Designing the Experiment: The study program under evaluation is designed to improve students' chances of passing the exam. The probability of success (passing the exam) is denoted as "p", while the probability of failure is denoted as "q", where "q = 1 - p". In this experiment, the focus is on determining the effectiveness of the study program. Data collection involves observing the number of students who pass the exam (successes) out of the 100 students who participate in the study program (trials). By analyzing this data, educators can assess the likelihood of student success and adjust the study program as needed to improve outcomes. Application of Binomial Theorem: The binomial theorem is applied to calculate the probability of a given number of successes (students passing the exam) in the fixed number of trials. For instance, if we want to find the probability that exactly 60 out of 100 students will pass the exam, we use the binomial probability formula: P(X = k) = (n choose k) * p^k * (1 - p)^(n - k) where: - P(X = k) is the probability of exactly k successes in n trials. - (n choose k) is the binomial coefficient. - p is the probability of success on a single trial. - n is the number of trials. - k is the number of successes. Conclusion: This binomial experiment meets all the necessary characteristics, making it a valuable tool for assessing educational interventions. By analyzing the outcomes, educators can make data-driven decisions to enhance student succes