Random experiments are really important for understanding probability. They help us learn about some key ideas. Here are a couple of them:
Events: These are the results of a random experiment. For example, when you roll a die, the possible results are {1, 2, 3, 4, 5, 6}.
Sample Spaces: This is the complete list of all possible outcomes. For example, if you roll two dice, the outcomes include pairs like (1,1), (1,2), and so on, all the way to (6,6).
When we run experiments, like flipping a coin 100 times, we can discover real-world probabilities. The more we flip the coin, the closer our results will get to the expected probabilities. This idea is known as the Law of Large Numbers.
Random experiments are really important for understanding probability. They help us learn about some key ideas. Here are a couple of them:
Events: These are the results of a random experiment. For example, when you roll a die, the possible results are {1, 2, 3, 4, 5, 6}.
Sample Spaces: This is the complete list of all possible outcomes. For example, if you roll two dice, the outcomes include pairs like (1,1), (1,2), and so on, all the way to (6,6).
When we run experiments, like flipping a coin 100 times, we can discover real-world probabilities. The more we flip the coin, the closer our results will get to the expected probabilities. This idea is known as the Law of Large Numbers.