The Simulator program allows you to specify a theoretical model or a set of data and take repeated samples. Its overall design is based on the simulation methods used in De Veaux, Velleman, and Bock's statistics textbooks. It enables you to construct sampling distributions, compute empirical p-values, and test hypotheses.
The program is written in Python, using several additional libraries (wx, numpy, scipy, and matplotlib). If you find a bug or would like to suggest a way to improve the program, please contact me.
- Mac Version
- Windows Version
Note: Some Windows computers may experience a bug where the program doesn't display the results of running a trial; in this case, clicking on the scroll bars will make the results appear
- Java Version (This version offers many more options than the Mac and Windows versions, but it also somewhat buggy.)
- Source Code for Java Version
To quickly get started, read the (short) manual, which includes a simple example.
To see the Simulator in action, you can watch a video of a student using it to solve a problem
This tutorial consists of four examples. Each example is a question that can be answered/investigated by constructing an appropriate sampling distribution. After stating the question, each example describes a way to set up the Simulator to answer the question. These four examples don't use all of the Simulator's features, but should give you a good sense of how the program works and can be used.