Evaluating Models with Data and Simulation Practice Test

A survey company claims that $P(\text{supports the proposal})=0.40$ for the population. They survey 80 people and find 28 support the proposal. You simulate 100 samples of 80 people each using $P=0.40$. In the simulations, 41 out of 100 samples had 28 or fewer supporters ("as extreme or more extreme" means $\le 28$). Which conclusion is most reasonable?

A factory claims 5% of its lightbulbs are defective, so $P(\text{defective})=0.05$. A quality inspector checks 60 bulbs and finds 9 defective. You decide to use simulation: repeatedly generate 60 bulbs with a 0.05 chance of being defective and count how often you get 9 or more defectives ("as extreme or more extreme" means $\ge 9$). If your simulation shows that 0 out of 200 simulated runs had 9 or more defectives, would this result cause you to question the model? Why?