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, multiple comparisons, analysis of variance, linear regression, model refinement, missing data, and causal inference. 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, offered through Wellesley's Quantitative Analysis Institute, can be counted as a 200-level course toward the major or minor in Mathematics, Statistics, Economics, Environmental Studies, Psychology or Neuroscience. Students who earned a Quantitative Analysis Institute Certificate are not eligible for this course.
Max Enrollment: 25
Prerequisites: Any introductory statistics course (any one of BISC 198, ECON 103/SOC 190, MATH/STAT 101, QR 180, STAT 160, STAT 218, POL 299, or PSYC 205).
Distribution Requirements: MM - Mathematical Modeling and Problem Solving
Typical Periods Offered: Fall
Semesters Offered this Academic Year: Fall