The teaching field of this study is the course “Statistical Inference in Data Science.” This course is required for junior and senior students taking the Biostatistics and Health Informatics module in the Department of Public Health. The statistical inference will introduce the basic concepts and theories of statistical methods, and the contents are abstract mathematical and statistical theories. However, students have difficulty learning theories because of insufficient prior knowledge of mathematics. In addition, nowadays, students are digital natives. Their cognitive processing belongs to shallow thinking, and their learning styles have changed. As a result, they have difficulty understanding the abstract concepts of statistical theories, resulting in low learning effectiveness, weak motivation, and passive attitudes. To improve these problems and the plight of the teaching site, in this study, we adopted an action research method and utilized experiential learning with problem-based learning and information technology integrated into instruction. Students are guided to explore the role and importance of statistical theory from real-world data analysis and applications. We tried to connect the statistical theories and real-world data analysis.