Chance events can make it tricky to understand experimental and theoretical probability. Here’s how:

1. Inconsistencies:

   • Experimental probability comes from doing real-life tests. Sometimes, these results don’t match what we expect. For instance, if you flip a coin 10 times and get heads 7 times, that’s a big difference from the expected 5 times.

2. Small Sample Sizes:

   • When we test with only a few tries, the results might not show the true picture. This can make it hard to know what’s really going on.

3. Misinterpretation:

   • Students can misunderstand patterns like streaks or gaps in the results. They might think these patterns are more important than they really are.

To tackle these issues, we can do a few things:

• Increase the number of trials we perform.
• Teach students about the law of large numbers, which states that the more we test, the closer our results will get to what we expect.

Doing these things can help our experimental results better match theoretical predictions.