Download Some useful elementary functions in R. If you need help in using a

Some useful elementary functions in R.
If you need help in using a function you write ?functionname where functionname is the name of the
function. For example ?mean will describe how to apply the function mean.
When using a function the correct arguments must be supplied as, for example, mean(vector) which will
give the mean of the values in ’vector’.
Funct ions/names-of
Brief description of what the function does
mean(arg)
median(arg)
quantile(arg)
summary(arg)
sd(arg)
var(arg)
Computes mean/average
Computes median
Computes quantiles
Computes mean, standard deviation and selected quantiles
Computes standard deviation
Computes variance
hist(arg)
barplot(arg)
boxplot(arg)
plot(arg)
Generate a histogram
Generate a barplot
Generate a boxplot
Generate an x-y plot
pnorm(arg)
pbinom(arg)
ppois(arg)
pexp(arg)
qnorm(arg)
qbinom(arg)
Computes probability in the normal distribution
Computes probability in the binomial distribution
Computes probability in the poisson distribution
Computes probability in the eksponential distribution
Find quantile(s) in the normal distribution
Find quantile(s) in the binomial distribution (qpois(arg), qexp(arg) likewise)
rnorm(arg)
Simulates normally distributed data. rbinom(arg), rpois(arg), rexp(arg) for
simulation of the binomial-, poisson- and exponential distributions
pt(arg)
pchisq(arg)
pf(arg)
qt(arg)
qchisq(arg)
qf(arg)
Computes probability in the t-distribution
Computes probability in the 2 distribution
Computes probability in the F-distribution
Find quantile n the t-distribution
Find quantile in the 2 distribution
Find quantile in the F-distribution
t.test(arg)
var.test(arg)
prop.test(arg)
chisq.test(arg)
lm(arg)
anova(arg)
Carries out a t-test for one or two vectors (comparing means)
Carries out an F-test for two vectors (comparing variances)
Carries out a test for two proportions (binomial) (comparing proportions)
Analysis of contingency tables
L inear regression and analysis of variance model estimation
Analysis of variance (often for lm()-models)