Listed in: Mathematics and Statistics, as STAT-136
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Shu-Min Liao (Section 01)
This is an interactive course designed to help students understand inequities in mental health issues via statistics. We will begin the course by examining mental health stigmas and practice self-care exercises to train our “happy muscles” together. We will discover the scientific evidence behind those self-care practices and explore existing racial disparities in mental health care systems, while learning about important statistical concepts and mastering our data analysis skills using R (a popular statistical software package). Statistical topics covered include descriptive statistics, visualization, study design, simulation-based inferences, and multiple regression. Students are expected to play an active role in co-creating the course and co-building an inclusive learning community with their peers and the professor. Course components include weekly reading and discussion, regular self-reflections and problem sets, and collaborative work in groups. We will use an OER (Open-Educational-Resources) textbook in this course. No prior experience with statistical software is expected.
This course is an alternative to STAT135 (Introduction to Statistics via Modeling) with a special focus on mental health issues. Students may not receive credit for both this course and STAT 111 or STAT 135. Limited to 24 students. Fall semester. Prof. Liao.
How to handle overenrollment: Priority for first-year students, then sophomores.
Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: weekly reading and discussion, regular self-reflections and problem sets, and collaborative work in groups. We will use an OER (Open-Educational-Resources) textbook in this course. No prior experience with statistical software is expected.