And then we want to calculate a p value. And just as a bit of review, a p value is the probability of getting a result at least as extreme as this one if we assume our null hypothesis is true. And in this particular case, because she suspects that not 10% are getting the exceeds expectations, this would be the probability of your sample statistic being less than or equal to the one that you just calculated for a sample size of n equals 10 given that your null hypothesis is true. And if this p value is less than your predetermined significance level, maybe that's 5% or 10%, but you'd want to decide it ahead of time, then you would reject, you would reject your null hypothesis because the probability of getting this result seems pretty low, in which case it would suggest the alternative. But then if the p value is not less than this, then you wouldn't be able to reject the null hypothesis. But the key thing, and this is what this question is all about, in order to feel good about this calculation, we need to make some assumptions about the sampling distribution. We have to assume that it's reasonably normal, that it can actually be used to calculate this probability, and that's where these conditions come into play.