In this recipe, we introduced Pearson's chi-squared test, which is used to examine whether the distribution of categorical variables of two groups differ. We will discuss how to conduct Pearson's chi-squared Test in R.
In this recipe, we will use the chisq.test
function that originated from the stat
package.
Perform the following steps to conduct a Pearson's chi-squared test:
First, build a matrix containing the number of male and female smokers and nonsmokers:
>mat<- matrix(c(2047, 2522, 3512, 1919), nrow = 2, dimnames = list(c("smoke","non-smoke"), c("male","female"))) >mat malefemale smoke2047 3512 non-smoke 2522 1919
Then, plot the portion of male and female smokers and nonsmokers in a mosaic plot:
>mosaicplot(mat, main="Portion of male and female smokers/non-smokers", color = TRUE)
Next, perform a Pearson's chi-squared test on the contingency table to test whether the factor...