Teachers can show students that measurement, sampling, design, and analysis issues are dependent on the model that is assessed. Students can directly manipulate the simulation model and try things out to see immediately how results change and how analyses are affected. Simulations are better for some purposes than is the analysis of real data. With real data, the analyst never perfectly knows the real-world processes that caused the particular measured values to occur. In a simulation, the analyst controls all of the factors making up the data and can manipulate these systematically to see directly how specific problems and assumptions affect the analysis.
Simulations also have some advantages over abstract theorizing about research issues.
Most of this work has been confined to the more technical literature in these fields. Although the simulations described here can certainly be accomplished on mainframe computers, this workbook will illustrate their use in manual and microcomputer contexts. There are several advantages to using simulations in these two contexts. The major advantage to manual simulations is that they cost almost nothing to implement. Computer simulations are also relatively low in cost.