Binary data is information that comes from events with only two possible outcomes: success (represented by 1) or failure (represented by 0). Sometimes, the variance of successful events can be higher than expected, causing an overdispersion issue. To tackle this, researchers used the Random-Clumped Binomial distribution method. They applied this method to student data and found that it effectively addressed the overdispersion problem. The likelihood of students not graduating in certain courses was calculated to be 0.1016, with a correlation between grades in different courses of 0.5661.