do was select all the variables that I wanted to test against the grouping variable, and construct a list of the chi squared statistic from each test, the variable being tested, and the crosstab of the two variables for later graphing. So that’s exactly what I did:

One really sweet thing about matrices in R is that you can mix them up with some parts having just numbers, some parts having text, and sub-matrices in other parts! A typical row of the “resultlist” would look something like this:

xsq testvar xtab

[1,] 200.7 “variable1″ numeric,6

Then all I needed to do to see the variable name and crosstab for that variable was to call “resultlist[1,2:3]“, and that gave me the numbers to graph.

**leave a comment**for the author, please follow the link and comment on his blog:

**Data and Analysis with R, at Work**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...