I have a data set with following structure:

a word | number of occurrence of a word in a document | a document id 


How can I perform a test for normal distribution in R? Probably it is an easy question but I am a R newbie.

If I understand your question correctly, then to test if word occurrences in a set of documents follows a Normal distribution you can just use a shapiro-Wilk test and some qqplots. For example,

## Generate two data sets
## First Normal, second from a t-distribution
words1 = rnorm(100); words2 = rt(100, df=3)

## Have a look at the densities
plot(density(words1));plot(density(words2))

## Perform the test
shapiro.test(words1); shapiro.test(words2)

## Plot using a qqplot
qqnorm(words1);qqline(words1, col = 2)
qqnorm(words2);qqline(words2, col = 2)


The qqplot commands give:


You can see that the second data set is clearly not Normal by the heavy tails (More Info). 

In the Shapiro-Walk normality test, the p-value is large for the first data set (>.9) but very small for the second data set (<.01). This will lead you to reject the null hypothesis for the second.
