Experimental probability is the probability of an event based on actual experiments or observations, not theory. You perform an experiment several times (trials), record outcomes, and use the results to estimate the probability.
Formula
Experimental Probability = (Number of times the event occurs) / (Total number of trials)
Example
Suppose you toss a coin 50 times and get heads 28 times.
Experimental probability of heads = 28 / 50 = 0.56 (or 56%).
How many trials are enough?
- More trials → more reliable: As the number of trials increases, experimental probability tends to approach the theoretical probability.
- Classroom guideline: About 30–50 trials usually show a clear pattern.
- High accuracy: Real-world studies may use hundreds or thousands of trials.
In short: Experimental probability uses real data, and doing more trials makes the estimate more accurate.
