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 machine learning and artificial intelligence.

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 machine learning and artistic intelligence.

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.

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.