Image via Wikipedia

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

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)


# create value labels

cyl.f <- factor(cyl, levels= c(4,6,8),

labels = c("4 cylinder", "6 cylinder", "8 cylinder"))
# plot densities

sm.density.compare(mpg, cyl, xlab="Miles Per Gallon")

title(main="MPG Distribution by Car Cylinders")

# 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