I was searching for some basic syntax in R (basically cross tabs and density plots) and I came across the Quick R site.

http://www.statmethods.net/

Its really a nice site for R beginners and anyone trying to remember some syntax.

R syntax can be very simple- a histoigram is just hist(), boxplot is just boxplot() and t test is just t.test(dataset)

Here is an example from the site-

http://www.statmethods.net/graphs/density.html


# Simple Histogram
hist(mtcars$mpg)

click to view

# Colored Histogram with Different Number of Bins
hist(mtcars$mpg, breaks=12, col="red")

click to view

# Add a Normal Curve (Thanks to Peter Dalgaard)
x <- mtcars$mpg
h<-hist(x, breaks=10, col="red", xlab="Miles Per Gallon",
main="Histogram with Normal Curve")
xfit<-seq(min(x),max(x),length=40)
yfit<-dnorm(xfit,mean=mean(x),sd=sd(x))
yfit <- yfit*diff(h$mids[1:2])*length(x)
lines(xfit, yfit, col="blue", lwd=2)

click to view

Histograms can be a poor method for determining the shape of a distribution because it is so strongly affected by the number of bins used.

KERNEL DENSITY PLOTS

Kernal density plots are usually a much more effective way to view the distribution of a variable. Create the plot using plot(density(x)) where x is a numeric vector.

# Kernel Density Plot
d <- density(mtcars$mpg) # returns the density data
plot(d) # plots the results

click to view

# Filled Density Plot
d <- density(mtcars$mpg)
plot(d, main="Kernel Density of Miles Per Gallon")
polygon(d, col="red", border="blue")

click to view

COMPARING GROUPS VIA KERNAL DENSITY

The sm.density.compare( ) function in the sm package allows you to superimpose the kernal density plots of two or more groups. The format is sm.density.compare(x, factor) where x is a numeric vector and factor is the grouping variable.

# Compare MPG distributions for cars with
# 4,6, or 8 cylinders
library(sm)
attach(mtcars)

# add legend via mouse click
colfill<-c(2:(2+length(levels(cyl.f))))
legend(locator(1), levels(cyl.f), fill=colfill)

click to view

It is not as exhaustive as http://cran.r-project.org/doc/manuals/R-intro.html

but it is much more simpler and easy to follow.

The site is created by Robert I. Kabacoff, Ph.D.

and he is working on a book called “R in Action”

I have received numerous requests for a hardcopy version of this site, so over the past year I have been writing a book that takes the material here and significantly expands upon it. If you are interested, early access is available.

 

If you have not been to that website, I recommend it highly (though the tagline or logo of R for SAS/SPSS/Stata users seems a bit familiar)-http://www.statmethods.net/index.html

Quick-R

for SAS/SPSS/Stata Users

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