.-
help for ^clt^
Central limit theorem demonstration
.-

The programs ^clt^ is designed to illustrate 
the Central Limit Theorem.  

^clt^ allows you to take a given number of samples of size ^n^
from a given distribution and show the distibution of sample means. 

After you invoke ^clt^, a dialog box is shown allowing you to
make the following choices regarding how the data is sampled.

^Distribution Type^
  Normal      - A normal distribution.
  Log normal  - Log of a normal distribution.
  Exp normal  - Exponential of a normal distribution.
  Exponential - Exponential of a uniform distribuiton
  Bimodal     - Two normal populations with means 3 units apart
                that are added together
  Binomial    - A 0/1 variable. If you choose this, you can use the
                ^If Binomial, P=^ pulldown to choose the probability
                of a 1 occurring.
  Uniform     - A uniform distribution.

^If Binomial, P=^ 
  If you draw from a binomial distribution, you can use the ^p()^ 
  option to specify the probability of success. The default is .5 .

^N per sample^
  Allows you to choose the sample size, default is 1.

^# of Samples^
  Allows you to choose how many samples are drawn, default is 1000.

You can also make the following choices regarding how the 
graph of the sampling distribution is displayed.

^Show Normal Overlay^
  Includes a normal overlay on the histogram.

^Draw Lines as +-1SD and +-2SD^
  Draws lines at 
    xbar - 2sd  
    xbar - 1sd
    xbar
    xbar + 1sd
    xbar + 2sd

^Show means as Z scores^
  Shows the X axis as Z scores, helping you to see
  skewness in the data.

^Show sums instead of means^
  Shows the values on the X axis as the sum of the scores
  in the sample (rather than the mean).  This is useful
  when the distribution is binomial.  

After you have made your selections, you can click the
^show^ button and the results are calculated and displayed.
If you choose a large number of samples (say over 3000), then
there may be a delay while the samples are drawn.

When you want to exit the program, click on the ^done^ button.


Author
------

Michael N. Mitchell
Statistical Computing and Consulting
UCLA, Office of Academic Computing
mnm@@ucla.edu