I am taking a course on statistics and I see this:
I don't get why there need to be 10 successes and 10 failures in the sample. What's the intuition behind why this needs to be a condition for the sampling distribution of sample proportions to be normal. Is it because if the probability of success was say 95% and n was 100, it's likely that sometimes, samples will produce a number of failures == 0? If that's the case, the probability of that sample will be 100%? Why wouldn't the sampling distribution be normally distributed around 95%?