clt.examp: Plot Examples of the Central Limit Theorem
Description
Takes samples of size n from 4 different distributions and
plots histograms of the means along with a normal curve with matching
mean and standard deviation. Creating the plots for different values
of n demonstrates the Central Limit Theorem.
Usage
clt.examp(n = 1, reps = 10000, nclass = 16)
Arguments
n
size of the individual samples
reps
number of samples to take from each distribution
nclass
number of bars in the histograms
Value
This function is run for its side effect of creating plots. It
returns NULL invisibly.
Details
The 4 distributions sampled from are a Normal with mean 0 and standard
deviation 1, an exponential with lambda 1/3 (mean = 3), a uniform
distribution from 0 to 1, and a beta distribution with alpha 0.35 and
beta 0.25 (U shaped left skewed).
Running the function with n=1 will show the populations. Run
the function again with n at higher values to show that the
sampling distribution of the uniform quickly becomes normal and the
exponential and beta distributions eventually become normal (but much
slower than the uniform).