As requested, here's some R code for checking the normality of a set of data. In the code below, I've assigned to the variable x a set of 12 random numbers generated from a normal distribution. For your projects, you'll already have a set of data to check.

> x <- rnorm(12,0,1) > x [1] 1.45969937 1.06523019 -0.55190387 0.50203983 -0.18073330 [6] 0.03498171 0.74422040 -0.26451116 -0.99968966 -1.65212671 [11] 1.16201012 0.29497770 > qqnorm(x) > qqline(x) > hist(x) > counts <- vector(mode="numeric",3) > for (i in 1:3) counts[i] <- length(subset(x,abs(x-mean(x)) < i*sd(x)))/length(x) > counts [1] 0.5833333 1.0000000 1.0000000

The above code generated these two plots: