Applied Statistics for Neuroscience

2 credits · Graduate

This intermediate-level statistics class is tailored for PhD students in neuroscience and related fields, emphasizing a collaborative learning approach. Led by a GSI with faculty oversight, students actively engage in discussions, presentations, and exercises. The course focuses on understanding statistical methods' applications, assumptions, and limitations in neuroscience research, as well as their implementation in Python. Covering traditional statistics and data modeling, students learn to analyze data and design experiments effectively. It's a dynamic format that requires students' active participation and commitment to reading and practical exercises.