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 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 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.

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).

Instructor: Pattanayak

Distribution Requirements: MM - Mathematical Modeling and Problem Solving

Typical Periods Offered: Fall

Semesters Offered this Academic Year: Fall

Notes: