The Chi-squared test is a common test of association between nominal or ordinal data. More powerful tests exist (see below), but the Chi-squared is by far the most simple one.
Produce a contingency table of
Period, a new variable made
Date to have three categories, and calculate chi-squared.
Period variable from
Date has already been covered in
> Period <- Date > Period[(Date>650)&(Date<=1200)] <- 1 > Period[(Date>100)&(Date<=650)] <- 2 > Period[(Date<=100)] <- 3
You should probably tell R these values aren’t numbers but categories. Notice the difference:
> summary(Period) Min. 1st Qu. Median Mean 3rd Qu. Max. 1.00 1.00 1.50 1.55 2.00 3.00 > Period <- factor(Period) > Mat <- factor(Mat) > summary(Period) 1 2 3 20 18 2
This hasn’t really effect on the following operations, but it helps you keeping a clean working environment.
> table(Mat,Period) Period Mat 1 2 3 1 20 0 0 2 0 18 2
See http://finzi.psych.upenn.edu/R/Rhelp02a/archive/2847.html for
another method using
We are now ready to perform the Chi-squared test:
> crosstab <- table(Mat,Period) > xtabs() # similar to table, but different results > chisq.test(crosstab) Pearson`s Chi-squared test data: table(Mat, Period) X-squared = 40, df = 2, p-value = 2.061e-09 Warning message: In chisq.test(table(Mat, Period)) : Chi-squared approximation may be incorrect
This result is OK, but has some differences from the one you would get doing all the operations by hand:
p-valueis not a fixed one (because you’re not using tables), but rather a floating point number, expressed in scientific notation. It is very low however.
- there’s a warning about a possible approximation of the
Other tests of association mentioned in Digging Numbers don't seem so widely used, and this is probably the reason why they are not part of the standard R distribution.
This test is included in the
cramer contributed package
This test is included in the contributed package
Kendall's tau-c is not included in any package, but it can be defined as a custom function. See https://stat.ethz.ch/pipermail/r-help/2006-September/112806.html