1. **State the problem:** We need to find the probability that an event will occur based on experimental data, and then find the probability that the event will not occur using the complement formula. 2. **Formula for probability of an event:** $$P(\text{event}) = \frac{\text{number of times the event occurs}}{\text{number of times the experiment is done}}$$ This formula means you divide how many times the event happened by the total number of trials. 3. **Complement rule:** $$P(\text{not event}) = 1 - P(\text{event})$$ This means the probability that the event does not happen is one minus the probability that it does happen. 4. **Example:** Suppose the event occurred 30 times out of 50 trials. Calculate: $$P(\text{event}) = \frac{30}{50} = 0.6$$ Then: $$P(\text{not event}) = 1 - 0.6 = 0.4$$ 5. **Explanation:** The event has a 60% chance of occurring based on the experiment, and a 40% chance of not occurring. This method helps us estimate probabilities from real data by counting occurrences and using the complement rule for the opposite event.