Finding the correct probabilities of events may be difficult to do. At times the correct results may seem to be wrong. The use of simulation can be of great benefit by saving both time and money over the alternative of solving the problem by applying only the abstract principles of probability theory. We define a simulation as follows.
| A simulation
of an experiment is a process that behaves the same way
as the experiment, so that similar results are produced. |
Alternatively, one could toss dice repeatedly and tally the results; program the TI-83+ graphing calculator to toss dice repeatedly [int(1+6rand)]; (or randInt(1,6,5) will roll 5 dice) or download a 30 day evaluation copy of MINITAB and simulate it. One might be tempted to use a standard spread sheet program, but since these were not written and are not endorsed by statisticians one should be very wary of the statistical results they produce. Some have been shown to be just plain wrong, but the software giant(s?) refuse to correct these errors.
A few other common teaching packages include: Fathom (much like Geometry Sketchpad and also by Key Curriculum), Data Desk (packaged with ActivStat, a multimedia Statisitical education package). Some professional packages include: SAS (Statistical Analysis System), BMDP, and SPSS (Statistical Package for the Social Sciences). All these packages are produced to provide statistically valid results (unlike many spreadsheets).
Example: What is the expected average family size if a couple plans to stop having children after having one child of each gender. (No processes, such as timing, acidity, deposition depth, etc. are used to enhance gender selection.)
Solution: Instead of using expensive and time consuming methods such as conducting a controlled experiment or surveying a large number of families, we will toss a coin. Both sides (heads and tails) are equally likely. Heads can represent girls and tails can represent boys. For each "family", toss until you get one head and one tail: (H,H,H,T), (T,T,T,H), (H,H,H,H,H,H,T), (H,T), etc. After a dozen "families" or so, we will obtain a result close to 3, the theoretical results.
Historically, random number tables were commonly used as a source of random numbers. We will use here the digits of pi which are commonly available. Here we will let boys be represented by the digits 0, 1, 2, 3, and 4 and girls be represented by the digits 5, 6, 7, 8, and 9. (Since the digits of pi are uniformly but also randomly distributed, we could have just as well used even vs. odd or perhaps used just 1's and 0's, ignoring the rest.) Starting with 14159 26535 89793 ... we have the following families: (BBBG), (GB), (GGB), (GGGGGB).
This simple simulation will give us good results without much effort. Whenever a simulation is developed, we must be careful to ensure that the process imitates the actual process very well. One could critize this example by noting that boys (0.513) and girls (0.487) are not equally likely, nor are sibling genders necessarily independent.
One of the first applications of simulation here at Andrews University was back in the mid 1970's to analyze computer terminal usage. The results were published in the infamous 1976 self study. The director of the computing center, LeRoy Botten, had Bruce Ferris, a 14-year old high school drop out, known as The Kid or TK, do the analysis. Simulations are commonly used to forecast weather, "play" war games, analyze nuclear power plants, and other applications where conducting experiments are challenging.
| T. OF CONTENTS | HOMEWORK | SOLUTIONS | ACTIVITY | CONTINUE |
|---|