OBFW Publishers A media report claims that 50% of U.S. teens with smartphones feel addicted to their devices. A skeptical researcher believes that this figure is too high. She decides to test the claim by taking a random sample of 100 U.S. teens who have smartphones. Only 40 of the teens in the sample feel addicted to their devices. Does this result give convincing evidence that the media report's 50% claim is too high? To find out, we want to perform a simulation to estimate the probability of getting 40 or fewer teens who feel addicted to their devices in a random sample of size 100 from a very large population of teens with smartphones in which 50% feel addicted to their devices. Let 1 feels addicted and 2 = doesn't feel addicted. Use a random number generator to produce 100 random integers from 1 to 2. Record the number of 1's in the simulated random sample. Repeat this process many, many times. Find the percent of trials on which the number of 1's was 40 or less. Does the problem describe a valid simulation design? Justify your answer. No, it does not describe a valid simulation design. The simulation should let 0-3 = feels addicted and 4-9= doesn't feel addicted. No, it does not describe a valid simulation design. It does not specify that you should ignore repeating numbers when choosing integers from the random number generator. No, it does not describe a valid simulation design. It does not specify how many times to repeat the simulation. Yes, it describes a valid simulation design. By letting 1 = feels addicted and 2 = doesn't feel addicted, the simulation would model the claim that 50% of U.S. teens with smartphones would feel addicted to their devices. No, it does not describe a valid simulation design. The simulation should let 0-5 = feels addicted and 6-9 = doesn't feel addicted.