hist(x, nclass = <<see below>>, breaks = <<see below>>, plot = T,
     probability = F, include.lowest  =  T, ...,
     xlab = deparse(substitute(x)))

x:

numeric vector of data for histogram.

nclass:

recommendation for the number of classes (i.e., bars) the histogram should have. The default is a number proportional to the logarithm of the length of x.

breaks:

vector of the break points for the bars of the histogram. The count in the bar is sum( breaks[i] < x & x <= breaks[i+1] ) except that if include.lowest is TRUE (the default), the first bar also includes points equal to breaks[1]. If omitted, evenly-spaced break points are determined from nclass and the extremes of the data.

plot:

logical flag: if TRUE, the histogram will be plotted; if FALSE, a list giving breakpoints and counts will be returned.

probability:

logical flag: if TRUE, the histogram will be scaled as a probability density; the sum of the bar heights times bar widths will equal 1. If FALSE, the heights of the bars will be counts.

include.lowest:

logical flag: if TRUE (the default), the lowest bar will include data points equal to the lowest break, otherwise it will act like the other bars (see the description of the breaks argument).

...:

additional arguments to barplot. The hist function uses the function barplot to do the actual plotting; consequently, arguments to the barplot function that control shading, etc., can also be given to hist. See the barplot documentation for arguments angle, density, col, and inside. Do not use the space or histo arguments.

xlab:

label for the plot x-axis. By default, this will be x.

Graphical parameters may also be supplied as arguments to this function (see par). In addition, the high-level graphics arguments described under par and the arguments to title may be supplied to this function.

if plot is FALSE, hist returns a list with components:

counts:

count or density in each bar of the histogram.

breaks:

break points between histogram classes.

If plot is TRUE, then hist calls barplot.

my.sample <-  rt(50, 5)
lab <- "50 samples from a t distribution with 5 d.f."
hist(my.sample, main = lab)