The course is conducted in English。

This course introduces students to the core concepts and methods of statistics, with a focus on learning how to use data effectively in the face of uncertainty. Key topics include data visualization, descriptive statistics, probability, statistical inference, and linear regression. Emphasis will be placed on building intuition and practical understanding rather than mathematical rigor.

Students will develop the skills to make sense of data, draw meaningful conclusions, and communicate results with clarity and confidence. The tools and thinking developed in this course are valuable for making informed decisions and conducting research across a wide range of disciplines. They also form the foundation of many modern applications, including data science, machine learning, and artificial intelligence.

This is an English-medium course. English must be used at all times in class, including for homework, quizzes, exams, and all other course-related work. We will use NTU COOL to share course materials and announcements. You are expected to check both NTU COOL and your school email daily to stay informed and up to date. All cell phones and other communication devices should be turned off or silenced during class. Students may be cold-called to answer questions. Active and voluntary participation in discussions is highly encouraged.

Diez, D. M., Barr, C. D., & Çetinkaya-Rundel, M. (2019). OpenIntro Statistics (4th ed.). The textbook is available as a free PDF download at https://leanpub.com/openintro-statistics.