Experiments help us learn about probability by giving us real-life data to support ideas we think about. Here are some important points:
Outcomes: Every experiment has specific results. For example, when you roll a die, there are 6 possible results: {1, 2, 3, 4, 5, 6}.
Relative Frequency: When we try something many times (like rolling a die 100 times), we can guess the chances of different outcomes. For example, we might find that the chance of rolling a 3 is about 17 times out of 100, which we can write as 0.17.
Law of Large Numbers: If we do more and more trials, the chances we calculate from our experiments will get closer to the expected probabilities. For instance, if we flip a coin 1000 times, we would expect to see about 50% heads and 50% tails. This backs up the idea that the chance of getting heads is 0.5.
Experiments help us learn about probability by giving us real-life data to support ideas we think about. Here are some important points:
Outcomes: Every experiment has specific results. For example, when you roll a die, there are 6 possible results: {1, 2, 3, 4, 5, 6}.
Relative Frequency: When we try something many times (like rolling a die 100 times), we can guess the chances of different outcomes. For example, we might find that the chance of rolling a 3 is about 17 times out of 100, which we can write as 0.17.
Law of Large Numbers: If we do more and more trials, the chances we calculate from our experiments will get closer to the expected probabilities. For instance, if we flip a coin 1000 times, we would expect to see about 50% heads and 50% tails. This backs up the idea that the chance of getting heads is 0.5.