To simulate the situation described in Part F, we can use a different approach than the one used in Part C. Here's a simulation that can be used:
1. Define the number of coin flips to be simulated (e.g., 1,000 flips).
2. Initialize two counters, `headsCount` and `tailsCount`, to keep track of the number of heads and tails, respectively.
3. Repeat the following steps for the specified number of coin flips:
a. Generate a random number between 0 and 1.
b. If the generated number is less than 0.5, increment `headsCount` by 1. Otherwise, increment `tailsCount` by 1.
4. Calculate the experimental probabilities by dividing `headsCount` and `tailsCount` by the total number of coin flips.
5. Compare the experimental probabilities with the theoretical probability (0.5 for a fair coin).
6. Repeat the simulation multiple times (e.g., 100 times) and calculate the average difference between the experimental and theoretical probabilities to evaluate the simulation's accuracy.
By running this simulation multiple times, we can assess how closely the experimental probabilities match the theoretical probability on average. This simulation provides a different approach compared to the previous one and can be used to model the situation with more flexibility and accuracy.