A manufacturer of bottled tea runs a promotion in which consumers can win a free bottle of tea if the cap of the bottle says "Winner.” The manufacturer claims that 1 in 5 bottles is a winner. A store owner notices that several of the first bottles of tea sold were winners. Suspecting the manufacturer’s claim is false, the store owner decides to randomly select 10 bottles of tea from the next shipment from the manufacturer. She is again surprised when 4 of the bottles are winners. Assuming the manufacturer’s claim is true, she simulates 100 values of selecting winners in 10 bottles. The dotplot displays these simulated proportions. Using the dotplot and the proportion of winners in the store owner’s sample, is there convincing evidence that the manufacturer’s claim is wrong?

Yes, because a proportion of 0.4 or more occurred 25 out of 100 times, the sample proportion of winners is statistically significant and there is convincing evidence that the manufacturer’s claim is false.
Yes, because a proportion of 0.4 or less occurred 75 out of 100 times, the sample proportion of winners is statistically significant and there is convincing evidence that the manufacturer’s claim is false.
No, because a proportion of 0.4 or more occurred 25 out of 100 times, the sample proportion of winners is not statistically significant and there is not convincing evidence that the manufacturer’s claim is false.
No, because a proportion of 0.4 or less occurred 75 out of 100 times, the sample proportion of winners is not statistically significant and there is not convincing evidence that the manufacturer’s claim is false.