1. Determine the total number of possible combinations of house models and garage/carport options. In this case, there are 6 house models and 2 options for each model (garage or carport), so there are a total of 6*2 = 12 possible combinations.
2. Assign probabilities to each of the 12 combinations. For example, if each combination is equally likely, then each combination would have a probability of 1/12.
3. Use a random number generator to simulate a large number of clients making choices. For each client, randomly select one of the 12 combinations.
4. Keep track of the number of clients who choose model B with a car garage. This will give you the frequency of this specific combination occurring in your simulation.
5. Repeat the simulation multiple times to generate a distribution of frequencies. The proportion of clients choosing model B with a car garage in the simulated data can be used as an estimate of the probability of this outcome occurring in the real world.
A large company plans to develop a private subdivision. There are 6 house
models to choose from and for each model, a client may opt to have a garage
or a carport. Use A, B, C, D, E, and F as labels for the house models.
a. Design a simulation to generate frequencies that can be used to
approximate the probability of a client who will choose model B with a
car garage.
3 answers
Use the results of the simulation to calculate the probability that a client
will choose model B with a car garage
will choose model B with a car garage
To calculate the probability that a client will choose model B with a car garage based on the results of the simulation, you can use the following formula:
Probability = Number of clients choosing model B with a car garage / Total number of clients
Here's an example of how you can calculate the probability based on the simulated data:
Let's say you ran the simulation 100 times and found that out of those 100 clients, 15 chose model B with a car garage.
Probability = 15 / 100
Probability = 0.15 or 15%
Therefore, based on the simulated data, the estimated probability that a client will choose model B with a car garage is 15%.
Probability = Number of clients choosing model B with a car garage / Total number of clients
Here's an example of how you can calculate the probability based on the simulated data:
Let's say you ran the simulation 100 times and found that out of those 100 clients, 15 chose model B with a car garage.
Probability = 15 / 100
Probability = 0.15 or 15%
Therefore, based on the simulated data, the estimated probability that a client will choose model B with a car garage is 15%.
1 answer