This is an intermediate statistics course focused on fundamentals of statistical inference and applied data analysis tools. Emphasis on thinking statistically, evaluating assumptions, and developing practical skills for real-life applications to fields such as medicine, politics, education, and beyond. Topics include t-tests and non-parametric alternatives, analysis of variance, linear regression, model refinement and missing data. Students can expect to gain a working knowledge of the statistical software R, which will be used for data analysis and for simulations designed to strengthen conceptual understanding. This course can be counted toward the major or minor in Mathematics, Statistics, Data Science, Economics, Environmental Studies, Psychology or Neuroscience. Students who earned a Quantitative Analysis Institute Certificate are not eligible for this course.

Units: 1

Max Enrollment: 24

Crosslisted Courses:

Prerequisites: Any introductory statistics course (BISC 198, ECON 103/SOC 190, STAT 160, STAT 218, POL 299, PSYC 105 or PSYC 205).

Distribution Requirements: MM - Mathematical Modeling and Problem Solving

Typical Periods Offered: Fall

Semesters Offered this Academic Year: Fall

Notes: