1, Unit 7 - Simulation Models
In the "Simulation Models" unit, students learn to design and carry out
simulations to estimate answers to questions about probability. Situations
involving uncertainty surround us, from weather forecasts to stock markets.
Many of these situations are too complex to be handled theoretically,
but some of them are quite accessible through the technique of simulation.
This technique has a history that is concurrent with the development
of computing technology, and your student uses methods that make good
use of the graphing calculator. Theoretical probability is developed
in Courses 2 and 3.
Ideas from Course 1, Unit 7
- Simulation model: A way of modeling a real situation that involves
randomly occurring events. For example, suppose that 45%
of a population has type O blood. Here's how to use simulation to estimate
the probability that 4 random
people entering a blood donor bank have blood type O. Model
the selection of one person chosen at random from the population by
assigning the numbers 1-45 to represent people with type O blood
and 46-100 to represent other people. Choosing 4 numbers at random
from 1 to 100 and counting how many are 1-45 would simulate 4 random
people entering a blood donor clinic and
identified by blood type.
- Trial: In the above
example, if 4 random numbers between 1 and 100 are drawn and the result
46, 70, 31," then there are 2 type O blood persons (represented by numbers
1-45) in this one trial of the simulation.
- Law of Large Numbers: The more trials you do, the more likely
that your result will be close to the exact, theoretical probability.
- Probability distribution: A list of all possible outcomes of a chance
situation along with the probability that each occurs.