Recently, information system researchers have become used to handling big data comprising more than 10,000 observations. Researchers using statistical inference in such very large samples have often found that p-values quickly go to zero as the sample size increases. This study investigates the p-value problem with large sample via central limit theorem. The results revealed that strong positive dependency of big data may be the main cause behind the problem.